Dr Kerry Hempenstall, Senior Industry Fellow, School of Education, RMIT University, Melbourne, Australia.

Each of my articles can be downloaded as a PDF file at https://tinyurl.com/y6vat4ut

Response to Intervention (RTI) and its subsequent close relative - Multitier System of Supports (MTSS) are popular, if controversial, initiatives developed primarily in the USA. As yet, they are less well known in general education in Australia. MTSS broadened the focus of RTI beyond academics to include other elements, such as social and emotional supports for struggling students.

In Australia, RTI and MTSS are gradually becoming better known, perhaps due to the increased attention to accountability in recent times. The unsatisfactory national NAPLAN and international PISA assessments are leading to pressure being placed on schools to lift student performance. RTI may be adopted by school systems as a means of providing data demonstrating levels of effectiveness, and a means of providing a direction for schools’ responses to that data. The expectation across the education community that general education teachers provide evidence-based instruction and regular progress monitoring is increasingly evident in policy documents, though classroom practice has yet to significantly reflect this change.

Response to Intervention is a term that first came to prominence in special education circles in the USA around 2004. Its initial focus was on a better means of the identification of learning disabilities (LD), an issue that had been problematic for many years. The core concern was that the various definitions of learning disabilities were exclusionary – they implied that a person must have a specific internal learning problem when all other likely causes of low achievement have been ruled out.

Before examining Response to Intervention, it is useful to consider the special education context in which it arose.

The term learning disabilities is attributed to Kirk (1963), who wrote:

“I have used the term "learning disabilities" to describe a group of children who have disorders in the development of language, speech, reading, and associated communication skills needed for social interaction. In this group, I do not include children who have sensory handicaps such as blindness, because we have methods of managing and training the deaf and blind. I also excluded from this group children who have generalized mental retardation” (p. 2–3).

Subsequently, other variables to be excluded included serious emotional disturbance, low English language proficiency, low intelligence, deprivation during the pre-school years, and inadequate teaching. Exclusionary definitions are usually unsatisfactory for a number of reasons, and there was an obvious need for an inclusionary definition that could specify the presence (rather than simply the presumption) of a inner learning disability beyond being simply a low achiever. This need was seemingly met in the 1970’s by the introduction of the discrepancy model that highlighted unexpected underachievement as the characteristic that separated the run-of-the-mill low achiever from those with these mooted learning disabilities. The diagnosis of a learning disability required a discrepancy between individuals’ measured IQ and their achievement in a given academic domain. Surely if a child is of at least average intelligence, their achievements should be commensurate with that intelligence? The presumption was that the low achievement was due to a modular central nervous system dysfunction affecting only one or few academic areas. This contrasts with the low achievement expected right across the curriculum for those struggling students with below average intelligence. This discrepancy notion and its related assessment tools had intuitive appeal, appeared straightforward to implement, and, until recently, has been the main method of diagnosing LD for many years. Because a diagnosis of learning disability provides access to additional funding in the US and in some states of Australia, quite an industry developed in providing assessments for diagnosis.

“SLD is the most prevalent disability category in IDEA. In the 2017–2018 academic year, 43% of all children and youth who received special education and related services in the public school system—or 2.3 million students—had SLD as their primary disability (National Center for Education Statistics 2018).” (p.86)

Kranzler, J. H., Yaraghchi, M., Matthews, K., & Otero-Valles, L. (2020). Does the response-to-intervention model fundamentally alter the traditional conceptualization of specific learning disability? Contemporary School Psychology, 24, 80-88.

There have, however, been many criticisms of the discrepancy definition of LD (Carnine, 2003; Siegel, 1989, 1992; Stanovich, 1991). It has been called a wait-to-fail model, as a child will have experienced several struggling years at school before a discrepancy can be detected with this approach. This does usually occur before Year 3 or 4, when a range of other secondary difficulties have been added to the original problem (Fletcher et al., 1998). Given the appreciation that the best opportunity to prevent later problems is to intervene early, children’s progress was jeopardized by the very process designed to assist them.

Further, when comparisons were made between IQ-discrepant and nondiscrepant struggling readers no differences were found in their likely educational outcomes, the characteristic underdeveloped skills related to the reading processes, or the outcomes of interventions (Stuebing et al., 2002).

“ … the finding that nondiscrepancy-defined (i.e., low IQ) poor readers and discrepancy-defined poor readers (i.e., those with IQs in the average to above average range) do not acquire reading skills in a fundamentally different manner suggest that IQ is largely irrelevant to defining dyslexia (Aaron, 1997), other than in applying exclusionary criteria concerning intellectual impairment.”

Tunmer, W., & Greaney, K. (2010). Defining dyslexia. Journal of Learning Disabilities, 43(3), 229–243.

“In summary, cognitive differences between children with reading disabilities who do or do not also have an aptitude achievement discrepancy, all seem to reside outside of the word-recognition module. These differences are consistently revealed on memory tasks and in academic domains other than reading, and they are present but somewhat attenuated in language processing tasks. With regard to word recognition processes themselves, children with and without a discrepancy show performance patterns that are remarkably similar. Both show pseudoword reading performance below that expected on the basis of their WRAT-R Reading levels. Both show performance on phonological coding tasks not involving production of a spelling or pronunciation (phonological choice task and pseudoword recognition) that is commensurate with their reading levels but inferior to the reading level of chronological age controls.” (p. 47-48)

Stanovich, K. E., & Siegel, L. S. (1994). Phenotypic performance profile of children with reading disabilities: A regression-based test of the phonological-core variable-difference model. Journal of Educational Psychology, 86(1), 24-53.

Other problems with the concept included the wide variety of definitions of LD - this means that assessment and identification were impossible to standardise. Many professions determined their own idiosyncratic methods, for example, some optometrists labelled as LD any child with a visual tracking problem, whereas a speech pathologist may emphasise deficient language processes.

“The long-entertained theory that LD could be measured psychometrically via an aptitude–achievement discrepancy has been soundly disputed as inadequate theory (Büttner & Hasselhorn, 2011) as well as empirically discredited (Aaron, 1997; Fletcher et al., 2002; cf. Johnson et al., 2010; Swanson, 2008)” (p.27).

Scanlon, D. (2013). Specific learning disability and its newest definition: Which is comprehensive? And which is insufficient? Journal of Learning Disabilities, 46(1) 26–33.

Differing definitions make research findings non-comparable with other research findings. It is often proposed that LD is a heterogeneous category, implicating one or more of: receptive language, expressive language, reading skills, reading comprehension, written expression, maths calculation, maths reasoning. Thus it is too broad a category to be useful educationally (Gresham, 2001). Lyon described the state of the LD field scathingly "Learning disabilities have become a sociological sponge to wipe up the spills of general education … It's where children who weren't taught well go." (Lyon, 1999)

Consider, as an example, dyslexia. In the discrepancy approach, dyslexia is assessed by the presence of a gap between a child’s intelligence and his reading attainment. However, it is now increasingly recognized that intelligence is far from perfectly correlated with reading. Stanovich (1992) calculated a median correlation of 0.34 across 14 studies involving 26 measures whose correlations ranged from 0.10 to 0.66. The range of correlations relate to the choice of intellectual assessment instruments and reading tests. The lower figures are more likely when the reading measure has a strong word-decoding emphasis, and the higher figures when comprehension is the major focus. Given this only moderate correlation, any intelligence-reading discrepancy may be more reasonably considered a normal statistical variation than evidence for a specific neurological deficit. In other words, there is no rule that intelligent people must find reading easy. The reason, of course, is that phonemic awareness is more strongly correlated with reading than is intelligence - and phonemic awareness does not necessarily parallel intelligence (Morris et al., 2012; Tunmer & Greaney 2010).

Further, it is noted that the development of literacy is closely intertwined with the development of intelligence (Stanovich, 1993). That is, the continued normal development of intelligence may rely on an adequate volume of reading. Vocabulary development and higher-order comprehension skills are best advanced through reading (Nagy & Anderson, 1984) once the beginning stages are passed. Thus, as children with reading difficulties grow older, their lack of reading could be expected to reduce the initial gap between measured intelligence and attainment. Over time dyslexic students' measured intelligence may more closely resemble that of their garden-variety colleagues, as problems additional to the phonological core develop (Stanovich, 1988). Sadly, the intelligent under-achiever may appear to become less intelligent because of our educational system's failure to adequately address his needs at the critical early stage. In a bizarre twist, the discrepancy is likely to diminish over time such that the child may lose his LD status, and thereby, any funding allocated for learning disabilities.

The other major problem with discrepancy-defined dyslexia is that a different group (between 2%-35% of the population) is described by employing different intelligence tests, and through different subtest analyses. For example, there was debate over which specific IQ test, and whether verbal or performance (or both) scales should be used - the use of one over the other certainly defines a different group as dyslexic. There is also disagreement over how large a discrepancy (e.g., 1, 1.66, or 2 SD) is needed for a diagnosis of dyslexia; disagreement over the minimum general intelligence level needed for a dyslexia classification; and, over the type of reading test chosen to define the reading deficit. Each of these decisions leads to a different population being defined.  Given the slippery nature of such assessment choices, it is unsurprising that such a model is falling from favour, although it still has currency in some special educational circles (Hale et al., 2010). For parents seeking funding assistance for their child in the USA, the advice has been to see as many professionals as you can afford - someone, somewhere will be prepared to classify your child as LD, with the attendant additional support that classification entails.

The decline of the discrepancy model

“Originally, the U.S. Individuals with Disabilities Education Act required the use of the discrepancy model to identify those students who needed assistance for a learning disability. In the 1990s, studies showed that children who had difficulty learning to read had difficulty with phonological awareness — matching printed letters of the alphabet to the speech sounds that those letters represented. Based on these findings, the reauthorization of the Act dropped the requirement that school systems use the discrepancy model. Many school systems, however, retained the discrepancy model as a means to classify students needing special educational services in reading.”

National Institute of Child Health and Human Development (2011). NIH-funded study finds dyslexia not tied to IQ. Research on brain activity fails to support widely used approach to identify dyslexic students. https://www.nih.gov/news-events/news-releases/nih-funded-study-finds-dyslexia-not-tied-iq

The discrepancy definition has declined in use over the past 10 years, as research findings found their way into educational policies at national and state levels. However, the relative ease of discrepancy assessment for those charged with identifying learning disabilities makes the demise of the discrepancy model difficult to complete. For example, there remain psychologists who continue to ignore the evidence when requested to assess students’ LD status.

“Taken as a whole, results of this study indicate that school psychologists differ widely in their approach to intelligence test interpretation, particularly for the identification of SLD, and that these differences are only modestly related to personal characteristics, level and accreditation/approval, status of professional training, and state regulations for SLD eligibility determination. Results of our study, however, also revealed the presence of a large research-to-practice gap, particularly as it concerns the use of ipsative analysis and the PSW methods for the interpretation of intelligence tests.” (p.9-10)

Kranzler, J.H., Maki, K.E., Benson, N.F., Floyd, R.G., & Fefer, S.A. (2020). How do school psychologists interpret intelligence tests for the identification of specific learning disabilities? Contemporary School Psychology, 24, 445-456.

Where to now?

The term LD itself is often considered now as of little benefit because it does not lead to interventions specific to the cause of the student’s problem. As for younger students yet to confront learning the requisite school skills, social justice demands that best educational practice must be supplied to all at-risk (or currently failing) students - intelligent or otherwise.

For failing students, strong evidence supports systematic, intensive teaching (Gersten et al., 2008; Swanson & Hoskyn, 1998; Torgesen, 2003): avoiding ambiguity in communication, employing carefully designed and trialled sequences of instruction, supplying ample massed and spaced opportunities for practice, ensuring careful monitoring and feedback until mastery is achieved, and further extended independent practice to obtain fluency, incorporation, and generalisation. Such effective learning programs tend to be effective for all classes of learners, not simply for those with some presumed idiosyncratic learning style (Goyen, 1992).

Years of research on learning disability had emphasised within-person factors to explain the unexpected difficulty that academic skill development poses for students with LD. Unfortunately, the impact of the quality of initial and subsequent instruction in ameliorating or exacerbating the outcomes of such disability has received rather less exposure until more recently as the criticisms of the discrepancy model have been increasingly acknowledged as valid.

“This problem persists to this day. In short, there is little scientific or professional support for the continued use of an IQ-achievement discrepancy in identifying children with SLD. ... To this we would add that IQ does not predict how well students with SLD learn to read or what their educational prognosis might eventually be (Vellutino et al., 2000). The fact is that we have better and more direct measures of reading achievement and individual differences in the ability to learn to read that are more closely related to the key phonological core constructs which have been shown to underlie reading ability. Such measures are also more time efficient than most measures of intelligence and they are more highly predictive of response to reading interventions than are measures of intelligence (Gresham, 2002; Vellutino et al., 2001; Wagner, Torgesen, & Rashotte, 1999)” (Gresham & Vellutino, 2010, p. 204 - 205).

Additionally, the 2020 survey of What’s Hot in Literacy noted that 51% of teachers considered they had inadequate strategies for academic intervention, and 48% noted inadequate or incorrect diagnosis of reading disabilities. 71% believe that variability of teacher knowledge and effectiveness is one of the greatest barriers to equity in literacy.

Response to Intervention

Increasingly, a different approach known as Response to Intervention (RTI) is supplanting the discrepancy approach, although there are also criticisms of this new emphasis (Baskette, Ulmer, & Bender, 2006). For example, some have argued that a hybrid of RTI and discrepancy approaches offer the optimal solution for assessment and intervention in LD (Hale et al., 2010).

While this debate over special education continues, the RTI model has found another, much broader, niche in education – as a framework for providing early identification of potential problems, and better instruction to students in general education, thereby reducing the demand for expensive special education services.

“Response to Intervention integrates assessment and intervention within a multi-level prevention system to maximize student achievement and to reduce behavioural problems. With RTI, schools use data to identify students at risk for poor learning outcomes, monitor student progress, provide evidence-based interventions and adjust the intensity and nature of those interventions depending on a student’s responsiveness, and identify students with learning disabilities or other disabilities” (National Center on Response to Intervention, 2010).

RTI derives from the application of the same scientific method used to study natural phenomena. The approach proceeds from a description of the problem, followed by the development of a hypothesis as to cause. A procedure is selected based upon the hypothesis, and the intervention is commenced, while data is then regularly collected, leading to a conclusion about the intervention’s effectiveness. This is a cyclical process that continues until the objective is attained for a given student.

There are a number of assumptions underlying the RTI framework. All students can learn, and the learning is strongly influenced by the quality of instruction. In fact, it is argued that there is a predictable relationship between instructional quality and learning outcomes. It is expected that both general classroom programs and additional specific interventions will be evidence-based to provide greater instructional quality. Assuming the curriculum content is evidence-based, another manipulable causal variable will be intensity of the intervention. This includes varying academic engaged time, lesson frequency, program duration, group size, engagement, lesson pacing, mastery criteria, number of response opportunities, correction procedures, goal specificity, and instructor skill.

RTI advocates argue that the model is useful for both beginning and remedial instruction. The sequence for a school or class involves all beginning students being screened for the pre-skills that evidence highlights are necessary for success in the domain in question. Appropriate universal screening tools are available at the National Center for RTI website (rti4success.org), and in numerous other sites. The derived data allow judgements of the students' current performance, by comparing them to a criterion-referenced benchmark. If scores are at or beyond the benchmark, students are judged to be satisfactorily managed within the general classroom program. If a student’s scores fall below the benchmark then general classroom instruction is considered insufficient for the child’s needs, and requires supplementation.

Most of the studies involving RTI have focused upon reading, but the breadth of application is increasing. All students are provided with research-validated instruction from the beginning, and are regularly re-assessed, at least three times per year. Additionally, student behaviour is assessed because of the close links (and possible reciprocal causation) between early academic success and student behaviour (Algozzine, McCart, & Goodman, 2011). This widening of RTI emphasis has led to the introduction of another descriptor – Multi-tier System of Supports (MTSS).

“More recently, multitier system of supports (MTSS) has become influential in educational policy. It provides an overarching framework that usually includes the three levels of RTI for struggling students. Extending beyond academics, its reach includes social and emotional supports, such as behavior intervention plans, and is intended to be applicable to all students.”

Greenwood, C. R., Carta, J. J., Schnitz, A. G., Irvin, D. W., Jia, F., & Atwater, J. (2019). Filling an information gap in preschool MTSS and RTI decision making. Exceptional Children, 85(3), 271–290. https://doi.org/10.1177/0014402918812473

Any student making slow progress is provided one or more research-validated interventions additional to the regular class program. For this group, academic progress is monitored more frequently to detect change using Curriculum Based Measures (CBM).

CBM is a means of assessing students’ basic skills. The intent is to provide a cheap, simple system that can be regularly used to measure students' initial skills and also their growth in performance, which is a proxy for the effectiveness of the instructional program. The tests have norms, so they can be used to judge which students are at risk. As an example, reading may be assessed using reading accuracy and speed on grade level text over a one minute, several times a year for average students, and weekly or fortnightly for struggling students. Graphing of progress aids decision making about progress. The reliability and validity of this type of assessment are well established (Reschly, Busch, Betts, Deno, & Long, 2009; Seungsoo, Dong-Il, Lee Branum-Martin, Wayman, & Espin, 2012). There are numerous examples available freely at Intervention Central (http://www.interventioncentral.org/cbm_warehouse). One caveat about their use is raised by Ball and Christ (2012) who warn against making decisions about student attainment growth based on too few data points. For this reason, decisions concerning any change of intervention are delayed until at least 6 data points are collected (Stecker & Lembke, 2007).

CBM probes have been particularly used to measure phonemic awareness, oral reading fluency, maths computation, writing, and spelling skills. In adding a behavioural component to RTI, two major components have been emphasized. One involves daily behaviour report cards which are teacher rating forms for evaluating a student’s behaviour. The other which the Solomon, Klein, Hintze, Cressey, and Peller (2012) meta-analysis highlighted is direct observation of target students’ behaviour as a means of data collection. Often, an external observer visits the classroom to observe and rate a student’s rates of on-task and academically engaged behaviours.

Tiers not tears?

Figure 1

Response to intervention tiers (Sugai, Simonsen, Coyne, & Faggella-Luby, 2007)

RTI/MTSS is often characterized as a 3 Tier approach applicable to both academics and behaviour aiming at prevention and amelioration of educational problems.

Tier I: Evidence-supported instruction is provided to all students within the classroom, and may be sufficient for 80-90% of the class. This means that all teachers of beginning reading in the school employ methods as chosen in conjunction with the school’s RTI team. The decision as to which actual reading method is chosen is made on the basis of investigating what has been shown to be effective. For example, a school elects to introduce a specific whole class program, such as Jolly Phonics, or Reading Mastery. It doesn’t necessarily mean that all teaching occurs in the whole class format; there may also be flexible grouping and differentiation based upon collected data. A behavioural example would be a teacher commencing a classwide behaviour strategy, such as the Good Behaviour Game.

Tier II: An individualized plan is designed for students who are deemed to need further additional support (perhaps 15% of the class). An example would be to offer supplemental peer tutoring in reading to increase some students’ low reading fluency. The interventions would normally be in small groups and occur in addition to the regular program. In the behaviour domain, an example might be a teacher systematically acknowledging displays of appropriate behavior, including contingent and specific praise to better engage a group of frequently off-task students.

Tier III: Intensive Intervention is supplied to students whose intervention needs are greater than these (maybe 5% of the class). Typically, these will be made available to students when the careful monitoring of their Tier 11 intervention indicates less progress than is expected. This may include more in depth assessment leading to more intense small group or individual instruction. In the behaviour domain, an example might be a development of a home-school contract for an individual with significantly challenging behaviour following a functional behaviour assessment.

“The components of a multi-level prevention system include universal screening, progress monitoring, and data-based decision making (American Institutes for Research, 2013).”

American Institutes for Research. (2013). Using a Response to Intervention framework to improve student learning; A pocket guide for state and district leaders. https://www.air.org/resource/using-response-intervention-rti-frameworkimprove-student-learning

If despite several well-designed and implemented interventions, there is a continued failure to respond to intervention – this may be viewed as evidence of an underlying learning disability if such a diagnosis is sought. Hence a major difference between using a discrepancy definition to diagnose a LD is that the RTI model exhausts all the best teaching practices before deciding on an LD classification. Only a student who is still struggling in Level 3 is a candidate for diagnosis.

There has been criticism of RTI as the replacement diagnostic tool for identifying learning disabilities. For example, Kranzler et al. (2020) and Reynolds (2009) found that using RTI overidentifies as LD too many low ability students.

“Thus, the prevalence of a weakness in general cognitive ability in students with SLD who have been identified in the RTI model is almost twice as high as that in the general population of same-age peers.” (Kranzler et al. 2020, p.84)

“Because RtI is a relatively new method to identify SLDs, there is far less research examining this method compared to AAD. Arguably, there are several advantages to RtI, including reliance on low-inference decisions because of the direct link between assessment data and treatment (Christ & Arañas, 2015; Salvia, Ysseldyke, & Bolt, 2012) and increased reliability due to the use of multiple datapoints in decision making (Fletcher, 2012). However, some argue that RtI does not truly identify SLDs due to the change in conceptualization of unexpected underachievement, because there is no comparison to cognitive ability (Kavale & Spaulding, 2008). Moreover, differences in nonresponse thresholds can result in different SLD identification decisions (Barth et al., 2008) that may not be stable over time (Brown Waesche, Schatschneider, Maner, Ahmed, & Wagner, 2011), and there is no convincing evidence to support commonly implemented decision rules regarding student progress (e.g., three data points above/ below expected growth line; Ardoin, Williams, Christ, Klubnik, & Wellborn, 2010; Burns, Scholin, Kosciolek, & Livingston, 2010). There are also further challenges associated with monitoring student progress and implementing interventions within RtI. Administration of two curriculum-based measures (CBMs) per week for 10 weeks may also be needed to accurately and reliably estimate slope and to guide even low-stakes decisions (Ardoin & Christ, 2009), which may be unrealistic to implement in authentic school contexts.” (p.344)

Maki, K.E., Barrett, C.A., Hajovsky, D.B., & Burns, M.K. (2020). An examination of the relationships between specific learning disabilities identification and growth rate, achievement, cognitive ability, and student demographics. School Psychology, 5, 343-352.

Be that as it may, the major benefit from RTI is likely to be not so much as a tool for diagnosis, but rather for its capacity to quickly identify educational hurdles regardless of cause, and to specify, monitor, and adapt interventions that address them.

“The Response to Intervention (RtI) model is sweeping the country, changing the way children’s educational needs are recognized and met. RtI was introduced through special education legislation as part of the Individuals with Disabilities Education Improvement Act (IDEA, 2004) and offered an alternative approach for identifying students with learning disabilities (Bender & Shores, 2007). Its impact today, however, has moved well beyond this initial goal (Council for Exceptional Children, 2007). RtI is designed to bring together information about each child’s strengths and needs with evidence-based instructional approaches that support the child’s success (Kirk, Gallagher, Coleman, & Anastasiow, 2009). Although RtI is still an emerging practice, it hinges on a collaborative approach to recognizing and responding to the needs of each child. This collaborative approach requires educators to think about the child first and match the supports and services to his or her strengths and needs. The allocation of resources follows the supports and services, promoting synergy rather than increasing fragmentation, as the needs of the child increase. In other words, within the RtI model, when the child’s needs are the most intense, educational resources can be combined to 2provide greater support. This use of resources differs significantly from traditional approaches where, as the needs of the child intensify, the supports and services become more separate and rigidly codified with clear boundaries delineating the allocation of resources.” (Hughes et al., 2011 p. 1)

In summary, there are three core concepts underpinning RTI. Scientific, evidence-based interventions are to be used in the general education classroom; brief data-based measurement of student reactions to these interventions is regularly performed; and this RTI data is used to determine and evaluate future instruction (Hazelkorn, Bucholz, Goodman, Duffy, & Brady, 2011).

The response to RTI

The experience in the USA was that initially general education journals published very little on RTI whilst special education journals published a great deal (Hazelkorn, Bucholz, Goodman, Duffy, & Brady, 2011). In more recent times, as RTI has become more accepted, generalist journals and various websites are now publishing a plethora of articles on RTI. Increasingly, so too are education policy makers. A simple Google search reveals 413,000,000 hits.

In 2012, the International Reading Association included Response to Intervention in its annual list of What’s Hot and What’s Not in Education, rating it as Very Hot (Cassidy, Ortlieb, & Shettel, 2012). Hot means that the topic has received a great deal of attention by education researchers and practitioners during the preceding year. The Reading Today surveys of 25 prominent literacy leaders have considered RTI to be Hot since 2007. A simple Google search revealed 117,000,000 hits in 2012 and 442, 000,000 in 2021.

“Many professional organizations and advocacy groups like the National Association of State Directors of Special Education, National Association of School Psychologists, and the National Center for Learning Disabilities (NCLD) support the Response-to-Intervention Model (RTI).They embrace RTI as a science-based practice and have made RTI knowledge and practice part of their professional expectations and advocacy (Charles and Judith, 2011).” (p. 2033)

Eissa, M.A. (2020). Effects of RTI on letter naming and spelling among kindergarteners at risk for reading failure. Elementary Education Online, 19(4), 2032-2041. doi:10.17051/ilkonline.2020.763216

“PBIS [Positive Behavioral Interventions and Supports] has been consistently correlated with reductions in student exclusion including suspensions, expulsions, poor attendance, and high school dropout rates. However, school-wide strategies that do not specifically involve effective instruction in academic areas are unlikely to result in increased academic achievement. To address this reality, multi-tiered systems of support (MTSS) involving tiered intervention for both academic and behavior have become commonplace. The Academic and Behavior Response to Intervention School Assessment (ASA) was developed to assess the fidelity with which schools are implementing MTSS for Reading, Mathematics, and behavior. Using the ASA to assess MTSS fidelity across 29 schools and four years, analyses were conducted to determine the predictive validity of sub-group domain scores. The question was whether ASA scores were predictive of student outcomes in terms of suspension and of state academic achievement scores in the areas of reading, math, and language. Results show that schools with higher fidelity in the behavior domain had significantly fewer suspension events than matched comparison schools. In comparison, higher fidelity in the reading domain was associated with more students at or above proficient on both the Language Mechanics measure and the Mathematics measure, but not in Reading; and higher fidelity in the math domain was also associated with more students at proficient or above on the Language Mechanics, but not in math or reading. Results are discussed in terms of implications for the further development of fidelity assessments and future research.” (p.308)

Scott, T.M., Gage, N.A., Hirn, R.G., Lingo, A.S., & Burt, J. (2019). An examination of the association between MTSS implementation fidelity measures and student outcomes. Preventing School Failure: Alternative Education for Children and Youth, 63(4), 308-316.

In 2012, the journal Psychology in the Schools published a special issue: “Addressing response to intervention implementation”. The articles pointed to the increasing breadth of application and popularity of the approach. It also highlighted the many issues still to be resolved, including “conceptual, procedural, and logistical questions related to RtI implementation” (Jones & Ball, 2012, p.207). There have been many implementation issues requiring attention from schools and districts as the model is not prescriptive regarding many of the details of RTI. It was also noted in the USA that a great deal of pre-service and in-service training was required to inform the various education practitioners, including teachers, administrators, reading coaches, school psychologists, speech therapists, special education teachers, and paraprofessionals.

The impact of RTI in education has shifted from a focus on special education to much broader applications. It is being employed in general education in areas such as preschool programs (Fox, Carta, Strain, Dunlap, & Hemmeter, 2010; Koutsoftas, Harmon, & Gray, 2009; VanDerHeyden, Snyder, Broussard, & Ramsdell, 2007), secondary grades (Pyle & Vaughn, 2012; Vaughn et al., 2008; Vaughn, Cerino, et al., 2010; Vaughn, Wanzek, et al, 2010), English Language Learners (Haager, 2007; Hernández Finch, 2012; McMaster, Kung, Han, & Cao, 2008; Orosco & Klingner, 2010; Xu & Drame, 2008), for challenging behaviour (Lane, Oakes, & Menzies, 2010; Mitchell, Stormont, & Gage, 2011; Solomon, Klein, Hintze, Cressey, & Peller, 2012), and for mathematics (Koellner, Colsman, & Risley, 2011; Lembke, Hampton, & Beyers, 2012).

The growth in acceptance has been considerable. In a USA survey in 2008, of the 44 states that responded, all reported that they either have or plan to introduce an RTI model (Hoover, Baca, Wexler-Love, & Saenz, 2008). In 2012, O’Connor and Freeman report that “implementation efforts have been occurring at some level in most school districts across the country” (p. 297). The 2011 RTI Adoption Survey (Spectrum K12, 2012) revealed that 94 percent of respondents in 2011 reported being at some stage of RTI implementation.

There has been a similar interest in the UK, although the terms waves of intervention is more commonly used. In the Primary National Strategy (2006), the waves were described as:

“Wave 1: High-quality inclusive teaching supported by effective whole-school policies

Wave 2: Wave 1 plus intervention designed to increase rates of progress and put children back on course to meet or exceed national expectations

Wave 3: Wave 1 plus increasingly personalised intervention to maximise progress and minimise gaps in achievement.” (p.7).

“Changes in RTI/MTSS implementation over the past decade reveal growing commitment among SEAs to support LEAs in implementing tiered systems of support. Although the terminology varied across states, our data were consistent with Bailey’s (2018) findings that in 2017 all states supported at least one initiative or provided guidance related to implementation of tiered systems of support in some capacity. This increased attention over the last decade is likely due to a number of factors, including the inclusion of multitier system of supports in federal and state legislation subsequent to IDEA 2004 and increased availability of federal funding and technical assistance through national centers.”

Berkeley, S., Scanlon, D., Bailey, T.R., Sutton, J.C., & Sacco, D.M. (2020). A snapshot of RTI implementation a decade later: New picture, same story. Journal of Learning Disabilities, 53(5), 332-342. doi:10.1177/0022219420915867

In 2020, the Journal of Learning Disabilities published a special issue in two parts: Special Series: Identifying and Serving Students with Learning Disabilities, including Dyslexia, in the Context of Multi-tiered Supports and Response to Intervention.

Criticism of RTI effectiveness

An evaluation by Balu et al. in 2015 cast doubt on the effectiveness of RTI on reading. However, there were design features, such as a lack of both random assignment and a control group, that limited the study’s validity.

“Because numerous well‐designed studies have documented the positive effects of high‐quality Tier 2 and 3 reading interventions (Gersten, Newman‐Gonchar, Haymond, & Dimino, 2017), critics have argued that the results of Balu et al.’s (2015) national evaluation speak more to widespread problems with RtI implementation than to the efficacy of the tiered interventions themselves (Arden, et al., 2017; Fuchs & Fuchs, 2017; Gersten et al., 2017). As reiterated by Arden et al. (2017) and others (e.g., Fixsen, Naoom, Blasé, Friedman, & Wallace, 2005), “how implementation occurs matters just as much as what is being implemented” (p. 271). Ultimately, high‐quality implementation can only occur when school systems are prepared to engage in comprehensive systems change. This process involves gradually fostering school readiness and building capacity for full implementation. … Gersten, Jayanthi, and Dimino (2017) suggested that more field evaluations of RtI are needed to address questions left unanswered by the IES national evaluation. In particular, these authors contended that smaller field evaluations should include both treatment and control groups, or what they referred to as “intervention and “business‐as‐usual” conditions (p. 252). Designs that incorporate both types of conditions would allow researchers to better understand and trace the impact of RtI interventions on student achievement outcomes.” (p.244)

Grapin, S.L., Waldron, N., Joyce-Beaulieu, D. (2019). Longitudinal effects of RtI implementation on reading achievement outcomes. Psychology in the Schools, 56(2), 242– 254. https://doi.org/10.1002/pits.22222

What are advantages of RTI for struggling learners?

It allows schools to intervene early to meet the needs of struggling learners. This has the effect of avoiding, or at least ameliorating, the cascading deficits that can occur as time passes and a student’s failure becomes entrenched and his progress falls further and further behind that of his peers. These have been described as Matthew Effects (Stanovich, 1986). “For unto everyone that hath shall be given, and he shall have abundance; but from him that hath not shall be taken away even that which he hath” (Matthew, 80-100 A.D., XXV: 29).

The Matthew Effects are not only about the progressive decline of slow starters, but also about the widening gap between slow starters and fast starters. There is ample evidence that students who do not make good initial progress in learning to read find it increasingly difficult to ever master the process. Stanovich (1986, 1988, 1993) outlines a model in which problems with early phonological skills can lead to a downward spiral where even higher cognitive skills are affected by slow reading development. Subsequently, this finding has been often supported by other researchers. A special issue of the Journal of Learning Disabilities in 2011 concluded:

“Across studies, the generalized findings are that Matthew effects are present in LD and that disadvantaged students continue to be at a great disadvantage in the future. This finding was evident particularly with regard to the relationship between vocabulary and reading comprehension (Oakhill & Cain; Sideridis et al.) as well as with regard to other reading skills such as phonological awareness (McNamara et al.) or math abilities (e.g., Morgan et al.; Niemi et al.). When looking at the framework of responsiveness to instruction implemented in the United States and various parts of the world, the message from the present studies is clear: Students with LD are likely to be classified as nonresponders as their trajectories of growth suggest. We need to switch our attention from assessing the difficulties of students with LD to how to intervene to solve their problems” (Sideridis, 2011, p.401).

At the same time as it may provide a safety net for students, it simultaneously increases the accountability of schools. At a time when the national NAPLAN and international PISA assessments are placing pressure on schools to lift student performance, RTI challenges schools to provide data demonstrating their effectiveness, but also provides a direction for a school’s response to that data. Whether it would be viewed by schools as an attractive approach or another imposition on a stressed system is moot. The expectation that general education teachers provide evidence-based instruction and regular progress monitoring represents a significant change compared to current practice in Australia.

Its introduction in the USA was expected to lead to a significant reduction in referrals to special education “by ensuring that all children in the general education setting have access to high-quality curriculum and instruction that are provided in a cascade of intensity” (Fox, Carta, Strain, Dunlap, & Hemmeter, 2010, p.3). In other words, it should remove from the LD category the group that Vellutino et al. (1996) referred to as instructionally disabled. This group comprises those children who were identified as having LD, but the cause of their struggle was inadequate instruction. This change is important, as the number of individuals identified with LD had increased by 150% to 200% since 1975. Though prevalence varied significantly from state to state, it was by far the largest category of special education. Additionally, it was noted that minority students were over-represented in the category, and that, once referred to special education, relatively few returned to the regular system (Bradley, Danielson, & Doolittle, 2005). It has been asserted for some time that the percentage of students who fail to make adequate progress can be reduced from its currently unacceptable level to something around 6% by employing early screening followed by evidence-based literacy programs (Lyon & Fletcher, 2003; Torgesen, 1998). If indeed there is a decline in the number of students labelled as disabled, then the negative consequences of labelling are avoided. It is also a hard tag to shake off once applied.

So, has there been a decline in referrals for special education?

“Much of the success of the sound MTSS implementation is evidenced by a decrease in special education referrals related to SLD given that the pre‐referral process associated with MTSS implementation allows for the elimination of unnecessary special education evaluations. As aforementioned this is reflected in an estimated reduction of SLD identification of up to 25% over the past several years.” (p.10)

Frank Webb, A., & Michalopoulou, L. E. (2021). School psychologists as agents of change: Implementing MTSS in a rural school district. Psychology in the Schools, 1–13. https://doi.org/10.1002/pits.22521

“A recent study by Albritton, et al. (2017) was aimed at determining the effectiveness of RTI in identifying preschool children in need of interventions in the areas of emergent language and literacy. This study focused on 274 students enrolled in a Head Start program, 92.3% of the participants were African American. The children were four years old and were considered at risk for educational difficulty due to their socioeconomic status. Students were assessed in the fall and again in the spring of the same school year. The initial assessment indicated that 29.9% of the students were in need of tier two supports and 2.6 were in need of tier three supports. After receiving interventions in the areas of print knowledge, phonological awareness, and receptive vocabulary, 76.8% of the tier two group was able to transition to tier one and all of the tier three students were able to move to tier two, with one student moving to tier one. Progress 11 monitoring in RTI can help to identify students who are culturally different but do not have a disability, as well as to identify those who are culturally different and are in need of special education (Castro-Villarreal, 2016).” (p. 10-11)

Savino, K. (2019). The effects of Response to Intervention on reducing the numbers of African American students in special education. Theses and Dissertations, 2701. https://rdw.rowan.edu/etd/2701

Other subgroups?

Although the RTI framework is intended to apply to all students, there have been examples of its successful use with various subgroups including gifted (Hughes et al., 2011), adolescent (de Haan, 2021), early childhood (Hinson, 2021).

“The implementation of the RtI Tier 2 model had a significant effect on the overall improvement in reading performance. These results are in line with previous studies that found significant changes once the intervention effects were analyzed on composite measures (Al Otaiba et al., 2014; Baker et al., 2015; Gilbert et al., 2013). … Within this context, direct instruction in small groups has proven beneficial for at-risk readers. In fact, previous studies found that Tier 2 direct instruction offered to small groups seems to be beneficial for students at-risk of reading failure (Agodini & Harris, 2010; Archer & Hughes, 2011; Carnine et al., 2004; Kamps et al., 2008; Richards-Tutor et al., 2016). … Another indicator we have used is the extent to which Tier 2 reduces the risk incidence of presenting reading and math difficulties in the early grades. Overall, the present findings indicate that the earlier the intervention, the greater the percentage of students who leave the situation of risk of LD in reading and math. This result coincides with previous studies (e.g., in reading, Gersten et al., 2020; in math, Bryant et al., 2011). Overall, these results are attributable to the fact that the intervention was carried out with adequate fidelity and had a significant positive impact on all grades. In fact, at the beginning of the intervention, the minimum requirements necessary to accurately carry out the implementation of the model were established (i.e., materials contained specific instructions on their implementation, a training and implementation schedule was designed, necessary materials for the evaluation of the fidelity of the implementation were designed, external observers were trained to do so, etc.) (Century et al., 2010; Johnson et al., 2006; Mellard & Johnson, 2008; O’Donnell, 2008)” (p. 14-15)

Jiménez, J., De León, S., & Gutiérrez, N. (2021). Piloting the Response to Intervention model in the Canary Islands: Prevention of reading and math learning disabilities. The Spanish Journal of Psychology, 24, E30. doi:10.1017/SJP.2021.25

“Since its implementation, RTI has received extensive attention at the elementary school level (RTI Action Network, n.d.). The same cannot be said about the application of RTI in preschool settings. With inclusive preschool programs available, there are an increasing number of students with special needs in early childhood programs (Lawrence et al., 2016). It is important to understand the benefits of early identification and intervention of children who exhibit challenging behaviors and basic skill concerns at the early childhood level. In this paper, the term “early childhood” is used to refer to children in their preschool years. Preschool age was chosen due to the lack of research regarding RTI with that particular age group. … a variety of behaviors are examined within the RTI process. At the early childhood level, academic behaviors such as alphabet knowledge, early listening skills, comprehension, language skills, verbal counting, and recognizing number symbols are considered important and critical to developing later skills. Social emotional skills such as following directions, transitioning between tasks, and communicating needs are skills needed to be successful in the school settings. Due to the importance of these skills, an emphasis is placed on helping students who have yet to develop these skills or who are considered behind their peers. Implementing RTI at this level allows children who may have not had prior exposure to learning opportunities the ability to receive additional instruction and assist in keeping them from falling behind. … several articles mentioned and used the progress monitoring tool, Individual Growth and Development Indicators of Early Literacy (myIGDIs).This can be administered by teachers to measure progress towards early literacy goals. This tool was used with multiple interventions, indicating that it is useful in monitoring progress of students in early childhood settings. Other progress monitoring tools that were mentioned in numerous academic articles include Dynamic Indicators of Basic Early Literacy Skills (DIBELS) and Clinical Evaluation of Language Fundamentals Preschool (CELF-P).” (p. 1-2, 42-43)

Hinson, K.Y. (2021). Response to Intervention in early childhood education. Masters Theses & Specialist Projects, Paper 3475. https://digitalcommons.wku.edu/theses/3475

RTI in practice

So, how might a school proceed to implement RTI for beginners? The first step would be to have all the early years teaching staff and support personnel become familiar with, and accepting of, this new framework. The demands of this familiarization and acceptance process varies from setting to setting, but should not be underestimated. School leadership (especially from the principal) has been found to be essential. Nellis (2012) provides a thoughtful coverage of the issues involved in establishing and maintaining an effective RTI team to enable implementations and monitoring decisions at the whole school and individual student level.

An early screen protocol

The next phase may involve universal screening of all students, or as a pilot, only those in their first year of schooling to attempt to predict which students may struggle with literacy, in particular. There are various means of accomplishing such prediction, but it is generally accepted that a simple test of letter name (or sound) and a measure of phonemic awareness together provide sufficient information to make reasonable predictions. Longitudinal research has made apparent that the strongest predictors of success in beginning reading are a knowledge of letter-sound/letter name correspondences (Chall, 1967; Stage, Sheppard, Davidson, & Browning, 2001) and phonemic awareness (Scarborough, 1998; Torgesen, 1998), a protocol more recently supported by Manolitsis and Tafa (2011). This provides a rationale for focussing assessment on these areas initially.

Torgesen (1998) suggests the commencing screening procedure should comprise a test of letter names, because letter knowledge continues to be the best single predictor of reading difficulties, and a test of phonemic awareness. Torgesen’s research also indicated that knowledge of letter-sounds is a stronger predictor for first graders. Additionally, the single strongest predictor of a beginning child’s end-of-year spelling ability was a one minute letter-sound fluency test at the year’s beginning in the Al Otaiba et al. (2010) study. Measuring fluency of letter-sound knowledge is a worthwhile extension of simply assessing untimed knowledge. In a study with first grade students (Speece & Ritchey, 2005), letter-sound fluency was a unique predictor of subsequent oral reading fluency levels. Further useful correlations are reported by Stage, Sheppard, Davidson, and Browning (2001). Letter-naming fluency and letter-sound fluency predicted oral reading fluency and reading growth generally during the following year. Struggling first graders typically could produce only eight letter names per minute in their first months of schooling.

As phonemic awareness is thought to involve a developmental sequence, the decision as to which form of test to employ for a student cohort assumes importance. For example, it is recognised that blending, segmenting, and deletion are quite difficult tasks for children before and during their first year of school (Schatschneider, Francis, Foorman, Fletcher, & Mehta, 1999). Tests in which few students can achieve success or tests in which most students are near ceiling are of little use as screening devices.

In a longitudinal study of 499 children from kindergarten through Grade 3 (Vervaeke, McNamara, & Scissons, 2007), an accuracy figure of 80% was obtained when kindergarten assessment of phonological awareness and letter-sound correspondence was compared to their Grade 3 reading achievement. The false negative and false positive rates were each 12%, representing encouraging predictive capacity over a significant period of time.

Good and his colleagues (Good & Kaminski, 2002) have established performance-based benchmarks using the freely available Dynamic Indicators of Basic Early Literacy Skills (DIBELS). The tests relevant to this screening task are Letter Naming Fluency and Initial Sound Fluency. Note that these tests are timed, so they add a component of speed along with power – efficiency along with knowledge. Employing fluency in the measurement of subword skills (e.g., letter names/sounds) has become of increasing interest (Speece, Mills, Ritchey, & Hillman, 2003) because of the significance of automaticity as a quality beyond mastery. In fact, Initial Sound Fluency assessed in school commencement has been shown to significantly predict end of year performance in word identification, nonsense word reading, and reading comprehension for both regular students and those for whom English is a second language (Linklater, O'Connor, & Palardy, 2009).

The DIBELS measures are also very brief, and easy to administer. Letter Naming Fluency involves a sheet with upper and lower-case letters, and students name as many letters as possible in one min. Fewer than 2 letters in one min at preschool or early first year at school is considered at-risk, between two and seven constitute some risk, and eight or more is classed as low risk.

In the DIBELS Initial Sound Fluency, students are shown (for one minute) a series of pages containing four pictures. (Pointing to the pictures) This is: tomato, cub, plate, doughnut. Which picture begins with /d/? Fewer than four initial sounds correct in one minute at preschool or early first year at school is considered at-risk, between four and seven constitute some risk, and eight or more is classed as low risk.

A similar system called AIMSweb is available from The Psychological Corporation (http://www.aimsweb.com). It includes subtests for Phoneme Segmentation, Letter Naming Fluency, Letter Sound Fluency, Oral Reading Fluency, Maths, and Behaviour. Other resources include Edcheckup (http://www.edcheckup.com), Easycbm (http://www.easycbm.com/), Project AIM (Alternative Identification Models) (http://terpconnect.umd.edu/~dlspeece/cbmreading/index.html), and Yearly Progress Pro (http://www.mhdigitallearning.com).

Another option, one that is used in the UK for reviewing the progress of students in their second year, is the Year 1 phonics screening check (Department for Education, 2012).. It is completed in mid Year 1, so it doesn’t replace the initial phonological screen described above. It could however be useful as an aid in detecting those students in need of Tier 2 support. It comprises a list of 40 words and non-words read to a teacher.

The school’s decision about how to proceed with instruction may depend upon the proportion of students defined as at “some risk” and/or “at risk”. The RTI framework is not prescriptive about this decision, but if the class average is low, then a red flag is raised about not only high quality initial instruction, but also about the need for forward planning for Tier 2 interventions.

Figure 2. Data indicative of a classwide problem (Ikeda et al., 2006)

If only the “at risk” group is selected, there will be fewer students to manage, and they are the most likely to experience difficulty. However, there are likely to be students in the “some risk” who also meet hurdles. Some studies have suggested focusing on the lowest 10% of students, some on those below the 25th percentile, and others suggest all those below the 40th percentile offers the fewest false negative predictions. To some degree this decision will be driven by the school resources allocated to the RTI program. Some systems employ benchmarks to discern who is likely to struggle. There are many decisions in practice that the research into RTI has yet to report optimal recommendations (O'Connor & Freeman, 2012).

Table 1

An example from the DIBELS system of benchmark goals for the first year of school.

Norms in standardised tests

There are always concerns about the applicability to Australian students of norms derived from populations in other countries. Obviously, it would be an advantage to have local norms for all the tests we wish to use; however, the huge cost of properly norming tests is prohibitive for many local developers. There are some grounds for defending US normed tests of reading. We speak and write the same language, and, in most Australian states, we commence school at about the same age. In international comparisons (e.g., OECD, 2004; UNICEF, 2002), our average reading attainment exceeds that in the USA, perhaps because of our lower proportion of disadvantaged and non-English speaking students. The implication of this disparity is that tests using US norms may slightly flatter our students. When students do not do well on such a test, it is likely that they would actually be lower on that test using local norms than is indicated by the test manual. So, if a student, for example, scores in the at-risk category on any of the DIBELS measures, any error caused by the US norms is likely to represent an underestimate of their level of difficulty. Further, according to the Galletly and Knight (2006) study, the current DIBELS norms are appropriate to states in Australia that begin teaching reading in their students’ first year. Certainly, further studies involving the testing of norms would add confidence to the vital decisions about how many students should be included in Tier 2 and Tier 3 programs.

The DIBELS system has become extremely popular as a means of ascertaining risk. Having completed the universal screening, one option is to present the evidence-based reading program to all students as normal, but to increase monitoring of the potential strugglers to weekly or fortnightly (rather than the three or four times per year for the low risk students). Another is to intervene immediately and place the identified group on a schedule of additional instruction, perhaps emphasizing Letter Name/Sound Fluency and Initial Sound Fluency. In the VanDerHeyden, Snyder, Broussard, & Ramsdell (2007) study, the researchers found increased accuracy of prediction when a test-teach-test protocol was employed by adding a brief intervention designed to address whether opportunities to learn were all that was missing for a subgroup of the potentially struggling cohort.

The progress checks are to ensure that subsequent progress (or lack of it) is quickly noted and responded to. They are charted to enable analysis using decision making protocols, such as is seen below. A significant difference between actual and expected attainment is evident from score comparisons against either the class average or the benchmarks, while rate of learning over several data points can be seen on a progress graph. A low attainment with a high rate of growth suggests the reason is probably a lack of opportunity, and some confidence that the existing instruction may be sufficient for the student to catch up. A low attainment and a flatter slope suggest the likely need for a Tier 2 intervention.

In this figure, the progress of a student in several phonological skills is plotted for the three test occasions of his first school year. The slopes of the graph indicate the extent of improvement over time – the steeper the slope, the more rapid was the progress. According to the DIBELS norms, Letter Naming Fluency scores of 27, 36, 53 correct in one minute are each in the low risk range. His Initial Sound Fluency scores of 18, 26, 34 correct in one minute each place him at “low risk” with this skill described as “established” by year’s end. Phoneme Segmentation Fluency is not usually assessed until mid-year; his score of 14 correct in one minute places him at “some risk”, and end-of-year 28 correct in one minute indicates an “emerging” skill. Nonsense Word Fluency is not usually assessed until mid-year; his score of 12 correct in one minute is just below the “low risk” threshold of 13, and thus classified as being at “some risk”. His end of year score of 22 correct in one minute is also within the “some risk” category with the threshold score for “low risk” being 25. Overall, the slopes indicate reasonable progress, with a need to monitor his Phoneme Segmentation Fluency and Nonsense Word Fluency monthly in the new year with a view to increasing intensity of instruction in phonemic awareness and decoding if necessary. There are excellent resources for planning, assessment norms, and decision rules available freely at the Oregon Reading First website (https://dibels.uoregon.edu/). Graphing software is available at several sites, including GRAPS (http://www.rtigraphs.com/home) and Chartdog (http://www.interventioncentral.org/tools/chart_dog_graph_maker).

Figure 3. DIBELS Progress Monitoring (McDougal, Clark, & Wilson, n.d.).

Students whose initial progress line has a flatter slope than that of the average student must subsequently make progress at an even faster pace than does the average student if they are to catch up. That is why early intervention is so important, and why program quality and intensity assume so much importance (Al Otaiba et al., 2008; Vaughn & Dammann, 2001; Vaughn, Denton, & Fletcher, 2010).

“Students who are behind do not learn more in the same amount of time as students who are ahead. Catch-up growth is driven by proportional increases in direct instructional time. Catch-up growth is so difficult to achieve that it can be the product only of quality instruction in great quantity” (Fielding, Kerr, & Rosier, 2007, p. 62).

Usually graphs used in a Tier 2 or Tier 3 intervention will include a final goal, and this allows a goal line to form part of the graph. The goal line is drawn from the baseline score to the projected score. The intent is for the data to be at or above the goal line most of the time, an indication that the intervention is having a positive effect. It is usual to make decisions about intervention change only after at least three weeks of instruction and at least 6 data points. If four of these points fall below the goal line a decision is made to alter the intervention (Stecker & Lembke, 2007).

In the example below, this four point rule was invoked after the Week 6 test, and so a change was made to the intervention. The teacher has several options; for example, to increase instructional time, change the teaching presentation technique, increase opportunities to respond (e.g., double dose), alter correction procedures, or change the grouping arrangement (individual instruction instead of small-group instruction). The regular weekly scores readily demonstrate to any observer whether the change was helpful. This type of data is particularly helpful to parents involved in Individual Educational Plan meetings. Sometimes the content of a school’s reporting of a child’s progress to these meetings can be a source of confusion to parents. Weak monitoring and reporting in schools and school systems has been cited by Rorris and colleagues, in their 2011 ACER report to The Review of Funding for Schooling Panel, as a major impediment to the adoption of effective educational programs.

In the example, the intervention intensity might be lifted by adding to the four times per week teacher instruction an additional two spelling sessions with a peer tutor each week. This increase may be sufficient to have the child back on track to reach her target. As there were also 4 data points above the goal line the goal line is elevated to ensure high expectations are maintained.

Figure 4. CBM data for a Tier 2 intervention in writing (McMaster, Ritchey, & Lembke, 2011).

If success in an intervention is not occurring, it is important to ensure that the program is being implemented in the prescribed manner. This is a common problem when teachers are unaware of the critical importance of program fidelity, and decide to modify the intervention according to their own judgement. Supervision and technical assistance has been shown to be essential as there is a strong relationship between fidelity of implementation and student outcomes (Vadasy, Jenkins, & Pool, 2000). Thus, the teacher needs to be retrained by watching the project coach perform the sequence correctly, being observed during their new attempt at intervention fidelity, being provided with feedback on this attempt, and subsequent observation post-training (Mellard, 2010).

More on Tier 3

If, despite several faithfully implemented Tier 2 interventions employing recognized evidence-based programs over at least a 20 week period (Wedl, 2005), a student continues to make unsatisfactory progress in a given domain then an RTI team may further manipulate some of the intensity variables highlighted by Mellard (2010). Most think of only frequency and duration of lessons and programs as intensity variables, but Mellard, McNight, and Jordan (2010) also include other features such as broader instructional design principles that attempt to reduce any ambiguity in the instructional communications occurring within lessons.

“Mellard suggests that schools evaluate 10 distinct variables that may be adjusted to increase instructional intensity. These variables include three dosage-related elements (minutes of instruction, frequency, and duration), as well as instructional group size, immediacy of corrective feedback, the mastery requirements of the content, the number of response opportunities, the number of transitions among contents or classes, the specificity and focus of curricular goals, and instructor specialty and skills” (p.219).

If even these modifications are insufficient, one may arrange for a full psychological and educational assessment, along with any other relevant professional assessment, for example a paediatric or a speech pathology assessment. The expectation of working through the tier system is that many fewer students receive this resource intensive referral, as most are adequately supported by the RTI system. Of course, the quality of RTI implementations may differ markedly from place to place, and over time. It should not be seen as a panacea, but rather as a useful framework for a reduction in the level of serious long term effects of extended student failure.

So, RTI has been employed increasingly for reading instruction. What about writing?

“To date, RTI approaches to instruction have focussed almost exclusively on reading and mathematics. Within these domains, they have been widely adopted, particularly in English-speaking countries (Berkeley et al., 2009), and there is evidence that they are successful in reducing the percentage of students requiring special education (see meta-analysis by Burns et al., 2005). Hattie (2012, 2015) estimated a standardised effect size of 1.07 for the RTI approach. Teachers’ attitudes towards RTI also tend to be positive. They find it valuable in supporting students’ learning (Greenfeld et al., 2010; Rinaldi et al., 2011; Stuart et al., 2011) and believe it has a positive impact on their teaching practices, autonomy and self-efficacy (Greenfeld et al., 2010; Stuart et al., 2011). We argue, in line with suggestions by previous authors (Dunn, 2019; Saddler & Asaro-Saddler, 2013), that the RTI framework has considerable potential value in teaching writing. This may be particularly the case in early primary school, where students have to contend with developing basic skills in spelling, handwriting and sentence construction alongside the skills necessary to generate and structure content. Transcription skills in first grade are not automatized and children who particularly struggle with these will then not gain the practice they require to develop composition skills. There is, therefore, potential for some children to fall behind their peers from an early stage, unless they are provided with additional support. Equally, the RTI principle of progress monitoring seems important in the context of learning to write. Single-task, occasional writing assessments provide a poor estimate of a child’s writing ability and progress (Van den Bergh et al., 2012).” (p. 3-4)

Arrimada, M., Torrance, M. & Fidalgo, R. (2021). Response to Intervention in first-grade writing instruction: A large-scale feasibility study. Reading & Writing. https://doi.org/10.1007/s11145-021-10211-z

One to one or small group?

The current most popular intervention in Australia is Reading Recovery, an expensive one to one program offered in the second year of a child’s education. It is probably best considered as a Tier 2 one to one intervention, but at present it represents the totality of structured literacy interventions in many Australian schools. In the UK too, it has been described (perhaps surprisingly) as the most intensive Tier 3 program available (Department for Children, Schools, and Families, 2009). As noted above, there have been criticisms of the lack of benefit analysis, much less cost-benefit analysis of this intervention.

The question of cost benefit has become more significant with the increasing number of studies in which small homogeneous group instruction (perhaps three to five students) can, in many cases, be as successful as one to one interventions, whether involving Reading Recovery or other beginning reading or early intervention programs (Elbaum, Vaughn, Hughes, & Moody, 2000; Wanzek & Vaughn, 2008). At a Tier 2 level, there are obvious savings to be made in offering evidence-based programs in small group over one to one format. The cost savings of doing so could be channeled into more intensive assistance (with smaller groups or one to one) for Tier 3 interventions.

Can RTI address the needs of older students?

The major interest in RTI is about the prevention of learning problems from the beginning, partly because of the difficulty of altering the educational trajectory of students who struggle for long periods. The Matthew Effect described earlier highlights the cascading deficits arising from a failure to thrive educationally. The research literature with secondary school students is sparse, and the applicability of RTI requires considerably more work before efficacy can be assured with this cohort.

However, RTI does have an intervention focus and provides the framework for intervention with older students. There is a stronger effort devoted to the middle primary grades than to secondary schools as the continuum of service provision becomes extreme by the time children arrive at secondary school. Vocabulary, domain knowledge, reading fluency, a sense of helplessness, and increasingly complex curriculum all conspire to thwart efforts at retrieving these students.

Roberts, Torgesen, Boardman, and Scammacca (2008) note that the instructional intensity and duration that might help close the achievement abyss for older students needs to be far more than is typically provided currently.

Vaughn, Wanzek, et al. (2010) warn that the impact of Tier 2 and Tier 3 interventions with Year 7 or 8 students will not have much effect if they are restricted to one school period per day.

“Instead, the findings indicate, achieving this outcome will require more comprehensive models including more extensive intervention (e.g., more time, even smaller groups), interventions that are longer in duration (multiple years), and interventions that vary in emphasis based on specific students’ needs (e.g., increased focus on comprehension or word study)” (p. 931).

Abbott et al. (2010) conclude that at least two and a half hours per school day needs to be devoted to literacy in a mix of large and small group instruction.

The pre-intervention CBM assessment for older students shifts from an emphasis on letter names/sounds and phonemic awareness to measures such as nonsense word fluency, oral reading fluency, story retell fluency, word identification fluency, and maze completion tests.

For many students the struggle endured in developing their phonological skills remains evident in that their reading remains slow, thereby hindering their comprehension even if their reading accuracy has reached acceptable levels (Torgesen et al., 2006). In fact, Fuchs, Fuchs, Hosp, and Jenkins (2001) found that a short oral fluency measure predicted reading comprehension more precisely than did another brief reading comprehension test. The correlation was 0.91. Clearly, for older students fluency is very strongly associated with reading comprehension. Similar results have been obtained by O’Connor et al. (2002) and by Swanson and O’Connor (2009) and hence the increased interest in fluency measures of students’ reading of connected text.

Research has also highlighted the value of extended fluency practice for such mid-primary students and secondary students (Joseph & Schisler, 2009; Kuhn & Stahl, 2003; Swanson, 2001). At a time when attempts to assist older readers focus exclusively on comprehension strategies, Mastropieri, Leinart, and Scruggs (1999) sound a warning that unless fluency is also addressed, comprehension strategy training will have little impact.

The emphasis on fluency of various skills and across grades is not one to which education in Australia has paid much attention. Fluency requires practice, and the main approach to teaching over the past 30 years, whole language, eschewed the necessity for practice.

Harn, Jamgochian, and Parisi (2009) argue for much greater attention to be paid by educators to the fluency of skills and knowledge rather than solely to accuracy as a truer measure of mastery. Their recommendation supports the work of Carl Binder (Binder, Haughton, & Bateman, 2002). Binder asserted that as educators we have failed to bring our students to the stage of fluency in the various skills we teach. A student may read a sentence without error, but takes 30 seconds to do so. Another student does so in 6 seconds. There is a difference between the two that is not evident in traditional untimed assessment tools. Fluency is the sum of effective teaching and practice. He considers four levels on the way to fluency: 1. Incompetence (no measurable performance). 2. Beginner's level (inaccurate and slow). 3. 100% accuracy (traditional "mastery"). 4. Fluency (true mastery = accuracy + speed).

Binder argues that there are real educational advantages in being able to perform fluently. He points to increased retention and maintenance in which there remains a greater capacity for the knowledge/skill to be recalled/performed long after the teaching has occurred. He also notes that fluency enables a resistance to distraction, and a capacity to remain at a task for much longer periods than can a student who is slow in working at a task. Finally, he points to the capacity to employ fluent skills in novel situations, and to use them as a bridge towards more complex skills. Fluency implies near effortless performance, hence “it frees up attention for higher order application rather than overloading attention with the mechanics of performance” (p.5). Similar conclusions were reached by Lindsley (1990) in his development of Precision Teaching, and Lindsley’s Celeration Charts have received renewed attention in recent times as a means of charting data.

Binder believes that this attention to fluency is relevant to all foundation skills, and he offers a series of estimates of fluent performance on a range of basic skills. For example, for spelling fluency - writing words from dictation at 15 – 10 words /min. For basic early arithmetic - Count by 1’s, 2’s, 5’s, and 10’s at a rate of 120 – 100 /min.

We have noted earlier that RTI employs the sorts of fluency goals to which Binder had referred, and they go further to offer age/grade norms for a range of basic skills such as letter names/sounds, phonemic awareness, nonsense word fluency, and oral reading fluency.

Can parents and paraeducators assist in intervention?

“Persampieri et al. (2006) and Gortmaker et al. (2007) demonstrated that parents were able to implement academic interventions accurately and effectively when they were provided with sufficient support. In this study, parents were provided with intervention implementation training and all intervention materials. In addition, a researcher regularly contacted parents through phone calls and written notes to assist with problem‐solving for any difficulties (e.g., audio recorder malfunction). … Results from this study are consistent with previous research which demonstrated that parent‐implemented reading interventions are effective for increasing students’ reading fluency (Gortmaker et al., 2007; Schreder et al., 2012). In particular, Gortmaker et al. and Schreder et al. conducted BEAs of participants’ reading fluency and parent‐implemented BEA‐identified interventions, which led to increases in participants’ reading fluency. However, this study extends the literature by testing BEA‐identified interventions that were implemented by parents in the context of a RtI system.” (1153-1154)

Zhou, Q., Dufrene, B.A., Mercer, S.H., Olmi, D.J., Tingstom, D.H. (2019). Parent-implemented reading interventions within a response to intervention framework. Psychology in the Schools, 56, 1139– 1156. https://doi-org.ezproxy.lib.rmit.edu.au/10.1002/pits.22251

“However, although in principle RTI appears to fit well with writing instruction, in practice both progress monitoring and additional support for struggling students may over-stretch school resources (Castro-Villarreal et al., 2014; Martinez & Young, 2011). This will be particularly the case where a single teacher has sole responsibility for a large, full-range classroom. In this context, recruiting parents to supervise researcher-designed remedial training may facilitate the implementation of a RTI-based program. Parental involvement has actually been defined as a key component of successful RTI-based programs (Stuart et al., 2011), though, to our knowledge, no detailed guidelines on parents’ role has been provided, and no studies have evaluated RTI implementations where parents supervised additional training. There is evidence that parental involvement benefits students’ learning, with estimated standardised effects of around 0.50 (Hattie, 2012, 2015). In writing, research suggests that instructional programs based on parents and children working together significantly improve spelling (Camacho & Alves, 2017; Karahmadi, et al., 2013) and even compositional quality (Camacho & Alves, 2017; Robledo-Ramón & García-Sánchez, 2012; Saint-Laurent & Giasson, 2005).” (p. 4)

Arrimada, M., Torrance, M., & Fidalgo, R. (2021). Response to Intervention in first-grade writing instruction: A large-scale feasibility study. Reading & Writing. https://doi.org/10.1007/s11145-021-10211-z

There’s evidence of a reduction in referrals for special education, but are there any longer term effects of RTI?

“The implementation of evidence-based practices through Response to Intervention (RtI) has been shown to reduce the prevalence rate of students dropping out from school (Bernardt & Hebert, 2017; Wood, Kimperman, Esch, Leroux, & Truscott, 2017).” (p.11)

Young, N.D., & Johnson, K. (2019). The potency of the Response to Intervention Framework. In N.D. Young (Ed.), Creating compassionate classrooms: Understanding the continuum of disabilities and effective educational interventions (pp. 11-21).Wilmington, Delaware: Vernon Press.

“ … students who experienced the early phases of RtI implementation (i.e., Phases I and II) during Grade 2 generally had higher mean comprehension scores in Grades 4 and 5 than students in the baseline condition. … Several studies have investigated student and systems outcomes associated with full‐scale RtI implementation. Collectively, this study has suggested that RtI implementation is associated with greater accuracy and decreased numbers of special education referrals, improvements in student achievement, and reduced assessment and placement costs for districts (Burns, Appleton, & Stehouwer, 2005; Lembke, Garman, Deno, & Stecker, 2010; VanDerHeyden, Witt, & Gilbertson, 2007).” (p. 242, 243)

Grapin, S.L, Waldron, N., Joyce-Beaulieu, D. (2019). Longitudinal effects of RtI implementation on reading achievement outcomes. Psychology in the Schools, 56(2), 242– 254. https://doi.org/10.1002/pits.22222

Is it doable in Australia?

It would certainly require wholesale changes to the often strongly held belief systems that education and science are incompatible (Hempenstall, 2006; Lilienfeld, Ammirati, & David, 2012). Some have argued that science has little to offer education, and that teacher initiative, creativity, and intuition provide the best means of meeting the needs of students. For example, Weaver considers scientific research offers little of value to education. “It seems futile to try to demonstrate superiority of one teaching method over another by empirical research” (Weaver, 1988, p.220).

Some outcomes of a failure to attend to empirical data are the popularity of learning styles, of rigid inclusion of all students at all times, of constructivism, of student directed learning (personalised learning), the distrust and rejection of instructional protocols, the belief that obtaining student engagement is the major role of teachers. For example, Smith (1992) wrote that student-teacher relationships are sufficient for effective learning to occur. Further, he rejected instruction in favour of a naturalist perspective “Learning is continuous, spontaneous, and effortless, requiring no particular attention, conscious motivation, or specific reinforcement” (p.432).

These beliefs with little or no empirical support perhaps reflect what Isaacs and Fitzgerald (1999) referred to as eminence-based practice rather than evidence-based practice.

Carnine (2000) noted that education has been largely impervious to research on effective practices, and he explored differences between education and other professions, such as medicine, that are now strongly wedded to research as the major practice informant. In psychology during the 1990’s, the American Psychological Association (Chambless & Ollendick, 2001) introduced the term empirically supported treatments as a means of highlighting differential psychotherapy effectiveness. Prior to that time, many psychologists saw themselves as developing a craft in which competence arises through a combination of personal qualities, intuition, experience. The result was extreme variability of effect among practitioners, a characteristic noted among teachers also.

In Australia in 2005, the National Inquiry into the Teaching of Literacy asserted that “teaching, learning, curriculum and assessment need to be more firmly linked to findings from evidence-based research indicating effective practices, including those that are demonstrably effective for the particular learning needs of individual children” (p.9). It recommends a national program to produce evidence-based guides for effective teaching practice, the first of which is to be on reading. In all, the Report used the term evidence-based 48 times.

Carnine (1991) argued that the leadership has been the first line of resistance to effective practices. He described educational policy-makers as lacking a scientific framework, and thereby inclined to accept proposals based on good intentions and unsupported opinions. Professor Peter Cuttance, director of the Melbourne University's Centre for Applied Educational Research in 2005 was equally blunt: “Policy makers generally take little notice of most of the research that is produced, and teachers take even less notice of it … ” (Cuttance, 2005, p.5).

In Australia, pressure for change has been building, and the view of teaching as a purely artisan activity is being challenged. Reports such as that by the National Inquiry into the Teaching of Literacy (2005) have urged education to adopt the demeanour and practice of a research-based profession, though it is not obvious that such exhortations have had a significant effect on classroom practice. However, State and national testing has led to greater transparency of student progress, and, thereby, to increased public awareness. Government budgetary vigilance is greater than in the past, and measurable outcomes are becoming the expectation from a profession that has not previously appeared enthused by formal testing.

There’s also the issue of teacher training to implement interventions.

In Australia, we have seen numerous reports that beginning teachers in particular may not have the knowledge of evidence-based practice needed as a first step to the use of RTI. A number of reports and studies have noted this deficit, and criticized the lack of this emphasis in teacher training courses (Fielding-Barnsley, 2010; Fielding-Barnsley & Purdie, 2005; Fisher, Bruce, & Greive, 2007; Louden, et al., 2005; Rohl & Greaves, 2005; Senate Employment, Workplace Relations and Education Committee, 2007). Additionally, education departments have been remiss in failing to evaluate programs that they introduce into the school system, such as Reading Recovery (Victorian Auditor-General, 2009).

If teacher training does not generally equip teachers in either the evidence base for the initial teaching of reading or with the tools to intervene effectively with students who struggle with literacy in particular, what sort of training might be effective? The majority of inservice training historically in Australian education has been that which can be squeezed into a one-off curriculum day. As Joyce and Showers (2002) report, this type of professional development does not typically translate into changes at the classroom level.

Table 2

Percentage of participants achieving desired outcomes at increasing levels of training

(Joyce & Showers, 2002).

Knowledge of effective instructional interventions

Given that frameworks are designed to support structures, rather than provide the entire finished product, schools usually require knowledge of appropriate evidence-based practices, and how to fit those into the day to day running of the school. Given that teachers do not generally receive such knowledge and skill in their pre-service training, many need the services of a trainer to assist in the various training and implementation issues that arise from the decision to adopt the RTI framework. RTI is not a self-contained panacea. The framework stands or falls on the faithful presentation to students of demonstrably effective interventions, otherwise it remains only a shell.

“High-quality intervention is grounded in scientifically proven materials with a strong evidence base; however, it is not enough for students to simply engage with a strong evidence-based intervention. Ongoing development of teacher knowledge to ensure the successful implementation of the high-quality intervention is also essential, as “curricula alone do not teach” (ILA, 2020). The effectiveness of the intervention is contingent upon the effectiveness of the provider. In order to achieve desired student outcomes and maintain the intervention’s evidence basis, program materials must be implemented as intended. Teaching as intended requires fidelity to program structure, including content, materials, duration, and frequency as well as fidelity to program procedures, including delivery, techniques, and student engagement. Effective intervention implementations consider both what is taught and how it is being taught (Sidler Folsom & Schmitz, 2018).” (p. 4)

Forsythe, L., Kohn, A., & Arnett, M. (2021). High-quality interventions to ensure literacy for all students. Center for the Collaborative Classroom. https://public.cdn.ccclearningportal.org/program/resources/field-team/MKT-5147-highqualityinterventions-whitepaper.pdf

Explicit, systematic, and sequential

“For most students, direct instruction in the foundational skills of reading is essential to their literacy success. When students do not make expected progress with the explicit foundational skills instruction provided during core instruction, they require additional instruction, or intervention, that is both explicit (direct and teacher-led) and systematic (methodical, incremental instruction organized into a coordinated instructional routine) (Gersten et al., 2008). Students who are identified as needing foundational skills intervention will benefit from instruction that is carefully sequenced so that skills are developed gradually and deliberately. (Torgesen, 2004). According to the International Literacy Association (2020), explicit and systematic intervention instruction that results in the needed acceleration of progress must also ensure frequent opportunities for student response, provide specific and immediate corrective feedback, support positive approaches to learning and behavioral supports, and teach the transfer of skills. Well-designed, systematic instructional programs ensure that children are taught systematically and are given opportunities to practice the skills before being required to do this work independently (Torgesen, 2004; Swanson, 1999).” (Forsythe, Kohn, & Arnett, 2021, p. 4).

Preparing teachers for RTI

“Successful implementation of intervention strategies for students having difficulties with reading is highly dependent on teachers’ knowledge. Curricula alone do not teach; skilled teachers know how to prioritize learning objectives. For students who are struggling, or who have reading disabilities, including dyslexia, it is vital that teachers know (a) how to identify students who need help, (b) what help to provide them, and (c) how to access appropriate resources for supports within their school and district. Strong teacher preparation programs prepare their candidates with knowledge to guide their practice, but they also provide many types of opportunities for candidates to practice or apply their coursework and receive supportive feedback. Preparation programs vary along a developmental continuum from preservice teacher training to graduate specialized training programs that include job-embedded activities. Preservice teachers can benefit from watching faculty model literacy lessons, watching video exemplars, and practicing teaching with peers. Initially, they may follow relatively scripted lesson plans with struggling or typical learners and eventually develop their own lesson plans for whole-group, small-group, and individualized instruction. More experienced teachers returning for graduate or certification programs may benefit from trying evidence-based practices within their own classroom setting. Ideally, preservice and inservice teachers have supervision from higher education faculty in person or remotely through technologies that allow a supervisor to observe via conferencing or to observe video clips. Within the university setting, teachers benefit from watching videos of their own and their peers’ teaching as a type of a community of practice that supports reflection and rehearsal. Some recent innovations involve virtual reality simulations that allow a preservice teacher to try out lesson plans with a virtual student, receive feedback from peers and faculty, and to reflect and replan prior to delivering a lesson to a student. Some of these innovations also facilitate teachers’ self-efficacy for teaching diverse learners and managing classroom behavior in order to keep students engaged and motivated.” (p.1)

International Literacy Association. (2020). Intensifying literacy instruction in the context of tiered interventions: A view from special educators [Literacy leadership brief], 1-13.

https://literacyworldwide.org/docs/default-source/where-we-stand/ila-intensifying-literacy-instruction.pdf?sfvrsn=5caabc8e_4

From what sources might expert support arise?

Certainly, in some schools are teachers who have studied the intervention field, and are capable of supporting a school through the introduction of RTI. Additionally, some suggest a role for educational psychologists (Frank Webb & Michalopoulou, 2021), and others envisage speech pathologists being an appropriate resource (de Haan, 2021). Special educators, too, are potential sources of expertise.

“All educators will be affected by the decision to implement RTI. For example, many special education teachers and other learning disability specialists will have to take on the roles of the interventionists, and they will be expected to become proficient in a variety of research-based methods and material in a relatively short amount of time. In addition, general education teachers will have to be become proficient in the new assessment procedures and data collection methods for progress monitoring and be able to interpret the data to inform their instruction. These changing roles are a concern due to the importance of fidelity and consistency within an effective RTI model (NJCLD, 2005).” (p.14)

Wise, C. (2017). The effectiveness of Response-to-Intervention at reducing the over identification of students with specific learning disabilities in the special education population. A Dissertation Presented to The Faculty of the Education Department Carson-Newman University In Partial Fulfillment of the Requirements for the Degree Doctor of Education. https://classic.cn.edu/libraries/tiny_mce/tiny_mce/plugins/filemanager/files/Dissertations/Dissertations2017/Coleman_Wise.pdf

Haager and Mahdavi (2007) summarise some of the other issues that challenge an RTI implementation. There may be policies and practices within schools or across education systems that conflict with the evidence-based nature underpinning RTI. At the local level teacher negativity can derail any new initiative. What they do delineate as essential are the grade level meetings to ensure mutual support and consistency of application, the availability of in-class coaching and supervision mentioned above, and the unwavering support and attention of school administration. Teacher training has been a major issue in the USA involving a great deal of time and expense (Baskette, Ulmer, & Bender, 2006). Additional hurdles identified by Jones, Yssel, and Grant (2012) include how to find sufficient personnel with the time for universal screening, and the pre-testing for, and scheduling of, interventions.

Concerns have been raised by van Kraayenoord (2010) about how RTI might fare in Australia. She makes the point that the level of intensity and duration provided to students during a Tier 3 intervention has been rarely offered in the regular school system, and both the concept and the cost of such extensive and extended interventions would challenge the education system. She also queries the emphasis on reading in the RTI research, where in Australia a much broader vision of “multiliteracies” has significant currency. Further, there may be a local reaction against a primary focus on a narrower definition of reading than is present in the popular four resources model of Freebody and Luke (1990). In any case, the major stumbling block, at least for most struggling beginners is to be able to get the words off the page (Rasinski, Homan, & Biggs, 2009; Stuart, 1995).

Somewhat surprisingly, van Kraayenoord argues that RTI should be aligned with existing teacher education emphases and local policies. At the same time, she argues for an evidence-basis to determine what is effective, but “we must not devalue teachers’ professional knowledge and decision making around curricula and pedagogical practices” (p.371). These would seem to be conflicting expectations; however, if they reflect a likely popular position, it is difficult to see how an effective version of RTI would be possible in Australia without it being mandated.

Esparza Brown and Doolittle (2008) describe what they see as a potential selling point for RTI when they argue that it represents the best of personalised instruction, as each child’s needs are assessed in order to provide instruction appropriate to their needs. However, personalised instruction can have a rather different and incompatible meaning as a recent educationally valued concept related to Constructivism. If one accepts the following definition it is difficult to reconcile with RTI. “Personalising learning is the process which empowers the learner to decide what, where, when and how they learn” (National College for School Leadership, 2010).

A further issue involves another educational value, that of inclusive education. It refers to the provision of assistance for students with disabilities in the classroom they would attend if they did not have a disability. Full inclusionists consider the meaning of this term precludes the use of any withdrawal from their classroom (Stainback & Stainback, 1992) for Tier 2 or Tier3 assistance as such actions contravene the spirit of inclusive education. Sometimes the objections to withdrawal emphasise a social justice or anti-discrimination perspective. Others cite the threat to students’ self-esteem of such schedules, as peers observe that the student requires special treatment. The philosophy does tend to polarise:

“Although state-of-the-empirical-data debates have contributed significantly to improving intervention efforts, the problem of effectively translating research findings into practice remains exacerbated by other less visible but powerful tensions materially impacting the field. Most prominent in this regard is the ideology of full inclusion, which has influenced policy and practice disproportionately to its claims of efficacy. The now familiar press for full inclusion has become an ideological on-rushing river, bypassing significant islands of contradictory evidence by now quite substantial, offering viable and more ethical alternatives. Indeed, the notion of empirical evidence seems antithetical to many full inclusionists’ views on research and practice (e.g., D. J. Gallagher, 1998; Smith, 1999). In place of evidence, we are offered trendy and deliberate postmodern convolutions, whose underlying aim, transparent but incoherent, is the dissolution of special education, irrespective of the consequences (see Sasso, 2001)” (Kaval, & Mostert, 2003, p.191).

Some supporters of another related philosophy known as differentiated instruction also reject withdrawal from the general classroom for most students (Tomlinson, 1999). However, according to some definitions the RTI model could be viewed as representing a form of differentiated instruction, even though at least some of the interventions (such as Tier 2 and 3) are likely to occur in withdrawal groups or in one to one settings. Given the perspective that a differentiated instruction goal is "to maximize student growth and individual success" (Tomlinson & Allan, 2000, p. 4), then, as Allan & Goddard (2010) assert, the approaches share similar goals. On the other hand, the espousal of teaching according to learning styles (Strong, Silver, & Perini, 2001) and multiple intelligences (Campbell, Campbell, & Dickinson, 1999) by some writers in the differentiated instruction field would appear to put the philosophy at odds with RTI.

Thus, there is a tension between what may be optimal in terms of educational effectiveness and the desire not to single out students in need. There is a view that it is not the setting but the instructional practices within the setting that determine student progress (Epps & Tindall, 1988), and a question arising from that perspective is whether all the necessary evidence-based practices can currently be provided within the general classroom. McLeskey and Waldron (2011) in reviewing the research on full inclusion and withdrawal programs concluded that “full inclusion is not a feasible alternative for meeting the basic academic needs in reading and math for most students with LD” (p.49).

Another concern that has not been fully resolved is what constitutes evidence-based programs suitable at each Tier level, and how are they to be discerned from the plethora of published programs or methods that all claim to be effective? It is difficult for teachers to make such determinations as there is precious little training in research methods in their courses (Lomax, 2004). Recognising this absence from the training curriculum emphasis the National Inquiry into the Teaching of Literacy (2005) recommended that teachers-in-training be provided with a solid understanding of research design to adapt to changing educational policy.

A possible component of any reform movement in Australia arises with the establishment and objectives of the Australian Institute for Teaching and School Leadership (2011). Among the standards and procedures of the Initial Teacher Education Program Accreditation document is: “6. Evidence: The credibility of national accreditation is built on evidence-based practice and contributes to the development of evidence through research about what works in quality teacher education. This evidence in turn informs the development of accreditation, allowing it to focus on those things shown to be related to outcomes” (p.1).

In the meantime, are there any immediate shortcuts to discerning the gold from the dross? If so, where can one find the information about any areas of consensus? Those governments that have moved toward a pivotal role for research in education policy have usually formed panels of prestigious researchers to peruse the evidence in particular areas, and report their findings widely (e.g., National Reading Panel, 2000). They attempt to assemble all the methodologically acceptable research, and synthesise the results, using statistical processes such as meta-analysis, to enable judgements about effectiveness to be made. It involves clumping together the results from many studies to produce a large data set that is intended to reduce the statistical uncertainty that accompanies single studies.

So, there are recommendations for practice produced by these bodies that can become useful resources in answering the question what works? These groups include the National Reading Panel, American Institutes for Research, National Institute for Child Health and Human Development, The What Works Clearinghouse, Florida Center for Reading Research, Coalition for Evidence-Based Policy, and the Best Evidence Encyclopedia among others.

There have been some criticisms of these efforts as the standards they set often preclude huge numbers of studies that don’t meet the gold standard of randomised controlled trials. Stockard (2010) accepted the value of this approach, but argued that including only randomized control trials omits a huge number of studies unnecessarily (What Works Clearinghouse includes no studies prior to 1985), and may actually produce misleading conclusions. For example, of 106 reviews of Reading Recovery, the What Works Clearinghouse found only four met their standards and assigned a medium to large effect on that basis.

So, it is advisable to seek analyses from a number of these review sites. At this time, there is no substitute for being able to analyse research oneself.

Continuing challenges for RTI/MTSS - Its relationship to special education:

“While some states have retained a clear relationship between their tiered approach and special education, others have explicitly stated that RTI or MTSS is a support system for all students and is not a pathway to special education. Both research and practice on RTI, MTSS, and other tiered systems have prioritized the models’ uses for screening-level identification and early intervening. Undoubtedly, students who had historically needed to “wait to fail” before qualifying for special education services (L. Fuchs & Vaughn, 2012) are identified and served sooner under the current models. However, approximately two-thirds of the states do not support a tiered approach for LD identification without still relying on data from additional formal testing. Researchers have speculated that a primary reason for this may be lack of clarity about the psychometric integrity of treatment based diagnoses from tiered models and uncertainty as to how they would satisfy statutory regulations (Hale et al., 2010; cf. Zirkel, 2017). As Hudson and McKenzie (2016a) report, there is wide variation in policy, guidance, and practices across and within states that do allow or require using RTI data for LD identification.” (p.339)

“The evolution in tiered models has also changed the role of the special education teacher (D. Fuchs et al., 2010). In addition to serving students with LD and other disabilities on their caseloads, special educators are also expected to work with their general education colleagues to support any student in need of intervention at any tier. However, many special education teachers in today’s schools are underprepared to meet the needs of the students that they serve (Brownell et al., 2010). A compounding factor is that initiatives such as the inclusion movement and RTI have decreased the numbers of special educators employed in schools, a drop of 17% nationally from 2005 to 2012 (Dewey et al., 2017). One consequence is that fewer specially trained teachers are available to work with their colleagues and serve the unique needs of learners who may have disabilities. When these teachers are then spread thin with the expectation to support all students, it may end up that students with disabilities are not provided the appropriate education they need to receive meaningful educational benefit (Dewey et al., 2017; see Endrew F. v. Douglas County School District, 2017). Hence, students who have disabilities such as LD may be supported in meeting general education curricular demands but not in their individually appropriate education as called for in the IDEA (Calhoon et al., 2019). The debate D. Fuchs et al. (2010) described between those who favor providing supports within or outside of special education systems is unresolved, with the state models indicating both approaches are in practice.” (p.339-340)

Berkeley, S., Scanlon, D., Bailey, T.R., Sutton, J.C., & Sacco, D.M. (2020). A snapshot of RTI implementation a decade later: New picture, same story. Journal of Learning Disabilities, 53(5), 332-342. doi:10.1177/0022219420915867

Inconsistencies across implementation sites are problematic for RTI

“In their review of the implementation science literature, Fixen and colleagues (2005) described implementation as “a process, not an event” (p. 15) that includes the following stages: (a) exploration and adoption, (b) program installation, (c) initial implementation, (d) full operation, (e) innovation, and (f) sustainability. Support for systemic implementation of tiered approaches such as RTI is available to both SEAs and LEAs through the federal Office of Special Education Programs’ (OSEP) technical assistance centers (e.g., National Center on Student Progress Monitoring, National Center on Intensive Intervention [NCII]), state professional development grants, and regional resource centers.… Despite available resources and a growing research base supporting RTI and related models (e.g., Burns et al., 2005; Gersten et al., 2009; Tran et al., 2011), a research-to-practice gap has been documented for on-the-ground implementation. … Several survey studies provide further insight into the breakdown in RTI implementation practices. Bineham and colleagues (2014) surveyed 619 general and special education administrators nationally and found a notable discrepancy between knowing about RTI and knowing how to implement the tiered framework. Al Otaiba and colleagues (2019) surveyed 139 general and special education teachers to understand their knowledge of Tier 1 and preparedness to make data-based decisions. They found teachers reported greater levels of understanding than preparedness to implement. Similar findings have been reported in several other investigations (e.g., Maki et al., 2018; Regan et al., 2015). While teachers and school leaders recognize the importance of multitiered models such as RTI, there is a persistent breakdown in their readiness to implement, which is likely exacerbated by ongoing evolution in thinking around the topic (e.g., Burns et al., 2016; D. Fuchs et al., 2012; L. Fuchs & Vaughn, 2012; Gersten & Dimino, 2006). Despite the enduring lack of clarity surrounding RTI in the field, it has had a significant impact on service delivery models and instructional practices in schools, primarily at the elementary level (Al Otaiba et al., 2014).” (p. 333)

Berkeley, S., Scanlon, D., Bailey, T.R., Sutton, J.C., & Sacco, D.M. (2020). A snapshot of RTI implementation a decade later: New picture, same story. Journal of Learning Disabilities, 53(5), 332-342. doi:10.1177/0022219420915867

Conclusion

This movement represents a change in the way we think about students who do not make good progress in their education. RTI shifts our attention from the characteristics of the learner to those of the teaching process. As educators, our capacity to influence student performance is more fruitfully focused upon what we can contribute rather than solely on what the student brings. The environment and what conditions promote achievement become our tools.

A consequence of this change is that we no longer require struggling students to obtain some form of diagnosis before we act. We can observe and act quickly, rather than forcing children into an extended “wait-to-fail” situation before assistance can be provided.

Effective early intervention can provide sufficient impetus to overcome any initial struggles before the debilitating effects of chronic failure become entrenched. It also enables our scarce resources to be available to the more severely hampered students.

“The RTI/MTSS framework is designed as a model for early intervention (Connor et al., 2014), meaning that it is intended to address academic and behavioral difficulties as early as possible in a child’s school career. Multi-tier instructional efforts have the potential to prevent struggling readers from facing long-term impact on their academic success. In the realm of intervention, there is an important emphasis on providing early intervention in order to proactively address academic difficulties (Connor et al., 2014; Gersten et al., 2008). (p.3)

Forsythe, L., Kohn, A., & Arnett, M. (2021). High-quality interventions to ensure literacy for all students. Center for the Collaborative Classroom. https://public.cdn.ccclearningportal.org/program/resources/field-team/MKT-5147-highqualityinterventions-whitepaper.pdf

“As is clear in this study, RTI approach in early childhood(specially kindergarten children identified as at risk for the acquisition of beginning reading)presumes use of evidence-based practices , and is an emerging practice with a promise that will lead to greater levels of effectiveness in teaching children reading sub-skills such as those taught in this study (e.g. letter naming knowledge and spelling knowledge).The results from this study were in the same line with those obtained by Kamps et al. (2007) who investigated the effect of three reading programs along with evidence-based direct instruction in small groups of at-risk students, using Tier 2 intervention. The programs employed were found to be strongly effective with at-risk students. Furthermore, differentiating instruction based on approaches such as of response-to-intervention model supported Linan-Thompson, Cirino & Vaughn (2007) suggestion that explicit, systematic, and intensive interventions should be provided to children who are at risk of lagging behind their same-aged- peers in reading. As indicated by Charles et al. (2013) "RTI holds the promise of preventing early delays from becoming disabilities later by intervening sooner to meet children's needs" (p. 2).” (p. 2039)

Eissa, M.A. (2020). Effects of RTI on letter naming and spelling among kindergarteners at risk for reading failure. Elementary Education Online, 19(4), 2032-2041. doi:10.17051/ilkonline.2020.763216

In the longer term, we should have the capacity to accurately screen students well prior to their first contact with literacy, thereby eliminating rather than just reducing, the failure period that is so damaging to children’s educational and personal development.

References

Aaron, P. G., Joshi, M., & Williams, K. A. (1999). Not all reading disabilities are alike. Journal of Learning Disabilities, 32, 120–137.

Abbott, M., Wills, H., Greenwood, C.R., Kamps, D., Heitzman-Powell, L., & Selig, J. (2010). The combined effects of grade retention and targeted small-group intervention on students' literacy outcomes. Reading & Writing Quarterly: Overcoming Learning Difficulties, 26(1), 4-25.

Al Otaiba, S., Connor, C., Lane, H., Kosanovich, M.L., Schatschneider, C., Dyrlund, A.K., Miller, M.S., & Wright, T.L. (2008). Reading First kindergarten classroom instruction and students' growth in phonological awareness and letter naming–decoding fluency. Journal of School Psychology, 46(3), 281-314.

Al Otaiba, S., Puranik, C.S., Rouby, D.A., Greulich, L., Sidler, J.F., Lee, J. (2010). Predicting kindergarteners' end-of-year spelling ability based on their reading, alphabetic, vocabulary, and phonological awareness skills as well as prior literacy experiences. Learning Disability Quarterly, 33(3), 171-183.

Alber-Morgan, S. (2010). Using RTI to teach literacy to diverse learners, K-8: Strategies for the inclusive classroom. Thousand Oaks, CA: Corwin Press.

Algozzine, R., McCart, A., & Goodman, S. (2011). Teaching academics and behavior: What comes first? [solving the-chicken-or-the-egg dilemma]. National PBIS Leadership Forum, Hyatt Regency O’Hare Rosemont, Illinois October 27.

Allan, S. D., & Goddard, Y. L. (2010). Differentiated instruction and RTI: A natural fit. Educational Leadership, 68(2). Retrieved from http://www.ascd.org/publications/educational-leadership/oct10/vol68/num02/Differentiated-Instruction-and-RTI@-A-Natural-Fit.aspx

Australian Institute for Teaching and School Leadership. (2011). Initial Teacher Education Program Accreditation. Retrieved from http://www.aitsl.edu.au/teachers/accreditation-of-initial-teacher-education/initial-teacher-education-program-accreditation.html

Ball, C. R. & Christ, T. J. (2012), Supporting valid decision making: Uses and misuses of assessment data within the context of RTI. Psychology in the Schools, 49(3), 231–244.

Balu, R., Zhu, P., Doolittle, F., Schiller, E., Jenkins, J., & Gersten, R. (2015). Evaluation of response to intervention practices for elementary reading (NCEE 2016‐4000). Washington, DC: U.S. Department of Education, Institute of Education Sciences

Baskette, M.R., Ulmer, L., & Bender, W.N. (2006, Fall). The emperor has no clothes! Unanswered questions and concerns on the response to intervention procedure. The Journal of the American Academy of Special Education Professionals, Fall, 4-24. Retrieved from http://www.naset.org/fileadmin/user_upload/JAASEP/Response_to_Intervention_Procedure.pdf

Binder, C., Haughton, E., & Bateman, B. (2002). Fluency: Achieving true mastery in the learning process. Retrieved from www.fluency.org/Binder_Haughton_Bateman.pdf

Bradley, R., Danielson, L., & Doolittle, J. (2005). Response to intervention. Journal of Learning Disabilities, 38(6), 485-486.

Campbell, L., Campbell, C., & Dickinson, D. (1999). Teaching and learning through the multiple intelligences (2nd ed.). Needham Heights: Allyn and Bacon.

Carnine, D. (1991). Curricular interventions for teaching higher order thinking to all students: Introduction to the special series. Journal of Learning Disabilities, 24, 261-269.

Carnine, D. (2000). Why education experts resist effective practices (and what it would take to make education more like medicine). Washington, DC: Fordham Foundation. Retrieved from http://www.sc-boces.org/english/IMC/Focus/DirectInstruction-carnine_article.pdf

Carnine, D. (2003, Mar 13). IDEA: Focusing on improving results for children with disabilities. Hearing before the Subcommittee on Education Reform Committee on Education and the Workforce United States House of Representatives. Retrieved from http://edworkforce.house.gov/hearings/108th/edr/idea031303/carnine.htm

Cassidy, J., Ortlieb, E., & Shettel, J (2012). What’s Hot and What’s Not? 2011 Results. International Reading Association. Retrieved from http://www.reading.org/General/Publications/ReadingToday/RTY-decjan-20102011-surveyprimary.aspx

Chall, J. S. (1967). The great debate. New York: McGraw Hill.

Chambless, D. L. & Ollendick, T. H. (2001). Empirically supported psychological interventions: Controversies and evidence. Annual Review of Psychology, 52, 685-716.

Conversations in literacy (2012). Guiding students to better reading. Retrieved from http://conversationsinliteracy.blogspot.com.au/2012/01/rti-moving-thru-tiers-without-moving.html

Cuttance, P. (2005). Education research 'irrelevant.' The Age, July 5, p.5.

de Haan, M. (2021) .Supporting struggling adolescent readers through the Response to Intervention (RTI) framework. Australian Journal of Learning Difficulties, 26(1), 47-66, DOI: 10.1080/19404158.2020.1870512

Department for Children, Schools, and Families. (2009). Every child a reader – the layered approach. Retrieved from http://readingrecovery.ioe.ac.uk/documents/Layered_approach.pdf

Department for Education. (2012). Year 1 phonics screening check FAQs. Retrieved from http://www.education.gov.uk/schools/teachingandlearning/pedagogy/a00198207/faqs-year-1-phonics-screening-check#faq1

Elbaum, B., Vaughn, S., Hughes, M.T., & Moody, S.W. (2000). How effective are one-to-one tutoring programs in reading for elementary students at risk for reading failure? A meta-analysis of the intervention research. Journal of Educational Psychology, 92(4), 605-619.

Epps, S., & Tindal, G. (1988). The effectiveness of differential programming in serving students with mild handicaps: Placement options and instructional programming. In M. C. Wang, M. C. Reynolds, & H. J. Walberg (Eds.), Handbook of special education: Research and practice, Volume I (pp. 213–248). New York: Pergamon Press.

Esparza Brown, J., & Doolittle, J. (2008). A cultural, linguistic, and ecological framework for Response to Intervention with English Language Learners. National Center for Culturally Responsive Education Systems (NCCREST). Retrieved from http://www.nccrest.org/Briefs/Framework_for_RTI.pdf

Fielding, L., Kerr, N., &Rosier, P. (2007). Annual growth for all students, Catch-up growth for those who are behind. Kennewick, WA: The New Foundation Press, Inc.

Fielding-Barnsley, R. (2010). Australian pre-service teachers' knowledge of phonemic awareness and phonics in the process of learning to read. Australian Journal of Learning Difficulties, 15(1), 99-110.

Fielding-Barnsley, R., and Purdie, N. (2005). Teacher’s attitude to and knowledge of metalinguistics in the process of learning to read. Asia-Pacific Journal of Teacher Education, 33(1), 65-76.

Fisher, B.J., Bruce, M.E., & Greive, C. (2007). The entry knowledge of Australian pre-service teachers in the area of phonological awareness and phonics. In A Simpson (Ed.). Future directions in literacy: International conversations 2007. University of Sydney. Retrieved from http://ses.library.usyd.edu.au/bitstream/2123/2330/1/FutureDirections_Ch5.pdf

Fletcher, J. M., Francis, D. J., Shaywitz, S. E., Lyon, G. R., Foorman, B. R., Stuebing, K. K., & Shaywitz, B. A. (1998). Intelligent testing and the discrepancy model for children with learning disabilities. Learning Disabilities Research and Practice, 13(4), 186-203.

Fox, L., Carta, J., Strain, P.S., Dunlap, G., & Hemmeter, M.L. (2010). Response to intervention and the pyramid model. Infants & Young Children, 23(1), 3–13.

Freebody, P., & Luke, A. (1990). Literacies programs: Debates and demands in cultural context. Prospect, 5(3), 7–16.

Fuchs, L.S., Fuchs, D., Hosp, M.K., & Jenkins, J.R. (2001). Oral reading fluency as an indicator of reading competence: A theoretical, empirical, and historical analysis. Scientific Studies of Reading, 5(3), 239-256.

Galletly, S.A., & Knight, B.A. (2006). The Dynamic Indicators of Basic Early Literacy Skills (DIBELS) used in an Australian context. Australian Journal of Learning Disabilities, 11(3), 147-154.

Gersten, R., Compton, D., Connor, C.M., Dimino, J., Santoro, L., Linan-Thompson, S., and Tilly, W.D. (2008). Assisting students struggling with reading: Response to Intervention and multi-tier intervention for reading in the primary grades. A practice guide. (NCEE 2009-4045). Washington, DC: National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education. Retrieved from http://ies.ed.gov/ncee/wwc/publications/practiceguides/

Good, R. H., & Kaminski, R. A. (2002). Dynamic indicators of basic early literacy skills (6th ed.). Eugene, OR: Institute for Development of Educational Achievement.

Good, R.H., & Kaminski, R.A. (1996). Assessment for instructional decisions: Toward a proactive/prevention model of decision-making for early literacy skills. School Psychology Quarterly, 11(4), 326-336.

Goyen, J. D. (1992). Diagnosis of reading problems: Is there a case? Educational Psychology, 12(3/4), 225-237.

Gresham, F. (2001, August). Response to Intervention: An alternative approach to the identification of learning disabilities. Paper presented at the Learning Disabilities Summit: Building a Foundation for the Future (Washington, DC, August 27-28, 2001).

Gresham, F.M., & Vellutino, F.R. (2010). What is the role of intelligence in the identification of specific learning disabilities? Issues and clarifications. Learning Disabilities Research & Practice, 25(4), 194–206.

Haager, D. (2007). Promises and cautions regarding using response to intervention with English language learners. Learning Disability Quarterly, 30(3), 213-218.

Haager, D., & Mahdavi, J. (2007). Teacher rules in implementing intervention. In Diane Haager, Janette Klingner, & Sharon Vaughn, (Eds.). Evidence-based reading practices for response to intervention (p. 245-264). 

Hale, J., Alfonso, V., Berninger, V., Bracken, B., Christo, C., Clark, E., Cohen, M., Davis, A., Decker, S., Denckla, M., Dumont, R., Elliott, C. Feifer, S., Fiorello, C., Flanagan, D., Fletcher-Janzen, E., Geary, D., Gerber, M., Gerner, M., Goldstein, S., Gregg, N., Hagin, R., Jaffe, L., Kaufman, A., Kaufman, N., Keith, T., Kline, F., Kochhar-Bryant, C., Lerner, J., Marshall, G., Mascolo, J., Mather, N., Mazzocco, M., McCloskey, G., McGrew, K., Miller, D., Miller, J., Mostert, M., Naglieri, J., Ortiz, S., Phelps, L., Podhajski, B., Reddy, L., Reynolds, C., Riccio, C., Schrank, F., Schultz, E., Semrud-Clikeman, M., Shaywitz, S., Simon, J., Silver, L., Swanson, L., Urso, A., Wasserman, T., Willis, J., Wodrich, D., Wright, P., & Yalof, J. (2010). Critical issues in Response-To-Intervention, comprehensive evaluation, and specific learning disabilities identification and intervention: An expert white paper consensus. Learning Disability Quarterly, 33, 223-236. Retrieved from http://www.iapsych.com/articles/hale2010.pdf

Harn, B.A. Jamgochian, E., & Parisi, D.M. (2009). Characteristics of students who don’t respond to research-based interventions. Council for Exceptional Children. Retrieved from http://www.cec.sped.org/AM/Template.cfm?Section=CEC_Today1&TEMPLATE=/CM/ContentDisplay.cfm&CONTENTID=10645

Hasbrouck, J., & Tindall, G. (2005). Oral reading fluency: Ninety years of measurement. (BRT Technical Report No. 33), Eugene, OR: Author. Retrieved from http://brt.uoregon.edu/techreports/.

Hazelkorn, M., Bucholz, J.L., Goodman, J.I., Duffy, M.L., & Brady, M.P. (2011). Response to Intervention: General or special education? Who is responsible? The Educational Forum, 75(1), 17-25.

Hempenstall, K. (2006). What does evidence-based practice in education mean? Australian Journal of Learning Disabilities, 11(2), 83-92.

Hernández Finch, M. E. (2012). Special considerations with response to intervention and instruction for students with diverse backgrounds. Psychology in the Schools, 49(3), 285–296.

Hoover, J.J., Baca, L., Wexler-Love, E., & Saenz, L. (2008). National implementation of Response to Intervention (RTI): Research summary. National Association of State Directors of Special Education. Retrieved from http://www.nasdse.org/Portals/0/NationalImplementationofRTI-ResearchSummary.pdf

Hosp, M.K. (2007). The ABCs of progress monitoring in reading. National Center on Student Progress Monitoring. Retrieved from http://www.studentprogress.org/weblibrary.asp#reading

Hughes, C. E., Rollins, K., & Coleman, M. R. (2011). Response to intervention for gifted learners. In M. Coleman & S. Johnsen (Eds.), RtI for gifted students: A CEC-TAG educational resource (pp. 1-20). Waco, TX: Prufrock Press

Ikeda, M.J., Rahn-Blakeslee, A., Niebling, B.C., Allison, R., NCSP, & Stumme, J. (2006). Evaluating evidence-based practice in response-to-intervention systems. NASP Communiqué, 34(8). Retrieved from http://www.nasponline.org/publications/cq/cq348evaloutcomes.aspx

International Literacy Association. (2020). What’s hot in literacy report. Newark, DE: Author. https://www.literacyworldwide.org/docs/default-source/resource-documents/whatshotreport_2020_final.pdf

Isaacs, D., & Fitzgerald, D. (1999).  Seven alternatives to evidence based medicine. British Medical Journal, 319(7225), 1618-1618.

Jones, R. E., & Ball, C. R. (2012). Introduction to the special issue: Addressing response to intervention implementation: Questions from the field. Psychology in the Schools, 49(3), 207–209.

Jones, R. E., Yssel, N., & Grant, C. (2012). Reading instruction in tier 1: Bridging the gaps by nesting evidence-based interventions within differentiated instruction. Psychology in the Schools, 49(3), 210–218.

Joseph, L. M., & Schisler, R. (2009). Should adolescents go back to the basics?: A review of teaching word reading skills to middle and high school students RASE TL & LD. Remedial and Special Education, 30(3), 131-147.

Joyce, B., & Showers, B. (2002). Student achievement through staff development (3rd Ed.). White Plains, NY: Longman Publishers.

Kavale, K. A., & Mostert, M. P. (2003). River of ideology, islands of evidence. Exceptionality, 11(4), 191– 208.

Kirk, S. A. (1963). Behavioral diagnosis and remediation of learning disabilities. Proceedings of the annual meeting of the Conference on Exploration into the Problems of the Perceptually Handicapped Child (1), 1-23. Evanston, IL.

Koellner, K., Colsman, M., & Risley, R. (2011). Multidimensional assessment: Guiding response to intervention in mathematics. Teaching Exceptional Children, 44(2), 48-56.

Koutsoftas, A. D., Harmon, M. T., & Gray, S. (2009). The effects of tier 2 intervention for phonemic awareness in a response-to-intervention model in low income preschool classrooms. Language, Speech and Hearing Services in Schools, 40(2), 116-130.

Kranzler, J. H., Yaraghchi, M., Matthews, K., & Otero-Valles, L. (2020). Does the response-to-intervention model fundamentally alter the traditional conceptualization of specific learning disability? Contemporary School Psychology, 24, 80-88.

Kuhn, M.R., & Stahl, S.A. (2003). Fluency: A review of developmental and remedial practices. Journal of Educational Psychology, 95(1), 3-21.

Lane, K. L., Oakes, W. P., & Menzies, H. M. (2010). Systematic screenings to prevent the development of learning and behavior problems: Considerations for practitioners, researchers, and policy makers. Journal of Disabilities Policy Studies, 21, 160-172.

Lembke, E. S., Hampton, D., & Beyers, S. J. (2012). Response to intervention in mathematics: Critical elements. Psychology in the Schools, 49(3), 257–272.

Lilienfeld, S.O., Ammirati, R., & David, M. (2012). Distinguishing science from pseudoscience in school psychology: Science and scientific thinking as safeguards against human error. Journal of School Psychology, 50(1), 7-36.

Lindsley, O. R. (1990). Precision Teaching: By children for teachers. Teaching Exceptional Children, 22(3), 10-15.

Linklater, D.L., O'Connor, R.E., & Palardy, G.J. (2009). Kindergarten literacy assessment of English Only and English language learner students: An examination of the predictive validity of three phonemic awareness measures, Journal of School Psychology, 47(6), 369-394.

Lomax, R.G. (2004). Whither the future of quantitative literacy research? Reading Research Quarterly, 39(1), 107-112.

Louden, W., Rohl, M., Gore, J., Greaves, D., Mcintosh, A., Wright, R., Siemon, D., & House, H. (2005). Prepared to teach: An investigation into the preparation of teachers to teach literacy and numeracy. Canberra, ACT: Australian Government Department of Education, Science and Training.

Lyon, G.R. (1999). Special education a failure on many fronts. LA Times, 12/12/1999. Retrieved from http://articles.latimes.com/1999/dec/12/news/mn-43238

Lyon, G.R., & Fletcher, J.M. (2003). Early identification, prevention, and early intervention for children at-risk for reading failure. Basic Education, Council for Basic Education. Retrieved from http://www.cdl.org/resource-library/articles/early_id.php?type=subject&id=10

Manolitsis, G., & Tafa, E. (2011). Letter-name letter-sound and phonological awareness: Evidence from Greek-speaking kindergarten children. Reading and Writing: An Interdisciplinary Journal, 24(1), 27-53.

Mastropieri, M.A., Leinart, A.W., & Scruggs, T.E. (1999). Strategies to increase reading fluency. Intervention in School and Clinic, 34(5), 278-283, 292.

McDougal, J., Clark, K., & Wilson, J. (n.d.). Graphing made easy: Practical tools for school psychologists. State University of New York at Oswego. Retrieved from http://www.oswego.edu/~mcdougal/web_site_4_11_2005/index.html

McLeskey, J., & Waldron, N. (2011). Educational programs for elementary students with learning disabilities: Can they be both effective and inclusive? Learning Disabilities Research & Practice, 26(1), 48–57.

McMaster, K. L., Kung, S., Han, I., & Cao, M. (2008). Peer-assisted learning strategies: A "tier 1" approach to promoting English learners response to intervention. Exceptional Children, 74(2), 194-214.

McMaster, K.L., Ritchey, K.D., & Lembke, E. (2011). Curriculum-based measurement for beginning writers: Recent developments and future directions, in Thomas E. Scruggs, Margo A. Mastropieri (ed.) Assessment and Intervention (Advances in Learning and Behavioral Disabilities, Volume 24), Emerald Group Publishing Limited, pp.111-148.

Mellard, D. (2010). Fidelity of implementation within a Response to Intervention (RtI) framework. National Center on Response to Intervention. Retrieved from http://www.ped.state.nm.us/rti/dl11/11-Fidelity%20of%20Implementation%20guidev5.pdf

Mellard, D., McKnight, M., & Jordan, J. (2010). RTI tier structures and instructional intensity. Learning Disabilities Research & Practice, 25(4), 217–225.

Mitchell, B.S., Stormont, M., & Gage, N.A. (2011). Tier two interventions implemented within the context of a tiered prevention framework. Behavioral Disorders, 36(4), 241-261.

Morris, R.D., Lovett, M.W., Wolf, M., Sevcik, R.A., Steinbach, K.A., Frijters, J.C., & Shapiro, M.B. (2012). Multiple-component remediation for developmental reading disabilities: IQ, socioeconomic status, and race as factors in remedial outcome. Journal of Learning Disabilities, 45(2), 99-127.

Nagy, W. E., & Anderson, R. C. (1984). How many words are there in printed English? Reading Research Quarterly, 19(3), 304-330.

National Center on Response to Intervention. (2010). Essential components of RTI—A closer look at response to intervention. Washington, DC: U.S. Department of Education, Office of Special Education Programs, National Center on Response to Intervention.

National College for School Leadership (2010). About personalised learning. Retrieved from http://www.nationalcollege.org.uk/index/leadershiplibrary/leadingschools/personalisedlearning/about-personalised-learning.htm

National High School Center, National Center on Response to Intervention, and Center on Instruction. (2010). Tiered interventions in high schools: Using preliminary ‘lessons learned’ to guide ongoing discussion. Washington, DC: American Institutes for Research. Retrieved from www.rti4success.org

National Inquiry into the Teaching of Literacy. (2005). Teaching Reading: National Inquiry into the Teaching of Literacy. Canberra: Department of Education, Science, and Training. Retrieved from www.dest.gov.au/nitl/report.htm

Primary National Strategy. (2006). Leading on Intervention: A resource to support leadership teams and leading teachers. Retrieved from http://www.teachfind.com/national-strategies/waves-intervention-model-0

National Reading Panel. (2000). Teaching children to read: An evidence-based assessment of the scientific research literature on reading and its implications for reading instruction. Washington, DC: U.S. Department of Health and Human Services.

Nellis, L. M. (2012). Maximizing the effectiveness of building teams in response to intervention implementation. Psychology in the Schools, 49(3), 245–256.

O'Connor, E. P., & Freeman, E. W. (2012). District-level considerations in supporting and sustaining RtI implementation. Psychology in the Schools, 49(3), 297–310.

O'Connor, R.E., Bell, K.M., Harty, K.R., Larkin, L.K., Sackor, S.M., & Zigmond, N. (2002). Teaching reading to poor readers in the intermediate grades: A comparison of text difficulty. Journal of Educational Psychology, 94(3), 474-485.

OECD. (2004). Adults at low literacy level (most recent) by country. International Adult Literacy Survey (IALS). Retrieved from http://www.nationmaster.com/graph/edu_lit_adu_at_low_lit_lev-education-literacy-adults-low-level

Orosco, M.J., & Klingner, J. (2010). One school’s implementation of RTI with English Language Learners: “Referring into RTI”. Journal of Learning Disabilities, 43(3) 269–288.

Psychological Corporation (2007). AIMSweb progress monitoring and response to intervention system. San Antonio, TX: Pearson. Retrieved from www.aimsweb.com

Pyle, N., & Vaughn, S. (2012). Remediating reading difficulties in a response to intervention model with secondary students. Psychology in the Schools, 49(3), 273–284.

Rasinski, T., Homan, S., & Biggs, M. (2009). Teaching reading fluency to struggling readers: Method, materials, and evidence. Reading & Writing Quarterly, 25(2), 192-204.

Reschly, A.L., Busch, T.W., Betts, J. Deno, S.L., & Long, J.D. (2009). Curriculum-Based Measurement Oral Reading as an indicator of reading achievement: A meta-analysis of the correlational evidence, Journal of School Psychology, 47(6), 427-469.

Roberts, G., Torgesen, J.K., Boardman, A., & Scammacca, N. (2008) Evidence-based strategies for reading instruction of older students with learning disabilities. Learning Disabilities Research & Practice 23(2), 63–69.

Rohl, M., & Greaves, D. (2005). How are pre-service teachers in Australia being prepared for teaching literacy and numeracy to a diverse range of students? Australian Journal of Learning Disabilities, 10(1), 3-8.

Rorris, A., Weldon, P., Beavis, A., McKenzie, P., Bramich, M., & Deery, A. (2011). Assessment of current process for targeting of schools funding to disadvantaged students. An Australian Council for Educational Research report prepared for The Review of Funding for Schooling Panel.

Scarborough, H. S. (1998). Early identification of children at risk for reading disabilities: Phonological awareness and some other promising predictors. In B. K. Shaprio, P. J. Accardo, & A. J. Capute (Eds.), Specific reading disability: A view of the spectrum (pp. 75-119). Timonium, MD: York Press.

Schatschneider, C., Francis, D. J., Foorman, B. R., Fletcher, J. M., & Mehta, P. (1999). The dimensionality of phonological awareness: An application of item response theory. Journal of Educational Psychology, 91(3), 439-449.

Senate Employment, Workplace Relations and Education Committee. (2007). Quality of school education. Commonwealth of Australia. Retrieved from http://www.aph.gov.au/SEnate/committee/eet_ctte/completed_inquiries/2004-07/academic_standards/index.htm

Seungsoo, Y., Dong-Il, K., Lee Branum-Martin, L., Wayman, M.M., & Espin, C.A. (2012). Assessing the reliability of curriculum-based measurement: An application of latent growth modelling. Journal of School Psychology, 50(2), 275-292.

Sideridis, G.D. (2011). Exploring the presence of Matthew Effects in learning disabilities. Journal of Learning Disabilities, 44(4), 399-401.

Siegel, L. S. (1989). IQ is irrelevant to the definition of learning disabilities. Journal of Learning Disabilities, 22(8), 469-479.

Siegel, L. S. (1992). An evaluation of the discrepancy definition of dyslexia. Journal of Learning Disabilities, 25(10), 618–629.

Smith, F. (1992). Learning to read: The never-ending debate. Phi Delta Kappan, 73(6), 432-441.

Solomon, B. G., Klein, S. A., Hintze, J. M., Cressey, J. M., & Peller, S. L. (2012). A meta-analysis of school-wide positive behavior support: An exploratory study using single-case synthesis. Psychology in the Schools, 49(2), 105–121.

Spectrum K12. (2012). 2011 RTI adoption survey. Retrieved from www.globalscholar.com/2011RTI

Speece, D. L., Mills, C., Ritchey, K. D., & Hillman, E. (2003). Initial evidence that letter fluency tasks are valid indicators of early reading skill. Journal of Special Education, 36, 223-233.

Stage, S.A., Sheppard, J., Davidson, M.M., & Browning, M.M. (2001). Prediction of first-graders' growth in oral reading fluency using kindergarten letter fluency. Journal of School Psychology, 9(3), 225-237.

Stainback, W., & Stainback, S. (Eds.) (1992). Controversial issues confronting special education: Divergent perspectives. Boston: Allyn and Bacon.

Stanovich, K. E. (1986). Matthew effects in reading: Some consequences of individual differences in the acquisition of literacy. Reading Research Quarterly, 21, 360-406. 

Stanovich, K. E. (1988a). Explaining the differences between the dyslexic and the garden-variety poor reader: The phonological-core variable-difference model. Journal of Learning Disabilities, 21(10), 590-612.

Stanovich, K. E. (1988b). The right and wrong places to look for the cognitive locus of reading disability. Annals of Dyslexia, 38, 154-157. 

Stanovich, K. E. (1991). Discrepancy definitions of reading disability: Has intelligence led us astray? Reading Research Quarterly, 26(1), 7–29.

Stanovich, K. E. (1992). Speculation on the causes and consequences of individual differences in early reading acquisition. In Phillip P. Gough, Linnea C Ehri, & Rebecca Treiman (Eds.), Reading acquisition. (pp.307-341). USA: Lawrence Erlbaum.

Stanovich, K. E. (1993). Does reading make you smarter? Literacy and the development of verbal intelligence. In H. Reese (Ed.), Advances in child development and behavior (Vol. 24, pp. 133-180). San Diego, CA: Academic Press.

Stecker, P.M., & Lembke, E.S. (2007). Advanced applications of CBM in reading (K–6): Instructional decision-making strategies manual. National Center on Student Progress Monitoring. Retrieved from http://www.studentprogress.org/summer_institute/2007/Adv%20Reading/AdvRdgManual_2007.doc

Stockard, J. (2010). An analysis of the fidelity implementation policies of the What Works Clearinghouse. Current Issues in Education, 13(4). Retrieved from http://cie.asu.edu/

Strong, R. W., Silver, H. F., & Perini, M. J. (2001). Making students as important as standards. Educational Leadership, 59(3), 56-61.

Stuart, M. (1995). Prediction and qualitative assessment of five and six-year-old children's reading: A longitudinal study. British Journal of Educational Psychology, 65, 287-296.

Stuebing, K. K., Fletcher, J. M., LeDoux, J. M., Lyon, G. R., Shaywitz, S. E., & Shaywitz, B. A. (2002). Validity of IQ-discrepancy classifications of reading disabilities: A meta-analysis. American Educational Research Journal, 39(2), 469–518.

Sugai, G., Simonsen, B., Coyne, M., & Faggella-Luby, M. (2007). A school improvement framework for promoting evidence-based academic and behavior supports. Presentation at Closing the Achievement Gap Conference, University of Connecticut, Storrs. Retrieved from http://www.pbis.org/pbis_resource_detail_page.aspx?Type=1&PBIS_ResourceID=143

Swanson, H.L. (2001). Research on interventions for adolescents with learning disabilities: A meta-analysis of outcomes related to higher-order processing. The Elementary School Journal, 101(3), 331-348.

Swanson, H.L., & Hoskyn, M. (1998). Experimental intervention research on students with learning disabilities: A meta-analysis of treatment outcomes. Review of Educational Research, 68(3), 277-321.

Swanson, H.L., & O’Connor, R.E. (2009). The role of working memory and fluency training on reading comprehension in children who are dysfluent readers. Journal of Learning Disabilities, 42, 548-575.

Tomlinson, C. (1999). The differentiated classroom: Responding to the needs of all learners. Alexandria, VA: ASCD.

Tomlinson, C. A., & Allan, S. (2000). Leadership for differentiating schools and classrooms. Alexandria, VA: ASCD.

Torgesen, J. (2003). Using science, energy, patience, consistency, and leadership to reduce the number of children left behind in reading. Barksdale Reading Institute, Florida. Retrieved from http://www.fcrr.org/staffpresentations/Joe/NA/mississippi_03.ppt

Torgesen, J., Myers, M., Schirm, A., Stuart, E., Vartivarian, S., Mansfield, W., Stancavage, F., Durno, D., Javorsky, R., & Haan, C. (2006). National Assessment of Title I Interim Report to Congress: Volume II: Closing the Reading Gap, First Year Findings from a Randomized Trial of Four Reading Interventions for Striving Readers. Washington, DC: U.S. Department of Education, Institute of Education Sciences.

Torgesen, J.K. (1998, Spring/Summer). Catch them before they fall: Identification and assessment to prevent reading failure in young children. American Educator. Retrieved from http://www.ldonline.org/article/225/

Tunmer, W., & Greaney, K. (2010). Defining dyslexia. Journal of Learning Disabilities, 43(3), 229–243.

UNICEF. (2002). A league table of educational disadvantage in rich nations. Innocenti Report Card No.4, November 2002. Florence, Italy: Innocenti Research Centre.

Vadasy, P.F., Jenkins, J.R., & Pool, K. (2000). Effects of tutoring in phonological and early reading skills on students at risk for reading disabilities Journal of Learning Disabilities, 33, 579-590.

van Kraayenoord, C.E. (2010). Response to intervention: New ways and wariness. Reading Research Quarterly, 45(3), 363-376.

VanDerHeyden, A. M., Snyder, P. A., Broussard, C., & Ramsdell, K. (2007). Measuring response to early literacy intervention with preschoolers at risk. Topics in Early Childhood Special Education, 27(4), 232-249.

Vaughn, S., & Dammann, J.E. (2001). Science and sanity in special education. Behavioral Disorders, 27(1), 21–29.

Vaughn, S., Cirino, P. T., Wanzek, J., Wexler, J., Fletcher, J. M., Denton, C. A., Barth, A.E., & Francis, D. J. (2010). Response to intervention for middle school students with reading difficulties: Effects of a primary and secondary intervention. School Psychology Review, 39(1), 3-21.

Vaughn, S., Denton, C. A., & Fletcher, J. M. (2010). Why intensive interventions are necessary for students with severe reading difficulties. Psychology in the Schools, 47(5), 432–444.

Vaughn, S., Fletcher, J. M., Francis. D. J., Denton, C. A., Wanzek, J., Wexler, J., Cirino, P.T., Barth, A.E., & Romain, M. A. (2008). Response to intervention with older students with reading difficulties. Learning and Individual Differences, 18(3), 338-345.

Vaughn, S., Wanzek, J., Wexler, J., Barth, A.E., Cirino, P.T., Fletcher, J.M., Romain, M.A., Denton, C.A., Roberts, G., & Francis, D.J. (2010). The relative effects of group size of reading progress of older students with reading difficulties. Reading and Writing: An Interdisciplinary Journal, 23(8), 931-956.

Vellutino, F. R., Scanlon, D. M., Sipay, E. R., Small, S., Chen, R., Pratt, A., & Denckla, M. B. (1996). Cognitive profiles of difficult to remediate and readily remediated poor readers: Early intervention as a vehicle for distinguishing between cognition and experiential deficits as basic cause of specific reading disability. Journal of Educational Psychology, 88(4), 601-638.

Vervaeke, S.-L., McNamara, J. K., & Scissons, M. (2007). Kindergarten screening for reading disabilities. Journal of Applied Research on Learning, 1(1), 1-19.

Victorian Auditor-General. (2009). Literacy and numeracy achievement. Retrieved from http://www.audit.vic.gov.au/reports__publications/reports_by_year/2009/20090204_literacy_numeracy/1_executive_summary.aspx

Wanzek, J., & Vaughn, S. (2008). Response to varying amounts of time in reading intervention for students with low response to intervention. Journal of Learning Disabilities, 41(2), 126-142.

Weaver, C. (1988). Reading: Progress and practice. Portsmouth, NJ: Heinemann.

Wedl, R. (2005). Response to intervention: An alternative to traditional eligibility criteria for student’s with disabilities.  Retrieved from http://www.educationevolving.org/pdf/Response_to_Intervention.pdf

Xu, Y., & Drame, E. (2008). Culturally appropriate context: Unlocking the potential of response to intervention for English Language Learners. Early Childhood Education Journal, 35(4), 305-311.

Dr Kerry Hempenstall, Senior Industry Fellow, School of Education, RMIT University, Melbourne, Australia. 2021

Each of my articles is available as a PDF at https://tinyurl.com/y6vat4ut

It is worthwhile separating the terms neuroscience from brain-based teaching/learning. The first involves science; whereas, the second varies from the useful to the fanciful. Some writers are sceptical about the second field, and others are more optimistic about the future if not so impressed by its current status. One caveat is that it is true that neuroscience studies can show something of what is happening in the brain when individuals engage in reading. However, they don’t show how the two groups arrived at their skilled or unskilled status, nor how the unskilled might become skilled readers. We continue to need cognitive and behavioural research to do that. It’s also important to appreciate the possibility that the noted brain processes in unskilled readers are possibly a consequence rather than a cause of their struggles with reading. Of course, if there are atypical brain processes discernible among children prior to reading instruction, then the neuroscience techniques, such as brain imaging, could become a potential means of early identification and hence earlier intervention that is currently performed. Intervening directly on the brain, that is, other than by environmental intervention such as reading instruction, is in its infancy.

One such (somewhat scary) area is neurotechnology:

“‘Neurotechnology’ is a broad field of brain-centred research and development dedicated to opening up the brain to computational analysis, modification, simulation and control. It includes advanced neural imaging systems for real-time brain monitoring; brain-inspired ‘neural networks’ and bio-mimetic ‘cognitive computing’; synthetic neurobiology; brain-computer interfaces and wearable neuroheadsets; brain simulation platforms; neurostimulator systems; personal neuroinformatics; and other forms of brain-machine integration (Nuffield Council on Bioethics, 2013; Rose et al. 2016; Yuste et al. 2017). … A vast range of techniques has been developed ‘aimed at cognitive modification and enhancement’, such as ‘brain-machine interfaces, … electric stimulators, and brain mapping technologies’, which ‘now target the brain for modification and rewiring’ (Pitts-Taylor 2016: 18).” (p.66)

Williamson, B. (2019). Brain data: scanning, scraping and sculpting the plastic learning brain through neurotechnology. Postdigital Science and Education, 1, 65–86. https://doi.org/10.1007/s42438-018-0008-5

Back to the here and now - neuroscience and education: What’s the potential link?

“Education is about enhancing learning, and neuroscience is about understanding the mental processes involved in learning. This common ground suggests a future in which educational practice can be transformed by science, just as medical practice was transformed by science about a century ago.” (Royal Society, 2011, p. v)

Royal Society. (2011). Brain waves module 2: Neuroscience: Implications for education and lifelong learning. https://royalsociety.org/topics-policy/projects/brain-waves/education-lifelong-learning/

“Educational neuroscience is an interdisciplinary research field that seeks to translate research findings on neural mechanisms of learning to educational practice and policy. There are equivalent fields that seek to translate neuroscience findings to law (e.g. Royal Society, 2011a), economics (e.g. Glimcher & Fehr, 2013) and social policy (e.g. Royal Society, 2011b), drawing on research in behavioural regulation, decision-making, reward, empathy and moral reasoning. The field is also a basic science that studies how education changes the brain, and what the mechanisms are that lead to behavioural change (or the absences thereof) through education. The relevance of neurobiology to education was recognised throughout the 20th century (e.g. Thorndike, 1926), but it was not until the 1990s and the “Decade of the Brain” (Jones & Mendell, 1999) that technological advances in in vivo imaging of brain function led to the theoretical advances that made educational neuroscience viable as a field (Varma, McCandliss, & Schwartz, 2008).

Despite strong critics (Bishop, 2014; Bowers,2016a; Bruer, 1997) and vigorous ongoing debate about the merits of bringing knowledge from neuro-scientific research to bear on educational problems(Gabrieli, 2016; Howard-Jones et al., 2016), the potential connections between neuroscience and education are being actively explored across the globe. Different labels have been used to describe such efforts, such as Neuroeducation, Educational Neuroscience and Mind, Brain and Education. The growth of the field has led to the establishment of new societies and groups: the International Mind, Brain and Education Society (IMBES; www.imbes.org) was founded in 2004; in 2009, the European Association for Research on Learning and Instruction (EARLI) founded a Special Interest Group called ‘Neuroscience and Education’ which has been holding biannual meetings since 2010. New journals have been established, such as ‘Trends in Neuro-science and Education’, ‘Mind, Brain and Education and ‘Educational Neuroscience’, which attract theoretical and empirical work that explores the inter-sections of neuroscience, psychology and education.” (p. 477)

Thomas, M. S. C., Ansari, D., & Knowland, V. C. P. (2019). Annual research review: Educational neuroscience: Progress and prospects. Journal of Child Psychology and Psychiatry, 60, 477–492. doi:10.1111/jcpp.12973

“It is important to stress from the outset that the “neuroscience” in EN refers almost exclusively to cognitive neuroscience. In other words, it is concerned with making links between the neural substrates of mental processes and behaviors, especially those related to learning. Observed correlations between brain imaging data and behavioral change only reflect a small part of this enterprise, with many methodologies shedding light on the mechanisms by which brain function—and in the current context, cognition—is realized. At its core, then, is the established brain-mind-behavior model of explanation that frames cognitive neuroscience (Morton & Frith, 1995), where the behavior is explicitly learning in the context of (formal) education. Therefore, although it may be concerned with biological processes and classroom behavior, it also has psychology, quite literally, at the center of its theorizing (Bruer, 1997). It is for this reason we welcome this exchange in the pages of Psychological Review.

EN does not favor solely neural levels of explanation, and certainly does not suggest that educational efficacy should be evaluated solely on the basis of neural function. Rather, EN claims that studies of brain function can contribute, alongside behavioral data, to an understanding of underlying learning processes, and that understanding underlying learning processes is relevant to education and can lead to improved teaching and learning. As far as we are aware, there are no established EN research groups who claim that neuroscience, in isolation from psychology or other disciplines, holds any value whatsoever for education. Instead, the exploitation of data from neuroscience is part of a wider perspective on the sphere of causal influences operating on educational outcomes that, for example, now includes a focus on factors such as sleep, diet, stress, and exercise.”(p. 620-621)

Howard-Jones, P., Varma, S., Ansari, D., Butterworth, B., DeSmedt, B., Goswami, U., ... & Thomas, M.S.C. (2016). The principles and practices of educational neuroscience: Commentary on Bowers. Psychological Review, 123, 620–627.

What might such a link achieve?

“The overall goal of brain-based education is to attempt to bring insights from brain research into the arena of education to enhance teaching and learning. The area of science often referred to as brain research typically includes neuroscience studies that probe the patterns of cellular development in various brain areas; and brain imaging techniques, with the latter including functional MRI (fMRI) scans and positron-emission tomography (PET) scans that allow scientists to examine patterns of activity in the awake, thinking, human brain. These brain imaging techniques allow scientists to examine activity within various areas of the brain as a person engages in mental actions such as attending, learning, and remembering.

Proponents of brain-based education espouse a diverse group of educational practices and approaches, and they generally attempt to ground claims about effective practice in recently discovered facts about the human brain. They argue that there has been an unprecedented explosion of new findings related to the development and organization of the human brain and that the current state of this work can inform educational practice in meaningful ways… . Other brain-based education literature that makes closer ties with brain research focuses on brain imaging of particular learning disabilities.”

McCandliss, B. (2021). Brain-based education: Summary principles of brain-based research, critiques of brain-based education. https://education.stateuniversity.com/pages/1799/Brain-Based-Education.html

“The reader’s brain contains a complicated set of mechanisms admirably attuned to reading. For a great many centuries, this talent remained a mystery. Today, the brain’s black box is cracked open and a true science of reading is coming into being. Advances in psychology and neuroscience over the last twenty years have begun to unravel the principles underlying the brain’s reading circuits. Modern brain imaging methods now reveal, in just a matter of minutes, the brain areas that activate when we decipher written words. Scientists can track a printed word as it progresses from the retina through a chain of processing stages, each of which is marked by an elementary question: Are these letters? What do they look like? Are they a word? What does it sound like? How is it pronounced? What does it mean?

On this empirical ground, a theory of reading is materializing. It postulates that the brain circuitry inherited from our primate evolution can be co-opted to the task of recognizing printed words. According to this approach, our neuronal networks are literally “recycled” for reading. The insight into how literacy changes the brain is profoundly transforming our vision of education and learning disabilities. New remediation programs are being conceived that should, in time, cope with the debilitating incapacity to decipher words known as dyslexia.”

Dehaene, S. (2009). Reading in the brain: The new science of how we read. New York: Penguin.

But some in education are sceptical:

“The core claim of educational neuroscience is that neuroscience can improve teaching in the classroom. Many strong claims are made about the successes and the promise of this new discipline. By contrast, I show that there are no current examples of neuroscience motivating new and effective teaching methods, and argue that neuroscience is unlikely to improve teaching in the future. The reasons are twofold. First, in practice, it is easier to characterize the cognitive capacities of children on the basis of behavioral measures than on the basis of brain measures. As a consequence, neuroscience rarely offers insights into instruction above and beyond psychology. Second, in principle, the theoretical motivations underpinning educational neuroscience are misguided, and this makes it difficult to design or assess new teaching methods on the basis of neuroscience. Regarding the design of instruction, it is widely assumed that remedial instruction should target the underlying deficits associated with learning disorders, and neuroscience is used to characterize the deficit. However, the most effective forms of instruction may often rely on developing compensatory (nonimpaired) skills. Neuroscience cannot determine whether instruction should target impaired or nonimpaired skills. More importantly, regarding the assessment of instruction, the only relevant issue is whether the child learns, as reflected in behavior. Evidence that the brain changed in response to instruction is irrelevant. At the same time, an important goal for neuroscience is to characterize how the brain changes in response to learning, and this includes learning in the classroom. Neuroscientists cannot help educators, but educators can help neuroscientists.” (p. 600)

Bowers, J. S. (2016). The practical and principled problems with educational neuroscience. Psychological Review, 123, 600–612. http://dx.doi.org/10.1037/rev0000025

“There are educational resources that tout the importance of the brain in learning and education. Carefully reviewing those sources shows that few of them draw from strong research evidence. What is more, they recommend a lot of poppycock methods, practices, techniques, and such. There can be little doubt that individual’s brains are involved in learning; the very concept of plasticity is a description of learning! But making the leap to popular practices—particularly practices for which there is little or no evidence that employing those practices improves learners’ outcomes—is a leap too far.

Is “brain-based learning” bunkum? No. Of course, not. Everyone uses her brain in learning! Is what lots of people contend is the evidence for brain-based education and recommended practices bogus? Yes.

Let’s please use sensible standards of evidence and logic before adopting teaching practices that may well waste the precious time of kids with disabilities. Learners with disabilities need the very best, the most efficient and effective instruction that we can provide. Few, if any, will benefit when we adopt popular theories that are not founded on solid evidence.”

Lloyd, J.W. (2021). Brain-based education: Is there any other kind? https://www.spedtalk.com/p/editorial-brain-based-education

“At present, though, genetic, structural and functional findings remain largely correlational and unconnected with one another. Results are provocative, but much work still is needed to move from a list of “neurophenotypes” towards a causal theory of gene-brain behavior relations in reading acquisition and RD. … Strong claims that a given program is brain-based are premature at best” (p.22).

Pugh, K., & Hagan, E.C. (2010). New directions in the cognitive neuroscience of reading development and reading disability. Perspectives on Language and Literacy, 36(1), 22.

“The idea that neuroscience research might provide guidance for teachers sounds promising. However, as with any new and aspiring research field, educational neuroscience has suffered to some extent from over-optimism and wishful thinking. A huge demand for improving educational practice has been a fertile ground for misconceptions around the question of how neuroscience can be applied to education. Speculative educational applications have emerged in the name of neuroscience (p.136)

Weigmann, K. (2013). Educating the brain. EMBO Reports, 14(2), 136-9. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3566840/

“Background: Our ability to look at structure and function of a living brain has increased exponentially since the early 1970s. Many studies of developmental disorders now routinely include a brain imaging or electrophysiological component. Amid current enthusiasm for applications of neuroscience to educational interventions, we need to pause to consider what neuroimaging data can tell us. Images of brain activity are seductive, and have been used to give credibility to commercial interventions, yet we have only a limited idea of what the brain bases of language disorders are, let alone how to alter them. Scope and findings: A review of six studies of neuroimaging correlates of language intervention found recurring methodological problems: lack of an adequate control group, inadequate power, incomplete reporting of data, no correction for multiple comparisons, data dredging and failure to analyse treatment effects appropriately. In addition, there is a tendency to regard neuroimaging data as more meaningful than behavioural data, even though it is behaviour that interventions aim to alter. Conclusion: In our current state of knowledge, it would be better to spend research funds doing well designed trials of behavioural treatment to establish which methods are effective, rather than rushing headlong into functional imaging studies of unproven treatments” (p.247).

“Our first priority should be to first develop interventions for children with language impairments and other neurodevelopmental disorders, and to produce good evidence of their efficacy using randomized controlled trials. Second, we also need to do far more methodological work to ensure our neuroimaging tools are as reliable, sensitive and standardized as our behavioural measures (Dichter et al., 2012). Third, we will need to develop multicentre collaborations to do studies with adequate statistical power to detect treatment effects. Only then will we be in a strong position to combine neuroimaging with intervention to answer questions about underlying mechanisms of effective intervention” (p.257).

Bishop, D. V. M. (2012). Neuroscientific studies of intervention for language impairment in children: interpretive and methodological problems. Research Review: Emanuel Miller Memorial Lecture 2012. Journal of Child Psychology and Psychiatry, 54(3), 247–259.

“The first point to note here is that the term ‘brain-training’ is somewhat of a tautology, since all learning happens in the brain. As one of our colleagues is known to say: “it certainly doesn’t happen in your big toe”. Any intervention that is given to any child, will, in some way, “train their brain”. So the question here is not should we train children’s brains, but how should we train their brains? … neuroplasticity tells us that the brain can adapt, but it does not tell us how the brain should be stimulated (or trained). Thus, neuroplasticity per se also does not inform us about how to treat learning difficulties.” (p.1)

Castles, A., & McArthur, G. (2013). ‘Brain-training’ … or learning as we like to call it. Learning Difficulties Australia Bulletin, 45(1), 1-2.

“Certainly our understanding of how neurons work, the role of neurotransmitters, and data showing correlations between brain activity and academic tasks has provided distinct clues into how a child learns. The problem, then, is not with the neuroscience data themselves, but how authors of these purported brain-based approaches appear to have erroneously filled in the missing research gaps. Thus, the problem is not with what neuroscientists and educators know, but with what they think they know. This ‘filling-in-the-gaps’ results from a variety of factors including misunderstanding of the research, misinterpretation or over interpretation of the data, and a belief in claims that are unsubstantiated or go beyond what the evidence supports. … Thus, given the data from neuroscience combined with evidence-based practices used in special education, special educators can be assured that they are, indeed, using brain-based educational instruction. Mastery-based programs that focus on fluency and repetition are most likely to increase both better traditional learning outcomes and produce neural circuits critical for both educational activities and transfer to daily living skills” (p. 46).

For example, the research described above on the formation of memory through long-term potentiation strongly suggests that neural connections are strengthened through repetition or practice (Freeberg, 2006; Garrett, 2008; Hardiman, 2003). Note that the importance of practice and rehearsal has been known for more than a century, long before the process of long-term potentiation was identified (Ebbinghaus, 1913; Hebb, 1949; Thorndike, 1913).” p.50).

Alferink, L. A., & Farmer-Dougan, V. (2010). Brain-(not) based education: Dangers of misunderstanding and misapplication of neuroscience research. Exceptionality, 18, 42-52.

“Many brain studies on reading and word comprehension are based on data from imaging techniques that reveal the distribution of activity in the brain during tasks such as reading single words and sentences and solving simple assessments problems (for instance by comparing watching an activity in a photo with reading about a similar activity - e.g. González, et al. 2006, Zwaan et al., 2002 but see Barsalou, 2016). However, such studies investigate the neural activity as an expression of what happens at the brain level when subjects solve tasks. The explanatory power of such studies may be challenged both methodologically and theoretically (e.g. Schilhab, 2017a), not least because current imaging techniques are too crude to identify differences between individual neurons or individual congregations of neurons (e.g. Beilock, 2010). The delicacy and complexity of what happens at the neural level become invisible, heightening the risk of producing flawed inferences (Alexander et al., 2015). Optimists might respond that such objections will become obsolete as the methods for capturing brain activity increase in subtlety. Moreover, cross-referencing different data sources, such as imaging and EEG, could compensate for the current lack of sensitive equipment. The theoretical objections, however, are more serious and less easy to dismiss.” (p.5)

Trasmundi, S.B., Kokkola, L., Schilhab, T., & Mangen, A. (2021). A distributed perspective on reading: implications for education. Language Sciences, in press. https://doi.org/10.1016/j.langsci.2021.101367

Whilst recognising current weaknesses in the neuroscience contributions to date, are there also grounds for optimism?

“Of course, educational neuroscience is a fledgling field, and there are legitimate criticisms that can be made of it. Here are some of them, drawn from a recent review (Thomas et al., 2019). First, educational neuroscience must amount to more than relabeling effects that are already well known from behavioral psychology with the names of brain structures (such as “executive function” with “prefrontal cortex” or “episodic memory” with “hippocampus”). It must progress psychological theory, and it must point to ways to improve brain health. Second, as Bishop (2014) argues, neuroscience methods are still limited in their sensitivity and specificity as screening or diagnostic tools for deficits. They can only complement more traditional behavioral and social markers of risk. However, some neuroscience measures may be available earlier, such as infant electroencephalographic measures of auditory processing to predict later dyslexia risk (Guttorm, Leppanen, Hamalainen, Eklund, & Lyytinen, 2009) or available-at-birth DNA measures to predict possible educational outcomes (Plomin, 2018). Early availability increases the opportunity for intervention or more targeted monitoring of traditional risk markers. A third legitimate criticism is that while educational neuroscience bears on learning, learning is only one aspect of education that influences outcomes; others include institutional, professional, curricular, political, economic, and societal aspects (Bronfenbrenner, 1992). Fourth, educational neuroscience needs to improve the quality of the dialogue between teachers, psychologists, and educators to ensure that the discussion is genuinely bidirectional, for example, through codesigning studies with teachers to improve the relevance of research and increase the chance of changing practices in the classroom. Finally, educational neuroscience’s progress has been gradual. Researchers (e.g., Howard-Jones et al., 2016; Thomas et al., 2019) have been clear on the complexity of the challenge of linking the classroom phenomenon of learning with learning in the brain, which is the interplay of perhaps eight different neural systems. Much of the groundwork in educational neuroscience will consist of understanding why the educational methods that work do indeed work (Thomas, 2013) in order to ultimately improve them? (p. 338)

Thomas, M.S.C. (2019). Response to Dougherty and Robey (2018) on neuroscience and education: Enough bridge metaphors—interdisciplinary research offers the best hope for progress. Current Directions in Psychological Science, 28(4), 337–340.

What has neuroscience contributed to our understanding of the brain processes involved in skilled and unskilled reading?

“As we learn to read, a brain region known as the 'visual word form area' (VWFA) becomes sensitive to script (letters or characters). However, some have claimed that the development of this area takes up (and thus detrimentally affects) space that is otherwise available for processing culturally relevant objects such as faces, houses or tools. … When we learn to read, we exploit the brain's capacity to form category-selective patches in visual brain areas. These arise in the same cortical territory as specialisations for other categories that are important to people, such as faces and houses. A long-standing question has been whether learning to read is detrimental to those other categories, given that there is limited space in the brain," explains Alexis Hervais-Adelman.

Reading-induced recycling did not detrimentally affect brain areas for faces, houses, or tools -- neither in location nor size. Strikingly, the brain activation for letters and faces was more similar in readers than in non-readers, particularly in the left hemisphere (the left ventral temporal lobe).

"Far from cannibalising the territory of its neighbours, the visual word form area (VWFA) is rather overlaid upon these, remaining responsive to other visual categories," explains Falk Huettig. "Thus learning to read is good for you," he concludes. "It sharpens visual brain responses beyond reading and has a general positive impact on your visual system."

Max Planck Institute for Psycholinguistics. (2019). Learning to read boosts the visual brain. ScienceDaily, 18 September 2019. www.sciencedaily.com/releases/2019/09/190918140743.htm

“Studies employing sophisticated brain imaging tools (e.g., functional magnetic resonance imaging, positron emission tomography, proton echo-planar spectroscopic imaging) have added to the knowledge about what actually occurs at the cellular level during successful intervention (Barquero, Davis, Cutting, 2014; Richards et al., 1999, 2000; Simos et al., 2007; Waldie, Haigh, Badzakova-Trajkov, & Kirk, 2013). It has been noted that struggling readers tend to have a significant amount of brain activity in Broca's area (an area important for speech) and also within the brain's right hemisphere (Waldie, Haigh, Badzakova-Trajkov, & Kirk, 2013). This is indicative of using less appropriate brain structures for the task – structures better suited to visualisation tasks. The consequence (Richards et al., 1999) is that the poorer readers may expend four to five times as much energy to complete a reading task when compared to good readers.

Facile readers display vigorous activity in both the left temporo-parietal and left temporo-occipital areas of the brain (Fletcher et al., 2000). This area enables the association of sounds to words and word parts – the phonological centre. The conversion of print to sound involves the angular gyrus (visual association) linking with the superior temporal gyrus (area for language). Pugh et al. (2002) asserted that the temporo-parietal region is initially crucial in integrating the phonological and orthographic features of text; whereas, the occipito-temporal system becomes important in enabling the effortless fluent word recognition in skilled readers. Subsequent brain research supports this view (Glezera et al., 2016). Some brain function differences are also evident in orally presented phonological tasks, prior to any contact with print, and eventually imaging (should it become simpler, quicker, and cheaper) may be employed as a means of predicting potential reading problems prior to instruction.

Importantly, when the struggling students were taught phonological processing skills (for example, over a 15 two-hour sessions), the brain energy expenditure levels and the locations of relevant brain activities came to resemble those of good readers (Richards et al., 2000). Lyon and Fletcher (2001) reported similar neuro-imaging changes when a 10-year-old student with severe reading disabilities was provided with 60 hours of intensive phonics instruction that also elevated his word-reading ability into the average range.”

Hempenstall, K. (2017). Is there an educational role for phonological processes other than phonemic awareness? https://www.nifdi.org/resources/hempenstall-blog/kerry-s-complete-list-of-blogs

Where is the reading activity occurring in the brain?

Horowitz-Kraus, T., & Hutton, J.S. (2015). From emergent literacy to reading: How learning to read changes a child’s brain. Acta Pædiatrica, 104, 648–656.

p. 274

Weiss, L. G., Saklofske, D. H., Holdnack, J. A., & Prifitera, A. (2015). WISC-V assessment and interpretation: Scientist-practitioner perspectives. San Diego, CA: Academic Press.

Apart from examining processes in the brain, there is also interest in differences in the physiology/structure of the brain. For example, might grey or white matter volume in the brain be related to reading?

“Studies have converged in their findings of relatively less gray matter volume (GMV) in developmental dyslexia in bilateral temporoparietal and left occipitotemporal cortical regions. However, the interpretation of these results has been difficult. The reported neuroanatomical differences in dyslexia may be causal to the reading problems, following from, for example, neural migration errors that occurred during early human development and before learning to read. Alternatively, less GMV may represent the consequence of an impoverished reading experience, akin to the experience-dependent GMV differences attributed to illiterate compared with literate adults. Most likely, a combination of these factors is driving these observations. Here we attempt to disambiguate these influences by using a reading level-matched design, where dyslexic children were contrasted not only with age-matched controls, but also with younger controls who read at the same level as the dyslexics. Consistent with previous reports, dyslexics showed less GMV in multiple left and right hemisphere regions, including left superior temporal sulcus when compared with age-matched controls. However, not all of these differences emerged when dyslexics were compared with controls matched on reading abilities, with only right precentral gyrus GMV surviving this second analysis. When similar analyses were performed for white matter volume, no regions emerged from both comparisons. These results indicate that the GMV differences in dyslexia reported here and in prior studies are in large part the outcome of experience (e.g., disordered reading experience) compared with controls, with only a fraction of the differences being driven by dyslexia per se.

Krafnik, A. J., Flowers, D. L., Luetje, M. M., Napoliello, E. M., & Eden, G. F. (2014). An investigation into the origin of anatomical differences in dyslexia. The Journal of Neuroscience, 34(3), 901-908.

“Neuroimaging studies of dyslexia have identified differences in structure and function that are associated with reading difficulty from childhood through adulthood. Although dyslexia is often diagnosed once reading difficulties become apparent around 7 or 8 years old, there is strong evidence that dyslexia is the consequence of differences in prereading abilities that are the building blocks of learning to read and in the brain regions that support those abilities. … Fewer studies have examined the effects of remediation on brain structure, but there is evidence of increases in gray matter volume or thickness and strengthened white matter connectivity as a result of remediation (Keller & Just, 2009; Krafnick et al., 2011; Romeo et al., 2017).” (p.798, 804)

D'Mello, A., & Gabrieli, J.D.E. (2018). Cognitive neuroscience of dyslexia. Language Speech and Hearing Services in Schools 49(4), 798-809. 10.1044/2018

“Neural specialization for reading is experientially driven and occurs through utilizing and repurposing distributed brain structures that support vision, audition, and language (Dehaene, 2009). The efficient integration across these spatially disparate brain regions is made possible by long-range white matter connections that form across development (Wandell, Rauschecker, & Yeatman, 2012). Three white matter tracts in particular have a documented association with reading and reading-related skills in adults and children as early as preschool.”

Ozernov-Palchik, O., Norton, E.S., Wang, Y., Beach, S.D., Zuk, J., Wolf, M., Gabrieli, J.D.E., & Gaab, N. (2018). The relationship between socioeconomic status and white matter microstructure in pre-reading children: A longitudinal investigation. Human Brain Mapping, 1–14. https://www.researchgate.net/publication/327944343_The_relationship_between_socioeconomic_status_and_white_matter_microstructure_in_pre-reading_children_A_longitudinal_investigation

The examples below show how neuroscience findings can be supportive of, rather than supplanting, previous basic educational research:

“Likewise, the data suggest that formation of memories through neural consolidation works best if students have a number of short learning sessions separated over time, not single long sessions. Again, the advantages of spaced or distributed practice over massed practice have also been known for many decades (see Olson & Hergenhahn, 2009; Ebbinghaus, 1913). Neuroscience, in this case, reinforced these best practices by providing the data at the neural level that supported these methods” (p.50).

Alferink, L.A., & Farmer-Dougan, V. (2010): Brain-(not) based education: Dangers of misunderstanding and misapplication of neuroscience research. Exceptionality, 18(1), 42-52.

“It should be clear that I am advocating here a strong ‘phonics’ approach to teaching, and against a whole-word or whole-language approach. Several converging elements support this conclusion (for a longer development, see Dehaene, 2009). First, analysis of how reading operates at the brain level provides no support for the notion that words are recognized globally by their overall shape or contour. Rather, letters and groups of letters such as bigrams and morphemes are the units of recognition. Second, experiments with adults taught to read the same novel script with a whole-word versus grapheme-phoneme approach show dramatic differences (Yoncheva, Blau, et al., 2010): only the grapheme-phoneme group generalizes to novel word and trains the left-hemispheric VWFA. Adults whose attention was drawn to the global shape of words, by whole-word training, showed brain changes in the homolog region of the right hemisphere, clearly not the normal circuit for expert reading.” (p.28)

Dehaene, S (2011). The massive impact of literacy on the brain and its consequences for education. Human neuroplasticity and education. Pontifical Academy of Sciences, 117, 19-32.

“It simply is not true that there are hundreds of ways to learn to read […] when it comes to reading we all have roughly the same brain that imposes the same constraints and the same learning sequence” (p. 218).

“We now know that the whole-language approach is inefficient; all children regardless of their socioeconomic backgrounds benefit from explicit and early teaching of the correspondences between letters and speech sounds. This is a well-established fact, corroborated by a great many classroom experiments. Furthermore, it is coherent with our present understanding of how the reader’s brain works” (p. 326).

“Every child is unique…but when it comes to reading, all have roughly the same brain that imposes the same constraints and the same learning sequence. Thus we cannot avoid a careful examination of the conclusions – not prescriptions – that cognitive neuroscience can bring to the field of education” (p. 218).

Dehaene, S. (2009). Reading in the brain: The science and evolution of a human invention. New York: Viking/Penguin.

“Neurocognitive processes: Interleaving topics can increase the efficiency with which learned material is remembered and also the effectiveness of some other learning processes. Interleaving may operate by reducing the suppression of neural activity in memory regions that occurs when similar stimuli are repeatedly presented.” (p. 31)

Howard-Jones, P. (2014). Neuroscience and education: A review of educational interventions and approaches informed by neuroscience. London: Education Endowment Foundation (p. 1-62). https://educationendowmentfoundation.org.uk/public/files/Publications/EEF_Lit_Review_NeuroscienceAndEducation.pdf

Sometimes the neuroscience research can explain phenomena previously noted, but sometimes unexplained or even misunderstood, in conventional educational research. For example:

“Recently, our growing understanding of how the brain is recycled for reading has led to a clarification of another mysterious phenomenon that occurs during childhood: mirror reading and mirror writing. Many young readers confuse mirror letters such as p and q or b and d. Furthermore, they occasionally write in mirror form, from right to left, quite competently and without seemingly noticing their error. This peculiar behavior can be explained by considering that the function of the ventral visual cortex, prior to reading, is the invariant recognition of objects, faces and scenes. In the natural world, very few objects have a distinct identity for left and right views. In most cases, the left and right views of a natural object are mirror images of each other, and it is useful to generalize across them and treat them as the same object. Single-cell recordings in monkeys show that this principle is deeply embedded in the visual system: many neurons in the occipito- temporal visual cortex fire identically to the left and right views of the same object or face (Freiwald & Tsao, 2010; Logothetis, Pauls, & Poggio, 1995; Rollenhagen & Olson, 2000).

Using neuroimaging, my colleagues and I have shown that, in the human brain, it is precisely the VWFA which is the dominant site for this mirror-image invariance (Dehaene, Nakamura, et al., 2010; Pegado, Nakamura, Cohen, & Dehaene, 2011). No wonder, then, that young children confuse b and d: they are trying to learn to read with precisely the brain area that confuses left and right of images! Mirror confusion is a normal property of the visual system, which is seen in all children and illiterate subjects, and which disappears for letters and geometric symbols when literacy sets in (Cornell, 1985; Kolinsky, et al., 2010). Only its prolongation in late childhood is a sign of dyslexia (Lachmann & van Leeuwen, 2007; Schneps, Rose, & Fischer, 2007). Teachers should therefore be aware of the specific difficulty posed by mirror letters, and should take the time to explain why b and d are distinct letters corresponding to distinct phonemes (it is particularly unfortunate that these phonemes are quite similar and easily confused). Interestingly, teaching the gestures of writing can improve reading, perhaps because it helps store view-specific memories of the letters and their corresponding phonemes (Fredembach, de Boisferon, & Gentaz, 2009; Gentaz, Colé, & Bara, 2003).” (p.27-28)

Dehaene, S. (2011). The massive impact of literacy on the brain and its consequences for education. Human neuroplasticity and education. Pontifical Academy of Sciences, 117, 19-32.

“We “hear” written words in our head. Sound may have been the original vehicle for language, but writing allows us to create and understand words without it. Yet new research shows that sound remains a critical element of reading. When people listen to speech, neural activity is correlated with each word's “sound envelope”—the fluctuation of the audio signal over time corresponds to the fluctuation of neural activity over time. In the new study, Lorenzo Magrassi, a neurosurgeon at the University of Pavia in Italy, and his colleagues made electrocorticographic (ECoG) recordings from 16 individuals. The researchers measured neural activity directly from the surface of the language-generating structure known as Broca's area as subjects read text silently or aloud. (This measurement was made possible by the fact that participants were undergoing brain surgery while awake.). Their neural activity was correlated with the sound envelope of the text they read, which was generated well before they spoke and even when they were not planning to speak, according to the report published in February in the Proceedings of the National Academy of Sciences USA. In other words, Broca's area responded to silent reading much in the same way auditory neurons respond to text spoken aloud—as if Broca's area was generating the sound of the words so the readers heard them internally. The finding speaks to a debate about whether words are encoded in the brain by a neural pattern symbolic of their meaning or if they are encoded via simpler attributes, such as how they sound. The results add to mounting evidence that words are fundamentally processed and catalogued by their basic sounds and shapes.

Sutherland, S. (2015). When we read, we recognize words as pictures and hear them spoken aloud. Scientific American: Mind, July 1, 2015. Retrieved from http://www.scientificamerican.com/article/when-we-read-we-recognize-words-as-pictures-and-hear-them-spoken-aloud/

Original study by Glezer, L.S., Kim, J., Rule, J., Jiang, X., & Riesenhuber, M. (2015). Adding words to the brain's visual dictionary: Novel word learning selectively sharpens orthographic representations in the VWFA. Journal of Neuroscience. 35(12), 4965-72.

“Three complementary sources of evidence suggest that words are the units of reading. First, eye movements during fluent reading are made mostly by making saccades from one word to the next. Second, the reading time of a single word is relatively independent of the number of letters. Third, a single letter may be more easily detected in brief presentations when embedded in a word. A possible inference of these findings is that education should be organized to teach children to read entire words instead of focusing in letter-by-letter identification. This procedure, usually termed holistic reading, led to concrete implementations that turned out to be a major pedagogical fiasco. As it turns out, the neuroscience of visual learning could actually have predicted this failure. The development of literacy is a case of pop-out learning, a process by which, after extensive practice, one can identify a specific set of shapes in cluttered fields very rapidly and with a subjective feeling of automaticity and lack of effort. For non-readers, reading is a slow, effortful and serial process that becomes automatic after many hours of training.”

Sigman, M., Peña, M., Goldin, A.P., & Ribeiro, S. (2014). Neuroscience and education: Prime time to build the bridge. Nature Neuroscience, 17(4), 497-502.

“We know that the activity and organization of the brain changes in response to experience. Memories and learning are reflected in the number and strength of connections between nerve cells. We also know that the brain is genetically mosaic, but a new study makes a remarkable connection between experience and the genetic diversity of the brain. It suggests that experience can change the DNA sequence of the genome contained in brain cells. This is a fundamentally new and unexplored way in which experience can alter the brain. It is of great scientific interest because it reveals the brain to be pliable, to its genetic core, in response to the world. … Linking early experience to the genomic variability of nerves suggests that early experience leaves an irreversible genomic imprint in the brain. This is an intriguing new twist on a debate that has been raging for centuries concerning the importance of nature versus nurture in behavior. This study implies that nature and nurture are not as independent as may have been imagined, and that nature is not as immutable as once thought.”

Martone, R. (2018). Early life experience: It’s in your DNA. Scientific American, July 10. https://www.scientificamerican.com/article/early-life-experience-its-in-your-dna/

“Our results show that adults with dyslexia are slightly right lateralized overall for language, a profile that differed significantly from the left-lateralized activation observed in typical readers. Though there was also left hemisphere activation observed during reading tasks in the dyslexic participants, the right hemisphere activity was more diverse and primarily occurring in OT regions during pseudoword reading. Right hemisphere compensation in dyslexia may increase as phonological demands increase

Our findings are consistent with earlier work with dyslexic children, suggesting that the activation in the right hemisphere is likely to be a cause rather than a consequence of reading impairment. Right hemisphere findings should be given more consideration in the literature, particularly as they may have important implications for early intervention, reading remediation and theories of neural plasticity. In 2003 Elise Temple and colleagues showed that auditory processing and oral language training can activate the left posterior reading network in reading disabled children but produces additional compensatory activation in other brain regions [60].

Our findings tentatively support the possibility that right OT compensation might also respond to intensive phonics/phonological processing training. Future designs would need to correlate behavioural measures of reading fluency/accuracy with the right compensatory activity throughout the remediation process to determine how best to accomplish this and whether the right hemisphere participation is helping or hindering the remediation. Such calculations might also address the possibility that the right hemisphere activity is inhibitory rather than compensatory as traditionally assumed.

It is still an open question whether right hemisphere activation acts in a compensatory or inhibitory role during single word reading in impaired readers. Taken together, in addition to an impaired left hemisphere posterior network, right posterior overactivity may be an important biological marker of dyslexia if our results are replicated. Dyslexic adults appear to compensate for their reading impairment by an increased recruitment of these areas to assist with visual coding. The possibility that the right hemisphere neural mechanisms are inhibitory rather than compensatory should be investigated in further studies.” (p.1071)

Waldie, K.E., Haigh, C.E., Badzakova-Trajkov, G., Buckley, J., & Kirk, I.J. (2013). Reading the wrong way with the right hemisphere. Brain Sciences, 3(3), 1060-1075. https://doi.org/10.3390/brainsci3031060

Earlier prediction of reading difficulties?

“But there is evidence that structural differences in the brains of children who will later have trouble learning to read are present before reading onset. (Raschle, Chang & Gaab, 2011; Raschle, Zuk & Gaab, 2012). dyslexia has a neural basis present before reading instruction begins, might you be able to identify children who will very likely have significant trouble with reading before instruction ever begins?

A number of laboratories have been working on this problem, and progress is being made. These researchers are not looking to toss out behavioral measures--they are looking to supplement them. The more successful of these efforts (e.g., Hoeft et al., 2007) show that behavioral measures predict reading problems, neuroscientific measures predict reading problems, and using both types of data provides better prediction than either measure alone. In other words, the neuroscientific data is capturing information not captured by the behavioral measures, and vice versa.”

Willingham, D. (2012). Neuroscience & Education:5 Days, 5 Ways. Day 5: Predicting Trouble. http://www.danielwillingham.com/daniel-willingham-science-and-education-blog/neurosci-educ-5-days-5-ways-day-5-predicting-trouble

“A clinical and educational goal of reading research is to improve the accuracy with which children at risk for dyslexia are identified so that they can receive early, preventive intervention rather than intervention that follows years of reading failure (Strickland, 2002). Although behavioral measures of phonological awareness, RAN, and letter knowledge in kindergartners predict reading ability years later (Catts et al., 2001; Schatschneider et al., 2004), the sensitivity and specificity of these behavioral measures is modest (Pennington and Lefly, 2001). There is some evidence that brain measures substantially enhance the accuracy of predicting reading ability across a school year (Hoeft et al., 2007; Rezaie et al., 2011) or across multiple years (Maurer et al., 2009; Hoeft et al., 2011). The present study indicates that DWI measures of white matter organization reveal a specific structural risk factor for reading difficulty that, in combination with behavioral and other brain measures, may improve the identification of prereaders at risk for dyslexia” (p.13256).

Saygin, Z.M., Norton, E.S., Osher, D.E., Beach, S.D., Cyr, A.B., Ozernov-Palchik, O., Yendiki, A., Fischl, B., Gaab, N., & Gabrieli, J.D.E. (2013). Tracking the roots of reading ability: White matter volume and integrity correlate with phonological awareness in prereading and early-reading kindergarten children. The Journal of Neuroscience 33(33), 13251-13258. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3742917/

“There is a considerable debate about how a deepening understanding of the brain basis of dyslexia may or may not be useful in light of current educational practices and policies (Bowers, 2016; Gabrieli, 2016). Although neuroimaging studies have revealed that dyslexia reflects functional and structural brain differences that diverge from typical brain development starting in infancy, reading instruction is not targeted at particular neural systems. Rather, instruction targets behavioral abilities, such as phonological awareness as a component of single-word decoding. One area in which neuroimaging studies may contribute particular educational value is in the prediction of response to instruction that would promote personalized or individualized instruction (Gabrieli, Ghosh, & Whitfield-Gabrieli, 2015). In one study of children with dyslexia around the age of 14 years, none of 17 conventional tests of reading and reading-related abilities predicted which particular children would or would not show gains in reading over the next 2.5 years (Hoeft et al., 2011). Neuroimaging methods, however, could predict with considerable accuracy which individual child would or would not make gains in reading over that same period (Hoeft et al., 2011). Similarly, brain measures in kindergarteners correlated better with reading level than did behavioral measures of those same children in fifth grade (Maurer et al., 2009). These studies suggest that brain differences among children may make them more or less likely to benefit from particular kinds of instruction.” (p. 805)

D'Mello, A., & Gabrieli, J.D.E. (2018). Cognitive neuroscience of dyslexia. Language Speech and Hearing Services in Schools 49(4), 798-809. 10.1044/2018

“Challenges to identification for both younger and older children may be best met with frameworks that recognize the multifactorial casual basis of reading problems (Pennington et al., 2012). Newer models of identification that combine across multiple indicators of risk derived from current skill, and that augment these indicators with other metrics of potential risk, may yield improved identification and interventions (e.g., Erbeli et al., 2018; Spencer et al., 2011). In particular, future research will need to consider and combine, while considering both additive and interactive effects, a wide array of measures, which may include genetic, neurological, and biopsychosocial indicators (Wagner et al., 2019). Furthermore, more evaluation is needed of some new models of identification that integrate both risk and protective, or resiliency, factors, to see if these models increase the likelihood of correctly identifying those children most in need of additional instructional support (e.g., Catts & Petscher, 2020; Haft et al., 2016). Even if beneficial, it is likely that for early identification to be maximally effective, early risk assessments will need to be combined with progress monitoring of response to instruction (Miciak & Fletcher, 2020).” (p. 12)

Petscher, Y., Cabell, S. Q., Catts, H. W., Compton, D. L., Foorman, B. R., Hart, S. A., Lonigan, C. J., Phillips, B. M., Schatschneider, C., Steacy, L. M., Terry, N. P., & Wagner, R. K. (2020). How the science of reading informs 21st-century education. Reading Research Quarterly, 55 (Suppl 1), S267–S282. https://doi.org/10.1002/rrq.352

“Longitudinal studies tracking brain development with child-friendly neuroimaging techniques during the first years of reading acquisition are critical to characterize variations in the developmental trajectories of brain networks and to relate such variations to children’s reading predisposition and attained reading level. Neuroscientific studies of reading hold the promise of identifying and characterizing early risk factors that cannot be detected by cognitive assessments in pre-reading stages4. To advance the field of dyslexia research and clinical practice, studies recruiting pre-readers or beginning readers and tracking them until the age when dyslexia is diagnosed are especially valuable. Such longitudinal designs enable observation of neuronal alterations at or before reading onset, not affected by the limited reading experience, to reveal early markers of dyslexia. Only then is it possible to disentangle causes from consequences of dyslexia and their neurobiological basis5. Compared with a cross-sectional design, which currently dominates in the field, the longitudinal approach reduces the confounding effect of between-subject variability6, enables assessment of the predictive value of different measures, and reveals how specific neural changes are related to age and changes in reading performance7.” (p. 1)

Chyl, K., Fraga-González, G., Brem, S. et al. (2021). Brain dynamics of (a)typical reading development—a review of longitudinal studies. npj Sci. Learn. 6(4), https://doi.org/10.1038/s41539-020-00081-5

Perhaps further benefits may accrue when interdisciplinary research becomes more common.

“An integrative approach not only allows educational and psychological protocols to be designed with a view to the neurophysiological variables of interest, but also allows neuroscientific experiments to be designed in the light of relevant psychological and educational behavioural parameters. For example, the psychological spacing effect, described above, may not only help to design educational programs to enhance rates of classroom learning but may also help to inform the design of experiments investigating the role of LTP in the brain. Another example is the testing effect, a learning phenomenon derived from educational research, in which memory retention is enhanced by multiple testing sessions during learning (Karpicke & Roediger, 2008; Rawson & Dunlosky, 2012; Roediger & Butler, 2011). The testing effect has a striking parallel in the psychological and neurophysiological phenomenon of reconsolidation, in which associative memory can be enhanced (or degraded) by the unpredictable presentation of a cue or conditioned stimulus without reinforcement, which appears to return the memory trace to a labile state (Lee, 2008; Pedreira, Pe´rez-Cuesta, & Maldonado, 2004). Optimizing the testing effect in the classroom could depend on a better understanding of the neural reconsolidation process occurring as a result of repeated testing; on the other hand, understanding more accurately the conditions and timing that produce the behavioural testing effect may help to design experiments that reveal more detail about reconsolidation in the brain.” (p.151)

Morris, J., & Sah, P. (2016). Neuroscience and education: Mind the gap. Australian Journal of Education, 60(2), 146–156.

“The overall goal of brain-based education is to attempt to bring insights from brain research into the arena of education to enhance teaching and learning. The area of science often referred to as brain research typically includes neuroscience studies that probe the patterns of cellular development in various brain areas; and brain imaging techniques, with the latter including functional MRI (fMRI) scans and positron-emission tomography (PET) scans that allow scientists to examine patterns of activity in the awake, thinking, human brain. These brain imaging techniques allow scientists to examine activity within various areas of the brain as a person engages in mental actions such as attending, learning, and remembering. Proponents of brain-based education espouse a diverse group of educational practices and approaches, and they generally attempt to ground claims about effective practice in recently discovered facts about the human brain. They argue that there has been an unprecedented explosion of new findings related to the development and organization of the human brain and that the current state of this work can inform educational practice in meaningful ways… . Other brain-based education literature that makes closer ties with brain research focuses on brain imaging of particular learning disabilities. Sousa wrote "we are gaining a deeper understanding of learning disabilities, such as autism and dyslexia. Scanning technology is revealing which parts of the brain are involved in these problems, giving hope that new therapies … will stimulate their brains and help them learn" (p. 54). Such direct ties between investigations of brain mechanisms associated with learning problems and intervention attempts provide a promising direction for brain-based educational research. Understanding how brain mechanisms of basic visual and language processes work together in typically and atypically developing readers is of central interest to many brain scientists and educators. Several studies centered on these issues were underway in fMRI laboratories in the early twenty-first century, with many of the studies involving brain scans collected before a particular educational intervention. Such direct interplay between educational intervention and brain-based measurements provides a means of assessing the degree to which a particular educational program impacts brain mechanisms associated with learning within a particular domain, such as reading. … Perhaps by explicitly combining evidence-based investigations of specific educational practices with brain imaging and psychological studies of learning, future research might take a step closer toward the goals of brain-based education and provide empirically validated contributions to enhancing education based on scientific insights into learning.”

McCandliss, B. (2021). Brain-based education: Summary principles of brain-based research, critiques of brain-based education. https://education.stateuniversity.com/pages/1799/Brain-Based-Education.html

"So I remain skeptical about the implications of neuroscience for education currently and into the near future. Maybe I should say the direct implications of neuroscience for education. I do believe that eventually we will be able to bridge neuroscience at its various levels of analysis with education, but I am convinced that all of these bridges will have a least one pier on the island of psychology.”

Bruer, J.T. (2006). Points of view: On the implications of neuroscience research for science teaching and learning: Are there any? CBE Life Science Education, 5(2), 111-7. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1618519/

“Scholarly treatments have been positive about the prospects, but more sober, and most have taken a position that is broadly consistent with ours. They argue that neuroscience has been and will continue to be helpful to education — indeed, recent reviews show beyond doubt that this is true (e.g., Katzir & Paré-Blagoev, 2006 ) — but they argue that data from neuroscience must be funnelled through a behavioral level of analysis (e.g., Bruer, 1997, 1998; Hirsh-Pasek & Bruer, 2007) or that neuroscience should be part of a broader approach to research in education, not the sole saviour (e.g., Ansari & Coch, 2006; Byrnes & Fox, 1998; Fischer et al., 2007; Geake & Cooper, 2003 ) (p. 147).

Willingham, D.T., & Lloyd, J.W. (2007). How educational theories can use neuroscientific data. Mind, Brain, and Education, 1(3), 140-149. http://www.danielwillingham.com/uploads/5/0/0/7/5007325/willingham__lloyd_2007.pdf

“Over the past decade, researchers have identified lacking professional development on dyslexia as stemming from “The Peter Effect” (i.e., “One cannot teach what they do not know”, Applegate and Applegate, 2004, as cited in Binks-Cantrell et al., 2012). Reportedly, the dyslexia myth is prevalent among higher education instructors at similar rates as preservice and in-service educators (Betts et al., 2019). Research on improving school professionals’ dyslexia knowledge has identified this pervasive misconception among pre-service and school professionals (Washburn et al., 2011, Washburn et al., 2014, Washburn et al., 2017; White et al., 2020). White et al. (2020) found no significant differences in dyslexia knowledge within education majors (e.g., elementary v. special education v. school psychology), or between education and non-education majors. This research underscores the expressed need for explicit, intensive professional development to address the persistent misconception of dyslexia among teacher candidates and school professionals. The question remains in how to change the persistent misconception of dyslexia, as the effect of knowledge transmission approaches remains an open question since “debunking” messages are not always effective in countering misinformation (Chan et al., 2017).

Researchers have identified this gap in school professional development, calling for a neuroscience primer that addresses the neurobiology of dyslexia (Anderson et al., 2020; Kearns et al., 2019). Neuroscience in education research has the potential to address this need. For example, the neuroscience concept of synaptic plasticity establishes why individuals with dyslexia require intensive practice to learn to read since axonal pathways differ from typically developing readers and individuals with dyslexia require more synapses trained to successfully associate phonemes with graphemes, to recognize words, and to associate meanings with words (Gabrieli, 2009; Klingberg et al., 2000).

While the neuroscience of reading has been identified as candidate knowledge for filling the conceptual gap in teacher-education related to dyslexia (e.g., Kearns et al., 2019; Seidenberg, 2013), little research exists on teacher education programs or standalone professional development models that provide such training. A few research studies have been aimed at improving school professionals’ knowledge of dyslexia through educational neuroscience training programs or interventions (Anderson et al., 2020). A recent study using conceptual change theory found that preservice teachers’ dyslexia knowledge could improve through reading refutation text as compared to control text on dyslexia (Peltier et al., 2020); however, it is unknown whether the researchers grounded their text explanations in the neuroscience of dyslexia.” (p. 317)

Alida, A. (2021). Advancing school professionals’ dyslexia knowledge through neuroscience: Bridging the science-education gap through developmental psychology. Frontiers in Education, 5, 316- 320. https://www.frontiersin.org/article/10.3389/feduc.2020.615791

A final topic- Neuromyths: A little knowledge … !

“Neuromyth is not a new concept. The word was first coined during the 1980s when the neurosurgeon Alan Crockard used it to describe a misleading concept about the brain function in the discipline of medicine (Howard-Jones, 2014; Fuentes and Risso, 2015). From an educational approach, a neuromyth was described as “a misconception generated by a misunderstanding, a misreading, or a misquoting of facts scientifically established (by brain research) to make a case for the use of brain research in education and other contexts” (OECD, 2002). Since that definition appeared, previous studies have emphasized the widespread presence of the neuromyths and their persistence, especially among individuals in contact with education (Howard-Jones et al., 2009; Dekker et al., 2012; Howard-Jones, 2014; Ferrero et al., 2016; Düvel et al., 2017; among others).

In 2002, the UK's OECD launched the Brain and Learning project (Howard-Jones, 2014), and Herculano-Houzel (2002) published the first survey about knowledge of the brain. She included 95 multiple-choice assertions, 83 related to the information that the general public has about brain research (Herculano-Houzel, 2002) and several neuromyths.

Five years later, the OECD wrote about the proliferation of the neuromyths around (a) critical periods, (b) the age of three as the time when everything important is decided, (c) multilingualism, (d) left vs. right brain people, and (e) the 10% of the use of our brain, as the most widely spread neuromyths. Most neuromyths are built in the base of a kernel of truth (Grospietsch and Mayer, 2018, 2019), i.e., valid scientific findings support them (Dekker et al., 2012), but they were adulterated because of misinterpretations, oversimplifications (Howard-Jones, 2014), and even due to a flawed interpretation of scientific results (Pasquinelli, 2012; Howard-Jones, 2014).

Research has provided evidence against neuromyths. As an example, neuroimaging research has demonstrated that both hemispheres are responsible for most of the procedures and are in constant communication, even though they differ in their functions (Ansari, 2008), which runs counter to myths such as left vs. right brain people, or multiple intelligences (Geake, 2008).

The myth about only 10% of brain use seems to be the most enduring neuromyth. It has survived more than a century. In 1907, Williams James wrote about the idea that humans used mental and physical resources below their means (James, 1907). Later, physicist Albert Einstein in a radio interview in 1920 (Pallarés-Domínguez, 2016), encouraged people to think more (Geake, 2008; Dündar and Gündüz, 2016; Papadatou-Pastou et al., 2017). He invited people to enhance their possibilities, using more than 10% of their brain, but he did not intend to spread such a colossal misunderstanding. However, as reported in the previous literature, not only can excellent scientific data be behind a neuromyth but also a neuroanatomical fact. The glia-neuron rate (or white matter-gray matter) which is one for every ten (Pasquinelli, 2012) may be responsible for the myth that claims that humans only use the 10% of their brain (because of the aforementioned rates). Scientific research shows how improbable this assertion may be, just taking into consideration that no one single brain area is 100% “out of work,” even when sleeping (Centre for Educational Research and Innovation and OECD, 2007).

Closely related to education, we can find the neuromyth of the visual, auditory, and kinaesthetic (VAK) learning styles. Under this approach, every child has a dominant learning style, which should be identified to teach each of them more precisely and create lesson plans according to their preferences (Geake, 2008; Macdonald et al., 2017). In this case, the kernel of truth is found in an oversimplification (Ansari, 2008) of fundamental research that has identified different parts of the brain that process visual, auditory, or kinaesthetic information (Dekker et al., 2012), i.e., different regions of the cortex have specific roles in sensory processing (Howard-Jones, 2014). Lack of evidence in VAK/learning styles has been successfully established (Pashler et al., 2008; Riener and Willingham, 2010; Willingham et al., 2015). Nevertheless, it is one of the most deeply rooted and widely believed neuromyths (Rodrigues Rato et al., 2013; Deligiannidi and Howard-Jones, 2015; Papadatou-Pastou et al., 2017, 2018; Varas-Genestier and Ferreira, 2017; Zhang et al., 2019). This misconception is widely considered a fact, even more than that of the hemispheric preference (Tardif et al., 2015). Teachers report having been taught about VAK/learning styles during training courses organized by their schools or the educational authorities of their governments (Lethaby and Harries, 2016; Kim and Sankey, 2017; McMahon et al., 2019). Moreover, some teachers insist they intend to continue working under the VAK perspective in their classrooms, even knowing that it is a neuromyth (Newton and Miah, 2017; Tan and Amiel, 2019).” (p. 2)

The distance between neuroscience and education is still too great. We have found reasons for the lack of knowledge among educators about science and the brain. Additionally, they have difficulties in accessing to the latest findings due to the absence of scientific literature in their mother tongue or the weakness of science communication. … First, we have to solve the methodological drawbacks in the research on neuromyths. Future research is needed to define rigorous guidelines to identify a new neuromyth or debunk another. Undoubtedly, this guideline has to be built on the basis of academic criteria and science. This work has revealed the urgency of finding new ways to survey teachers about their perceptions, their cognitive bias, and their sincere beliefs. Moreover, access to knowledge could avoid widening the gap between neuroscience and education as a result of cultural conditions (Hermida et al., 2016). (p. 15)

Torrijos-Muelas, M., González-Víllora, S., & Bodoque-Osma, A.R. (2021). The persistence of neuromyths in the educational settings: A systematic review. Frontiers in Psychology, 11, article 591923.

“Alongside this craze for all things brain-based, or ‘neuro’, a smaller movement has arisen, of desperate evidence-based psychologists and educators, seeking to temper enthusiasm with reality and to dispel some of the nonsense spouted by the ‘brainiacs’, also known as ‘neuromyths’. (A less polite term that you might also encounter online is ‘neurobollocks’.) Like zombies, however, neuromyths are extremely hardy and merely providing contrary empirical evidence is rarely sufficient to kill them off. They might pause, briefly, but then they keep on coming. And they breed …

The extent of this problem is revealed in a recent article by Dekker, Lee, Howard- Jones and Jolles, published in Frontiers in Psychology (http://tinyurl.com/8wsjczw) which reports the results of a survey of 242 teachers conducted in the UK and the Netherlands. Over 90% expressed interest in ‘scientific knowledge about the brain’ and 90% were of the view that such knowledge would positively inform their teaching practice. The teachers responded to an online survey that mixed a selection of neuromyths with true statements about the brain. In addition to the collection of background information (about age, sex, level of education etc), they were also asked about their degree of interest in scientific knowledge about the brain and its influence on their teaching, any ‘brain-based’ methods they had encountered in their school, and whether they read popular science magazines or journals, among other questions.

Over 50% of the teachers indicated that they believed in seven of the 15 neuromyths included in the questionnaire. Over 80% expressed belief in the following: “Individuals learn better when they receive information in their preferred learning style (e.g., auditory, visual, kinesthetic)”; “Differences in hemispheric dominance (left brain, right brain) can help explain individual differences amongst learners”; and “Short bouts of co-ordination exercises can improve integration of left and right hemispheric brain function”. Over 80% of the British teachers had encountered Brain Gym (specifically) and (learning styles) generally (98%) in their schools.

So far, so bad; but it gets worse, much worse. When the researchers examined the results in more detail, they found that teachers who actually knew more about the brain tended to believe in more neuromyths. Yes, that’s right; the more they knew about the brain, the more neurobollocks they believed! As the authors put it: “These findings suggest that teachers who are enthusiastic about the possible application of neuroscience findings in the classroom find it difficult to distinguish pseudoscience from scientific facts. Possessing greater general knowledge about the brain does not appear to protect teachers from believing in neuromyths.”

Wheldall, K. (2012). Neuromyths: A little learning is a dangerous thing. Notes from Harefield. http://www.kevinwheldall.com/2012/10/neuromyths-little-learning-is-dangerous_26.html

There has long been concern about a gap between teacher classroom practice in children’s literacy development and the research findings about what works. A parallel concern is now being expressed about the proliferation of neuromyths within education. It appears that too high a proportion of teachers and education faculties subscribe to untenable beliefs and practices based upon these myths:

“Dyslexia’s most persistent misconception may be related to misunderstandings about the brain and learning known as “neuromyths” (Lilienfeld et al., 2010). Over the past decade, research has identified educators’ misconceptions about the brain and learning, focusing on how these myths arise and why they persist (Howard-Jones, 2014). For example, Macdonald et al. (2017) found a clustering of “classic” neuromyths (items related to learning styles, dyslexia, the Mozart effect, the impact of sugar on attention, right-brain/left-brain learners, and using 10% of the brain), such that the dyslexia myth was often endorsed by the same individuals who endorsed other neuromyths. This clustering of misconceptions raises the question of whether addressing these misconceptions through neuroscience may address the dyslexia myth, among other brain-behavior misunderstandings. Seidenberg’s (2013) two-culture hypothesis for the research to practice gap in reading is similar to Howard-Jones’ (2014), who contends the most persistent neuromyths endorsed across PK12 through higher education are due to “cultural distance” between neuroscience and education, tracing persistent myths about the brain and learning as germinating from “seeds of confusion”, “cultural conditions”, and biased distortions of scientific data (pp. 817–819). Pasquinelli (2012) identifies three processes about neuromyths’ origins as 1) distortions of scientific facts, 2) obsolete offspring of scientific hypotheses, or 3) outgrowths from misinterpretations of experimental results. In the case of the dyslexia myth, its origins can be found in obsolete ideas stemming from previously held scientific hypotheses, which have been debunked by 40 years of reading research. Unfortunately, approaches that bridge reading research and education fields featuring updated models of dyslexia with prominent contributions from neuroscience are not typically accessible to preservice educators or school professionals (Anderson et al., 2020; Riley, 2020).” (p. 317)

Alida, A. (2021). Advancing school professionals’ dyslexia knowledge through neuroscience: Bridging the science-education gap through developmental psychology. Frontiers in Education, 5, 316- 320. https://www.frontiersin.org/article/10.3389/feduc.2020.615791

“Numerous empirical studies5 reveal that even though pre-service and in-service teachers as well as university instructors exhibit great interest in neuroscience, they are unable to differentiate neuromyths from “neurofacts”6 (Grospietsch and Mayer, 2020). Studies demonstrating endorsement of neuromyths among in-service teachers have been conducted in England (Dekker et al., 2012; Simmonds, 2014; Horvath et al., 2018), the Netherlands (Dekker et al., 2012), Switzerland (Tardif et al., 2015), Italy (Tovazzi et al., 2020), Spain (Ferrero et al., 2016), Portugal (Rato et al., 2013), Greece (Deligiannidi and Howard-Jones, 2015), Turkey (Karakus et al., 2015), Morocco (Janati Idrissi et al., 2020), China (Pei et al., 2015), Australia (Bellert and Graham, 2013; Horvath et al., 2018), Canada (Lethaby and Harries, 2016; Blanchette Sarrasin et al., 2019), United States (Lethaby and Harries, 2016; Macdonald et al., 2017; Horvath et al., 2018; van Dijk and Lane, 2018) and Latin America (Herculano-Houzel, 2002; Bartoszeck and Bartoszeck, 2012; Gleichgerrcht et al., 2015; Hermida et al., 2016; Varas-Genestier and Ferreira, 2017; Bissessar and Youssef, 2021). Studies demonstrating endorsement of neuromyths among pre-service teachers have been conducted in England (Howard-Jones et al., 2009; McMahon et al., 2019), Germany (Düvel et al., 2017; Grospietsch and Mayer, 2018; 2019), Switzerland (Tardif et al., 2015), Austria (Krammer et al., 2019; 2020), Slovenia (Škraban et al., 2018); Spain (Fuentes and Risso, 2015), Greece (Papadatou-Pastou et al., 2017), Turkey (Dündar and Gündüz, 2016; Canbulat and Kiriktas, 2017), South Korea (Im et al., 2018), Australia (Kim and Sankey, 2017), United States (Ruhaak and Cook, 2018; van Dijk and Lane, 2018) and Latin America (Herculano-Houzel, 2002; Falquez Torres and Ocampo Alvarado, 2018). The majority of such studies focus on pre-service and in-service teachers across all subjects and school types. Their findings consistently show that pre-service and in-service teachers endorse a large number of neuromyths, despite some (country-specific7) differences in the endorsement of certain individual myths (Grospietsch and Mayer, 2020). The hypothesis that cultural differences between countries influence which neuromyths gain currency where has taken hold in the research discourse (e.g., Pei et al., 2015; Ferrero et al., 2016; Hermida et al., 2016), even though this has not yet been systematically tested.

A few studies on neuromyths investigate specific groups such as post-graduate teacher trainees (Howard-Jones et al., 2009), pre-service special education teachers (Ruhaak and Cook, 2018), school principals (Zhang et al., 2019), or pre-service music (Düvel et al., 2017) and biology teachers (Grospietsch and Mayer, 2018; Grospietsch and Mayer, 2019). Comparisons of different groups are undertaken by Canbulat and Kiriktas (2017), Dündar and Gündüz (2016), Düvel et al. (2017), Gleichgerrcht et al. (2015), Herculano-Houzel (2002), Horvath et al. (2018), Macdonald et al. (2017), Simmonds (2014), Tardif et al. (2015) and van Dijk and Lane (2018). Macdonald et al. (2017) show that members of the general public endorse neuromyths more frequently than educators and persons with high neuroscience exposure. Herculano-Houzel (2002) likewise identifies a significant difference between the general public and neuroscientists. Her study finds differences between high school respondents, college respondents, graduate respondents, psychology students and neuroscientists (listed in order of decreasing endorsement of neuromyths). According to Gleichgerrcht et al. (2015) and van Dijk and Lane (2018), university professors and instructors in the field of teacher education exhibit slightly lower endorsement of neuromyths compared to (pre-service) teachers. In a study by Canbulat and Kiriktas (2017), in-service teachers endorse neuromyths slightly less frequently than pre-service teachers. These findings contradict those by Tardif et al. (2015), who found stronger endorsement of many neuromyths among in-service teachers. Zhang et al. (2019) and Horvath et al. (2018) demonstrate that even school principals and award-winning teachers endorse neuromyths with a high frequency. With the exception of the aforementioned differences, empirical findings on the prevalence of neuromyths can be considered quite consistent: Neuromyths are not sufficiently disavowed – particularly among teachers and university instructors, who are frequently assumed to be professionals in teaching and learning. Endorsement of the neuromyths on the existence of learning styles and the effectiveness of Brain Gym, which have found their way into learning guides and educational programs, is particularly high among these two groups as well as all other studied groups (Grospietsch and Mayer, 2020).

Tardif et al. (2015) demonstrate that (pre-service) teachers come into contact with neuromyths and associated practices during both their academic and practical training. A study by Howard-Jones et al. (2009) confirms that 56–83% of pre-service teachers encounter educational programs rooted in neuromyths during their first year of practical training in schools, which is associated with a high level of acceptance of these myths. Simmonds (2014) shows that many teachers use or have used unproven techniques such as Brain Gym in their instruction. Lethaby and Harries (2016) and Blanchette Sarrasin et al. (2019) provide evidence that many teachers who endorse neuromyths also employ instructional practices linked to these misconceptions in their classrooms (this is the case more frequently among preschool and elementary school teachers than secondary school teachers). Grospietsch and Mayer (2019) found a small positive association between endorsement of neuromyths and constructivist beliefs about teaching and learning. This association might indicate that highly engaged, innovative teachers are the ones who make a well-intentioned effort to incorporate ostensibly neurodidactic principles into their instruction. Conversely, Ruhaak and Cook (2018) show that teachers with accurate conceptions regarding neuromyths are more likely to employ effective instructional practices rather than ineffective ones based on neuromyths.” (p.255-256)

Grospietsch, F., & Lins I. (2021). Review on the prevalence and persistence of neuromyths in education – where we stand and what is still needed. Frontiers in Education, 6, 250-262. https://www.frontiersin.org/article/10.3389/feduc.2021.665752

And in Australian education?

“Hitherto, the contribution of philosophers to Neuroscience and Education has tended to be less than enthusiastic, though there are some notable exceptions. Meanwhile, the pervasive influence of neuromyths on education policy, curriculum design and pedagogy in schools is well documented. Indeed, philosophers have sometimes used the prevalence of neuromyths in education to bolster their opposition to neuroscience in teacher education courses. By contrast, this article views the presence of neuromyths in education as a call for remedial action, including philosophical action. The empirical basis of this article is a survey, conducted over a period of three years, involving a total of 1144 first-year pre-service student teachers, which revealed alarming levels of belief in five common neuromyths related to children and learning. This study also attempted to probe the origins of these mistaken beliefs and why they gain traction. The findings suggest an urgent need in teacher education to address the problem of neuromyths, not simply because they are mistaken, they often misdirect valuable resources and mislabel children. The article calls for a compulsory unit on neuroscience and education in all courses of teacher education. Moreover, teaching neuroscience in education cannot be left to specialist neuroscientists, philosophers must be involved.” (p. 1214)

Kim, M., & Sankey, D. (2018). Philosophy, neuroscience and pre-service teachers’ beliefs in neuromyths: a call for remedial action. Educ. Philos. Theory, 50(13), 1214–1227. doi:10.1080/00131857.2017.1395736

“Background: It is not well understood whether qualified teachers believe neuromyths, and whether this affects their practice and learner outcomes. Method: A standardised survey was administered to practising teachers (N = 228) to determine whether or not they believe fictional (neuromyth) or factual statements about the brain, the confidence in those beliefs, and their application. Results: Although factual knowledge was high, seven neuromyths were believed by >50% of the sample. Participants who endorsed neuromyths were generally more confident in their answers than those who identified the myths. Key neuromyths appear to be incorporated into classrooms. Conclusion: Australian teachers, like their overseas counterparts, have some neuroscience awareness but are susceptible to neuromyths. A stronger partnership with neuroscientists would addresss the complex problem of disentangling brain facts from fictions, and provide better support for teachers.

Hughes, B., Sullivan, K., & Gilmore, L. (2020). Why do teachers believe educational neuromyths? Trends in Neuroscience and Education, 21. 100145. https://doi.org/10.1016/j.tine.2020.100145

“The term neuromyths refers to misconceptions about learning and the brain. Educator neuromyths may result in inappropriate instruction, labelling of learners, and wasted resources. To date, little research has considered the sources of these beliefs. We surveyed 1359 Australian preservice educators (M = 22.7, SD = 5.7 years) about their sources of information for 15 neuromyth and 17 general brain knowledge statements. Consistent with previous studies, neuromyth beliefs were prevalent. Predictors of neuromyth accuracy included general brain knowledge and completion of university classes addressing neuromyths, although effects were modest. Depending on the belief, participants relied on general knowledge, academic staff, school staff, and popular media. … attempts to address widely accepted neuromyths in preservice teachers have met with inconsistent success. Developing strategies for effectively addressing neuromyths, particularly those with the potential to negatively impact on teaching and learning, stands as a priority for future research.” (p. 94)

Carter, M., Van Bergen, P., Stephenson, J., Newall, C., & Sweller, N. (2020). Prevalence, predictors and sources of information regarding neuromyths in an Australian cohort of preservice teachers. Australian Journal of Teacher Education, 45(10), 94-113. http://dx.doi.org/10.14221/ajte.2020v45n10.6

Sigh, we’re back to the role of evidence-based practice in education!

Dr Kerry Hempenstall, Senior Industry Fellow, School of Education, RMIT University, Melbourne, Australia.
Each of my articles is available as a PDF at https://tinyurl.com/y6vat4ut

Interest in autism spectrum disorder has led us down numerous paths – and some culs de sac.

Eugen Bleuler in 1908 coined the term autism to describe just one severely withdrawn patient - autós meaning self in the Greek language - implying an inward focus that is reflected in difficulties with social interaction. From the 1940s, Asperger took a particular interest in the higher functioning individuals with autism, while Kanner’s work focussed upon the more severely affected. As to causation, Bruno Bettelheim claimed that maternal “coldness” was the cause of ASD. Intuition, rather than evidence, produced this outrageous proposition, yet, such was the influence of the psychoanalytic interpretations of human behaviour that this view remained influential for many years.

Since then, there have been many unproven assertions about its cause, such as mercury poisoning purportedly from MMR [measles, mumps, and rubella] vaccinations asserted by now disgraced anti-vaxxer and physician Andrew Wakefield. Other proposed causes have included television, power lines, nuclear power stations, mobile phone towers, sex position during conception, food allergies, air pollution, and environmental toxins. For a list of 43 mooted environmental causes, see Russell, Kelly, and Golding (2010).

Russell, G., Kelly, S., & Golding, J. (2010). A qualitative analysis of lay beliefs about the aetiology and prevalence of autistic spectrum disorders. Child: Care, Health, and Development, 36(3), 431-436. http://www.brown.uk.com/brownlibrary/russell.pdf

Forged by desperation, intuition, or cynical exploitation, non-evidence based treatments have proliferated. For example, the use of hyperbaric chambers, removal of purported heavy metals from the body (chelation), holding therapy, auditory integration therapy, secretin injections, wrapping in cold wet sheets, craniosacral therapy, cannabis, dolphin-assisted therapy, art therapy, music therapy, pet facilitated therapy, camel milk, and various dietary regimes.

“The second part of the text focuses on ‘Historical, Cultural and Psychological Issues.’ ‘History of Fad, Pseudoscientific, and Dubious Treatments in Intellectual Disabilities’, provides a captivating overview of the history of questionable treatments and key components of sound research methodology. Here is where several chapters analyze the most appalling illustrations of bad practice. They include: psychomotor processing, gentle teaching, sensory integration theory, auditory integration therapy, facilitated communication, nonaversive interventions, positive behavioral support, biological or alternative medical interventions, and energy based and paranormal-based therapies. The discussion outlines longstanding factors that can lead to practitioner acceptance without evidence of effective outcomes. ‘The Delusion of Full Inclusion’, is a must read as is ‘Explaining Gullibility of Service Providers Toward Treatment Fads.’ ‘Developmental Disabilities and the Paranormal’ explains why autism attracts dubious therapies. … In part five, ‘Intervention Specific Issues’, the writers offer detailed analysis of several questionable therapies in chapters titled ‘Sensory Integration Therapy’, ‘Auditory Integration Training’, Facilitated Communication’, ‘Positive Behavior Support’, ‘Non-aversive Treatment’, ‘Gentle Teaching’, ‘Pet Me, Sniff Me, Squeeze Me’, ‘Relationship Based Therapies’, ‘Old Horses in New Stables’, ‘The Gluten Free, Casein Free Diet’. … The contributing authors cover separate topics, but agree that interventions utilizing the principles of Applied Behavior Analysis have produced wide-ranging, long-lasting benefits to individuals with autism and ID.” (McKeithan, 2017, p.184)

Mckeithan, G. (2017). Review of: controversial therapies for autism and intellectual disabilities: Fad, fashion, and science in professional practice. International Journal of Developmental Disabilities, 63(3), 184-185.

“The desire for a quick fix or the many interventions that promise cures or rapid results lead parents, professionals, and policy makers toward unproven or ineffective interventions for individuals with autism spectrum disorder (ASD). Symptoms of ASD appear early in life and persist throughout the person’s lifetime. Although we have seen advances in the treatment of ASD, the cause remains widely unknown and this then leaves autism wide open for the development of a large number of interventions (Worley et al., 2014). The unfortunate truth is that these interventions are most often not subject to scientific inquiry and thereby are often used in the absence of any reported efficacy. Parents and children are potentially subjected to harm and, at the very least, a roller coaster ride of emotions as their hopes are raised and dashed again and again. It is of utmost importance that the public is educated about interventions for individuals with ASD and that interventions based in pseudoscience are not left unchecked and allowed to persist. The antidote to pseudoscience is education, critical thinking, and the use of the scientific method. Consumers must be critical of the “newest fad” touted by celebrities, professionals, or advocates of the intervention. At this time, it is well documented that treatments based in ABA [Applied Behavior Analysis] have the most research support and ideally should receive the most attention and promotion in comparison with the pseudoscientific interventions to which we previously referred. The responsibility of our community lies with the promotion of science-based interventions while educating others to have a critical lens toward unproven interventions.” (p.415)

McDonald, M.E., & DiGennaro Reed, F.D. (2018). Distinguishing science and pseudoscience in the assessment and treatment of autism spectrum disorder. In S. Goldstein & S. Ozonoff (Eds.), Assessment of autism spectrum disorder (p. 415–441). Guilford Press.

“The hope for an immediate and dramatic panacea for ASD leads many professionals, parents, and policy makers to unproven interventions. According to Favell (2005), when parents are looking for a treatment for their children, claims of quick, effortless, and easy interventions, although undocumented, can be more attractive, than the scientifically based approaches that don’t make the same claims. Interventions presented as Levels 1 and 2 with validated evidence for effectiveness, can be labor intensive and slow in yielding progress. As long as there is no definitive explanation for the growing number of cases of ASDs, new theories will be put forth and people will claim to have found a cure. The scientific and professional community’s responsibility is clear. In order for parents to be informed consumers and advocates for their child with autism spectrum disorders, the need for valid evidence-based practices has never been more critical.” (p.300)

McDonald, M.E., Pace, D., Blue, E., & Schwartz, D. (2012). Critical issues in causation and treatment of autism: Why fads continue to flourish. Child & Family Behavior Therapy, 34(4), 290-304.

“The “chicness” of an intervention should not be determined by its age or origins but by its effectiveness. Unfortunately, some interventions are considered chic for other reasons, including pretense that they do what they do not. Some interventions are considered chic by their proponents because they claim to allow people with disabilities to do something no one thought they could or to be something no one imagined they are. On closer inspection, the claims made about these interventions are found to be false; proponents falsely claim to make people with disabilities something they manifestly are not, falsely attribute behavior or ability to persons with disabilities, or grossly exaggerate individuals’ abilities. Such sham is characteristic of “faith healing,” particularly of physical or sensory disabilities, but it is most deviously, often shamelessly, practiced in cases of cognitive and emotional/behavioral disabilities. Perhaps the most familiar practice of disability chic related to cognitive function is facilitated communication (FC, now often relabeled “rapid prompting”). Its description and a review of related research are beyond the scope of this article. However, media coverage of FC, plus the fact that a dean of education (Douglas Biklen) at a major institution of higher education (Syracuse University) promoted and continues to promote it has made it an intervention considered chic by some (e.g., see Biklen, 2001; Engber, 2015; Jacobson, Foxx, & Mulick, 2016). The fact is that FC remains a chic intervention in some circles, even though the practice has been thoroughly debunked. It is considered an alternative means of communication on which The Association for Persons with Severe Handicaps (TASH) takes no position (Trader & Edwards, 2016). Promotion or acceptance of FC as a means of communication is a kind of science denial (Specter, 2009), pretense buttressed by individual belief. FC is considered legitimate only by extreme denial of scientific evidence and extreme adherence to an ideology considered superior to science. FC and other practices that some still consider chic are a matter of considerable frustration to those who see applied behavioral analysis as chic because it is grounded in evidence (see Foxx & Mulick, 2016; Jacobson et al., 2016; Travers, Tincani, & Lang, 2014). We see the TASH acquiescence to extremism in this case as equivocation at best, probably more accurately described as science denial.” (p.55)

Kauffman, J.M., & Badar, J. (2018). Extremism and disability chic. Exceptionality, 26(1), 46-61. DOI: 10.1080/09362835.2017.1283632

Often a claim, having been shown to be ineffective, returns in a new guise. For example, the Rapid Prompting Method (RPM) appears to represent a variant of the discredited Facilitated Communication approach.

“This systematic review was deemed empty and revealed no evidence in relation to RPM’s effectiveness meeting our inclusion criteria. The developers of RPM and its proponents have yet to fulfill the crucial burden of proof requirement demanded for novel interventions. Although lack of evidence does not necessarily demonstrate a lack of effect, until future trials have demonstrated safety and effectiveness, and perhaps more importantly, have first clarified the authorship question, we strongly discourage clinicians, educators, and parents of children with ASD from using RPM.” (Schlosser, et al., 2019, p. 8)

Schlosser, R.W., Hemsley, B., Shane, H. Todd, J., Lang, R., Lilienfeld, S.O., Trembath, D.M., Fong, S., & Odom, S. (2019). Rapid prompting method and autism spectrum disorder: Systematic review exposes lack of evidence. Review Journal of Autism and Developmental Disorders, 6, 403-412. https://doi.org/10.1007/s40489-019-00175-w

“FC involves a therapist (or facilitator) supporting the hand of a person with autism while a message is typed on a letter board. FC is widely acknowledged to be a pseudoscientific, unsafe, and unethical treatment for people with autism. RPM is a more recent intervention for people with autism that involves the facilitator holding and moving the letter board while the individual with autism moves their own hand. Those who espouse the perceived benefits of FC and RPM make strikingly similar claims of hidden intelligence and extraordinary communication abilities in people with autism following treatment. Conclusion: Clients, proponents, and practitioners of RPM should demand scientific validation of RPM in order to ensure the safety of people with disabilities that are involved with RPM.” (p. 219)

Tostanoski, A., Lang, R., Raulston, T., Carnett, A., & Davis, T. (2014) Voices from the past: Comparing the rapid prompting method and facilitated communication. Developmental Neurorehabilitation, 17(4), 219-223. DOI: 10.3109/17518423.2012.749952

So, the search for cause(s) continues in the science-based domain, as do the intervention attempts of those with a less-than-scientific persuasion. In the scientific research, the influence of genetics and gene-environment interaction are now major areas of interest.

Whitehouse, A. (2016). What causes autism? What we know, don’t know and suspect. The Conversation, February 19, 2016. https://theconversation.com/what-causes-autism-what-we-know-dont-know-and-suspect-53977

What is the ASD prevalence in Australia and USA?

“In 2018: there were 205,200 Australians with autism, a 25.1% increase from the 164,000 with the condition in 2015. Males were 3.5 times more likely than females to have the condition, with prevalence rates of 1.3% and 0.4% respectively.” (Australian Bureau of Statistics, 2018)

Australian Bureau of Statistics. (2018). Disability, Ageing and Carers, Australia: Summary of Findings, 2018. https://www.abs.gov.au/statistics/health/disability/disability-ageing-and-carers-australia-summary-findings/latest-release

“This study aimed to provide an autism spectrum disorder (ASD) prevalence update from parent and teacher report using the Longitudinal Study of Australian Children (LSAC). The LSAC is a prospective cohort study of Australian children representative of the population with two cohorts: Kinder (birth year 1999/2000) and Birth cohort (birth year 2003/2004). … Parent-reported ASD prevalence in 2016 in 12-year-old children from the Birth cohort of the Longitudinal Study of Australian Children was 4.4%, and higher than the 2.6% in the earlier born Kinder cohort. The Birth cohort had a milder presentation with fewer social, emotional, and behavioral problems than the Kinder cohort. Milder cases of ASD are being diagnosed in Australia resulting in one of the highest reported prevalence rates in the world” (May, Brignell, & Williams, 2020, p. 821)).

May, T., Brignell, A., & Williams, K. (2020). Autism Spectrum Disorder prevalence in children Aged 12–13 years from the Longitudinal Study of Australian Children. Autism Research, 13, 821–827.

“The U.S. Department of Education (USDE, 2014) reported that more than 5.8 million children, or 8.4% of the total student population between the ages of 2 and 6, received services under IDEA Part B in 2012 (IDEA, 2004). Of these students receiving special education services, 40% were classified as having specific learning disabilities, 18% had speech or language impairments, 7% were diagnosed as having autism, and 7% were classified as having intellectual disabilities, with the remaining students falling into the categories of other health impairments, emotional disturbances, and all other disabilities combined (USDE, 2014).”

What’s happening with diagnosis of ASD and assessment issues?

“There have been significant changes in the way Autism has been defined especially in the last decade. The changes encompass criteria over a spectrum rather than individual diagnoses based on clusters of criteria. With these changes, there has been a push for earlier screening and diagnosis to be made to ensure individual impacted by the deficits have ample time and opportunity to receive the services they need. Additionally, with the changes that have come up, screening tools and assessments have also been changed and improved to assist with the increasing demand of early screening. Screeners have been created to help in primary care settings so physicians can gauge the severity of symptoms and refer patients to the appropriate resources. The assessment and diagnostic process for Autism involves a large battery including parental interviews and forms, the ADOS-II, and a multitude of other intellectual assessments to get a full picture of what the individual is experiencing. Once an individual is diagnosed with Autism, the interventionist team, physicians, and clinicians assist the family in finding the appropriate resources and treatment plan.” (p.66)

Chahin, S.S., Apple, R.W., Kuo, K.H., & Dickson, C.A. (2020). Autism spectrum disorder: Psychological and functional assessment, and behavioral treatment approaches. Translational Pediatrics (Neurodevelopmental and Neurobehavioral Disorders in Children), 9(1), S66-S75.

“Clendon et al. (2021) contribute to this forum with a tutorial on how to assess emergent and early literacy skills in children with ASD who have limited verbal communication skills. This group of children with ASD has been described as “the neglected end of the spectrum” (Tager-Flusberg & Kasari, 2013), partly because of the difficulties in valid assessment. The authors present a comprehensive emergent and early literacy assessment battery that was developed and trialed as part of a pilot project specifically for children with ASD who do not use verbal communication, with many of these children demonstrating an intellectual disability. In addition, the authors provide an overview of ASD-specific assessment considerations, summarized in an assessment preparation checklist, to assist clinicians in selecting appropriate assessment tools and providing appropriate supports during the assessment sessions (see also Paynter, 2015). The tutorial clearly highlights the need for a comprehensive, well-planned, individualized, and child-friendly assessment approach involving all members of the educational team.” (p.150)

Westerveld, M.F., & Paynter, J. (2021). Introduction to the forum: Literacy in autism-across the spectrum. Language, Speech and Hearing Services in Schools, 52(1), 149-152.

There is diversity among those with ASD

Dr. Stephen Shore is responsible for the famous quote: “If you’ve met one person with autism, you’ve met one person with autism.”

Dr. Stephen Shore “This quote emphasizes that there is great diversity within the autism spectrum. While the commonalities of people on the autism spectrum include differences in communication, social interaction, sensory receptivity, and highly focused interests, it’s important to understand that the constellation of these characteristics blends together differently for each individual. This is why some on the spectrum are good at mathematics while other may be good in their arts, sports, or writing – just like the rest of humanity. Autism is an extension of the diversity found in the human gene pool.”

Lime Connect. (2020). Leading perspectives on disability: A Q&A with Dr. Stephen Shore, 23/3/2020. https://ibcces.org/blog/2018/03/23/12748/

Adding to this diversity is the wide range of comorbid conditions affecting the ASD community. Apart from sex differences such as a male to female ratio of  4– 5:1, there are reported elevated rates of ADHD, schizophrenia, and epilepsy, gastrointestinal difficulties (including constipation and diarrhea), sleep disorders, autoimmune disorders, Type 1 diabetes, muscular dystrophy, and CNS/cranial anomalies (Supekar, Iyer, & Menon, 2017).

Supekar, K., Iyer, T., & Menon, V. (2017). The influence of sex and age on prevalence rates of comorbid conditions in autism. Autism Research, 10(5), 778-789. http://med.stanford.edu/content/dam/sm/scsnl/documents/the-influence-of-sex-and-age-on-prevalence-rates-of-comorbid-conditions-in-autism.pdf

This paper is largely focussed upon the issue of literacy with this population. Do children with ASD have particular problems with reading?

For an interesting series of 10 very recent articles on ASD and reading, see Language, Speech and Hearing Services in Schools: Literacy in Autism—Across the Spectrum (janvier 2021)at  http://www.cra-rhone-alpes.org/spip.php?article12249

First it is important to recognise that not all children with ASD will have difficulties with reading acquisition. However, studies suggest that an unnecessarily high proportion do so. They are a heterogenous group, varying across a number of characteristics relevant to reading. Providing only average figures across the various domains, thus, can be misleading.

“Children with Autism Spectrum Disorder (ASD) are at increased risk of failure in acquiring and developing adequate reading skills (e.g., Henderson et al. 2014; Westerveld et al. 2016). Although the majority of children with ASD show difficulties in reading comprehension, studies suggest as many as 50% of children with ASD struggle with reading accuracy, with some children not learning to read at all (Nation et al. 2006; Westerveld et al. 2018).” (p.3060)

Westerveld, M.F., Paynter, J., Brignell, A. et al. (2020). No differences in code-related emergent literacy skills in well-matched 4-year-old children with and without ASD. Journal of Autism and Developmental Disorders, 50, 3060–3065. https://doi.org/10.1007/s10803-020-04407-5

“Autism spectrum disorder (ASD) is an early-onset neurodevelopmental disorder characterized by social communication deficits and restricted, repetitive patterns of behavior or interests (American Psychiatric Association, 2013). … Beyond these core diagnostic characteristics, the clinical presentation of ASD is highly heterogeneous, although delays in oral language development are common and approximately 30% of children go on to develop only minimal verbal communication skills2 (Anderson et al., 2007; Kasari et al., 2013). Limitations in social communication and oral language development as well as other common comorbidities, including challenging behaviors and intellectual disability, have the potential to constrain academic participation and achievement for some children with autism (Jones et al., 2009; Randi et al., 2010). With an estimated 1% of children worldwide diagnosed with ASD and the potential for growing numbers due to underdiagnosis of girls,3 there is a pressing need to identify effective methods for improving educational outcomes for this population (Australian Bureau of Statistics, 2018; Baxter et al., 2015; Christensen et al., 2016; Elsabbagh et al., 2012; Kirkovski et al., 2013). It is well known that reading skills are linked with educational and other life outcomes. Reading can be an area of weakness for some children with autism (Frith & Snowling, 1983; Mawhood et al., 2000; Minshew et al., 1994; Nation et al., 2006). According to the “simple view of reading,” skilled reading requires the development and coordination of two distinct abilities: decoding and listening comprehension (Gough & Tunmer, 1986).” (p. 225-226)

Arciuli, J., & Bailey, B. (2021). The promise of comprehensive early reading instruction for children with autism and recommendations for future directions. Language, Speech and Hearing Services in Schools, 52(1), 225-238.

“Reading is arguably one of the most important skills children learn at school (National Early Literacy Panel, 2008). Although reading is sometimes highlighted as an area of relative strength for children with ASD (e.g., see review of academic skills by Keen, Webster, & Ridley, 2016), many children with ASD, even those with intelligence in the average range, show difficulties acquiring reading skills (Nation, Clarke, Wright, & Williams, 2006). For those who learn to read, up to 60% may show below average performance in reading comprehension (Ricketts, 2011; Ricketts, Jones, Happe, & Charman, ´ 2013). It is, therefore, important to acknowledge the literacy needs of children with ASD along with their social-communication needs. … There is a lack of strong epidemiological data regarding the proportion of children with ASD who experience reading difficulties, with the best current estimates of between 30–60% based on existing data (e.g., Jones et al., 2009; Nation et al., 2006; Ricketts et al., 2013). The estimated high proportion of children with ASD presenting with reading difficulties is not surprising, given that communication impairments affecting oral language and pragmatics are characteristic of ASD, with approximately 25–35% of children with ASD minimally verbal (i.e., little or no verbal communication) at school entry (e.g., Anderson et al., 2007; Rose, Trembath, Keen, & Paynter, 2016). Drawing from the simple view of reading, impairments in oral language clearly put children with ASD at risk of later reading challenges. In addition, rates of intellectual disability (approximately 30%) are elevated in ASD (Centers for Disease Control and Prevention, 2014), and the difficulties children with intellectual disability experience in skills — including reasoning, planning, and problem-solving — are likely to translate to difficulties across educational activities, including learning to read. Although the majority of children with ASD who show reading difficulties experience challenges in reading comprehension skills, with relative strengths in word recognition (Jones et al., 2009; Nation et al., 2006; Ricketts et al., 2013; Troyb et al., 2014), it is important to acknowledge the considerable individual differences in reading ability (Norbury & Nation, 2011).” (p. 205-207)

Paynter, J., Westerveld, M. F., & Trembath, D. (2016). Reading assessment in children with autism spectrum disorder. Journal of Psychologists and Counsellors in Schools, 26(2), 205-217. doi: doi 10.1017/jgc.2016.15

Aren’t students with ASD hyperlexic?

“Much research has focused on children with ASD having “hyperlexia” (i.e., precocious abilities to decode text that are incongruent with, and exceed, their reading comprehension abilities; Frith & Snowling, 1983). This contrasts with research findings that indicate a hyperlexic profile (i.e., strong decoding, poor comprehension) is not the most common (e.g., 25% in Nation et al., 2006) profile observed in children with ASD. These findings highlight the importance of including detailed assessment of word recognition skills in children with ASD rather than assuming this is an easily learnt skill. To illustrate, in our recent study (Westerveld et al., 2018) investigating the word reading abilities of 41 children with ASD who were in their first year of schooling, we found that 56% performed below expectations in reading accuracy on a standardized assessment of reading ability (York Assessment of Reading for Comprehension; Snowling et al., 2012).” (p.167)

Clendon, S., Paynter, J., Walker, S., Bowen, R., & Westerveld, M.F. (2021). Emergent literacy assessment in children with autism spectrum disorder who have limited verbal communication skills: A tutorial. Language, Speech, and Hearing Services in Schools, 52, 165–180.

“Reading can be an area of weakness for some children with autism (Frith & Snowling, 1983; Mawhood et al., 2000; Minshew et al., 1994; Nation et al., 2006). According to the “simple view of reading,” skilled reading requires the development and coordination of two distinct abilities: decoding and listening comprehension (Gough & Tunmer, 1986). This model captures the well-accepted fact that reading ability is underpinned by multiple componential skills. Many early studies of reading and autism focused on hyperlexia or precocious reading, where decoding skills seemed more advanced relative to comprehension skills or broader intellectual functioning (Burd & Kerbeshian, 1985; Calhoon, 2001; Grigorenko et al., 2003; Huemer & Mann, 2010; Lanter & Watson, 2008; Newman et al., 2007). However, more recent studies have pointed out the discrepancies in definitions of hyperlexia and the great variability seen in both the decoding and comprehension skills of children with autism (Arciuli et al., 2013; Norbury & Nation, 2011; Tong et al., 2019). As such, the topic of hyperlexia is less of a focus in the autism literature than it once was.” (p. 226)

Arciuli, J., & Bailey, B. (2021). The promise of comprehensive early reading instruction for children with autism and recommendations for future directions. Language, Speech and Hearing Services in Schools, 52(1), 225-238.

“Right posterior inferior temporal sulcus in hyperlexic reading. This extra-striate region has been implicated in visual form recognition (Tanaka, 1997), and our normative developmental study revealed that children developmentally disengage this area over the course of reading acquisition (Turkeltaub et al., 2003). Young children probably recruit these right extrastriate regions for early phases of reading, during which they use visual patterns or visual context to recognize words (e.g., a small word with a tail is “dog,” a word in a red hexagonal sign is “stop”) (Ehri, 1999; Frith, 1985; Hoien and Lundberg, 1988). Then, these areas are likely disengaged as children rely more on letter-to-sound correspondences and less on visual configural analysis to identify words. … the fMRI data do not support a memory-based mechanism for reading. (p.1)

Turkeltaub, P.E., D. L. Flowers, A. Verbalis, M. Miranda, L.Gareau & Eden, G.F. (2004). The neural basis of hyperlexic reading: An fMRI case study. Neuron, 41, 1-20.

Some have argued that children with ASD are visual learners, and any difficulties are best addressed by teaching them through some form of visually-based instruction.

“Many educators have found that children with one of the autism spectrum disorders may struggle with verbal instruction, or the decoding of a written text, but seem to thrive with instruction that incorporates anything visual, particularly visuals that correspond seamlessly with the text with which they are engaging” (Reading Eggs, nd).

Reading Eggs (n.d.). Retrieved from http://readingeggs.com.au/articles/2012/08/15/reading-and-autism/

“Because children with ASD have a greater propensity to learn through visual means than auditory-based teaching techniques, visually based strategies such as video modeling hold promise in positively impacting the learning of children with ASD.” (Ganz, Earles-Vollrath, & Cook, 2011, p. 17)

Ganz, J.B., Earles-Vollrath, T.L., & Cook, K.E. (2011). Video modelling: A visually based intervention for children with Autism Spectrum Disorder. Teaching Exceptional Children, 43(6), 8-19.

So, do the low progress children with ASD require a special form of reading instruction, such as one that eschews initial phonics in favour of strategies that shift the emphasis to the visual? Adopting this perspective may lead to a strong emphasis on whole word reading in beginning reading instruction to the detriment of ensuring a strong base of phonological skills. Would that be beneficial?

Some research has failed to find such a visual predilection among students with ASD.

“Children with autism spectrum disorder (ASD) are often described as visual learners. We tested this assumption in an experiment in which 25 children with ASD, 19 children with global developmental delay (GDD), and 17 typically developing (TD) children were presented a series of videos via an eye tracker in which an actor instructed them to manipulate objects in speech-only and speech + pictures conditions. We found no group differences in visual attention to the stimuli. The GDD and TD groups performed better when pictures were available, whereas the ASD group did not. Performance of children with ASD and GDD was positively correlated with visual attention and receptive language. We found no evidence of a prominent visual learning style in the ASD group. (Trembath, Vivanti, Iacono, et al., p. 3276)

Trembath, D., Vivanti, G., Iacono, T. et al. (2015). Accurate or assumed: Visual learning in children with ASD. J Autism Dev Disorders, 45, 3276–3287. https://doi.org/10.1007/s10803-015-2488-4

“The present study examined the learning curves in children with ASD, ADHD, VCFS and controls across repeated trials using the visual and word selective reminding tasks of the TOMAL. The main novel finding is that contrary to expectations, the ASD group demonstrated a relative weakness in visual learning compared to neurotypicals and children with ADHD, and this does not appear to be accounted for by differences in general visuo-spatial abilities as children with ASD demonstrated similar nonverbal intellectual skills as the neurotypical and ADHD sample.” (Erdodi, Lajiness-O’Neill, & Schmitt, 2013, p.886)

Erdodi, L.A., Lajiness-O’Neill, R., & Schmitt, T.A. (2013). Learning curve analyses in neurodevelopmental disorders: Are children with autism spectrum disorder truly visual learners? Journal of Autism and Developmental Disorders, 43, 880–890. doi: 10.1007/s10803-012-1630-9.

However, even if it were true that students with ASD were more visually-driven, it doesn’t necessarily follow that instruction should thus focus on whole word reading and picturing strategies. It can also be interpreted that the phonological domain requires more intensive, evidence-based instruction for skilled reading to occur, just as it is usually the case with struggling neurotypical readers.

As a general principle, effective reading programs tend to be shown to be effective for all children rather than only for specific groups (Goyen, 1992; O'Neill & Dunlap, 1984). Perhaps this is because the task itself is a more productive curriculum focus than are differences in learner characteristics. So, attention to the methods shown to reflect current knowledge about reading development and instruction appears to be the most apt direction.

Goyen, J. (1992). Diagnosis of reading problems: Is there a case? Educational Psychology, 12, 225-237.

O'Neill, R., & Dunlap, G. (1984, Spring). DI principles in teaching autistic children. Direct Instruction News, 3(3), 21.

“More recent research has focused on confirming that similar skill sets contribute to successful reading in children with and without autism (e.g., Dynia et al., 2017; Jacobs & Richdale, 2013; McIntyre et al., 2017; Nash & Arciuli, 2016; Ricketts et al., 2013). However, at least some of the reading difficulties experienced by children with autism can be attributed to more distal factors, including the nature of children’s literacy experiences and the type and quality of reading instruction…. Similarities in the skills underlying reading for children with and without autism have prompted researchers to investigate whether children with autism can benefit from the same kind of evidence-based reading instruction that is helpful for any beginning, at-risk, or low-progress reader.” (p.226)

Arciuli, J., & Bailey, B. (2021). The promise of comprehensive early reading instruction for children with autism and recommendations for future directions. Language, Speech and Hearing Services in Schools, 52(1), 225-238.

“The present paper firstly confirmed prior research [8,9,22] by showing a great heterogeneity (from floor to ceiling levels) in literacy skills in this sample of 12-year olds with ASD without ID. Importantly, though, there were significantly increased rates of poor reading comprehension and reading fluency in our study cohort compared with population norms. The crosssectional results obtained in the study also support the notion that different language/cognitive skills are uniquely predictive of different literacy subskills. These findings are important as they detail the language/cognitive background factors associated with each of the important literacy skills analyzed in the study. Interestingly, when it comes to the relative importance of the language/cognitive skills in predicting literacy scores, the pattern of results is likely to be familiar to many general reading researchers (i.e. outside the context of autism) (c.f., 3,7]. Thus, literacy seemed to be supported by many of the same underlying subskills in children with ASD as in non-ASD children. As pointed out by Bailey and Arciuli [14], potentially important issues are at stake in this context, because if there are similar concurrent predictors of literacy and literacy problems in children with ASD, then there are greater reasons to assume that standard models of (remedial) literacy instruction might be helpful also for children with ASD. From clinical and educational perspectives, this also highlights the importance of assessing literacy skills in students with ASD so that pedagogic interventions can be provided for those in need of it – instead of assuming that any literacy problems are secondary or “just part of the autism.” Besides support for general phonological models of spelling and word reading accuracy [4,7], we observed a clear and distinct association between RAN and reading fluency, also in keeping with a large general literature on children’s literacy development [23]. Besides phonological awareness, also semantic processing, indexed by listening comprehension capacities, made a unique contribution in predicting word reading accuracy and spelling, which align well with predictions from the lexical quality hypothesis [5]. Finally, for reading comprehension, we found it to be statistically predicted mainly by listening comprehension. Also this finding is in line with a widely accepted general model of reading comprehension, namely the simple view of reading [24], which predicts that reading comprehension capacities in individuals with adequate word reading skills (accuracy and fluency) will closely mirror listening comprehension.” (p.3, 4)

Johnels, J.A., Fernell, E., Kjellmer, L., Gillberg, C., & Norrelgen, F. (2021). Language/cognitive predictors of literacy skills in 12-year-old children on the autism spectrum. Logopedics Phoniatrics Vocology, DOI: 10.1080/14015439.2021.1884897

There is also support for this position arising from some of the neuroscience findings, such as from Dehaene (2009, 2020).

“It simply is not true that there are hundreds of ways to learn to read […] when it comes to reading we all have roughly the same brain that imposes the same constraints and the same learning sequence” (p. 218) - “… all children regardless of their socioeconomic backgrounds benefit from explicit and early teaching of the correspondences between letters and speech sounds. This is a well-established fact, corroborated by a great many classroom experiments. Furthermore, it is coherent with our present understanding of how the reader’s brain works” (Dehaene, 2009, p. 326).

Dehaene, S. (2009). Reading in the brain: The science and evolution of a human invention. New York: Viking/Penguin.

“Rescind the idea that all children are different. The idea that each of us has a distinct learning style is a myth. Brain imaging shows that we all rely on very similar brain circuits and learning rules. The brain circuits for reading and mathematics are the same in each of us, give or take a few millimetres-even in blind children. We all face similar hurdles in learning, and the same teaching methods can surmount them. Individual differences, when they exist, lie more in children’s extant knowledge, motivation, and the rate at which they learn. Let’s carefully determine each child’s current level in order to select the most relevant problems-but above all, let’s ensure that all children acquire the fundamentals of language, literacy, and mathematics that everyone needs” (Dehaene, 2020, p.240-241)

Dehaene, S. (2020). Why brains learn better than any machine . . . for now. Penguin Publishing Group.

Having pointed to the general instructional direction, what modifications may be specific to this diverse cohort remains an important focus for research?

“Generally speaking, instruction should be individualized in line with profiles of weaknesses, strengths, and interests in children with autism in order to be optimally effective (e.g., Trembath & Vivanti, 2014). In the case of reading instruction, for instance, foundational phonemic awareness and phonics skills should be targeted as a matter of priority for children with autism who have very limited decoding skills, although opportunities to develop reading comprehension, vocabulary, and fluency skills should also be made available to each individual at some point and tailored (e.g., questions in reading comprehension activities could be tailored to match children’s oral language abilities). (p.231)

Arciuli, J., & Bailey, B. (2021). The promise of comprehensive early reading instruction for children with autism and recommendations for future directions. Language, Speech and Hearing Services in Schools, 52(1), 225-238.

 Apart from the phonological domain, another potential area of need for intervention is reading comprehension.

“To gain a broader understanding of the reading capabilities of children representative of the autism spectrum, Nation et al. (2006) examined the reading skills of 41 children with ASD ages 6–15 including 16 identified with autism, 13 with pervasive developmental disorder not otherwise specified (PDD-NOS), and 12 with Asperger syndrome. Inclusion criteria included “measurable language skills” even if language skills were limited. Children were assessed on measures of single word recognition in isolation, pseudoword or nonword recognition, text reading accuracy, and text comprehension; on average, they demonstrated good word reading ability and poor comprehension. Their vocabulary and oral language comprehension scores were highly correlated with their scores on the reading comprehension measure (i.e., .72 and .67 respectively). However, the authors noted large individual differences in performance with some children scoring far above average, and others unable to complete the task. This level of variance demonstrates the heterogeneity in reading ability across the autism spectrum, and suggests using caution when interpreting mean scores for this population of students (Nation et al.). Another study specifically examined the degree to which students with ASD could master phonics rules. Calhoon (2001) studied the word recognition skills of ten children with autism who obtained varied IQ scores ranging from 60 to 100, and were able to identify sight words on a second grade level at the onset of the study. The author assessed each child’s understanding of word parts, grapheme-phonemes, onsets and rime, and recognition of high frequency words. Results indicated that the children had developed phonics skills and that they attended to word parts that provide cues such as rimes. The author suggested phonics instruction that encompasses word families, word parts, and structural analysis (e.g., prefixes and suffixes) may prove beneficial for students with autism. Two further studies have shown that children with Asperger syndrome who developed grade level decoding skills could comprehend material containing factual information, but had trouble making inferences (Griswold, Barnhill, Myles, Hagiwara, & Simpson, 2002; Myles et al., 2002).” (p.1-2)

“Because of the unstable reading profile associated with ASD (Nation et al., 2006), some learners will have difficulty developing both word reading and comprehension skills. Therefore, it is important that reading instruction emphasize both code- and meaning focused skills. Although limited in number and variable in quality, the reviewed studies indicate that children with ASD can benefit from instruction in the five areas of reading recommended by the NRP as well as NRP advocated strategies. In combination these studies yield support for comprehensive reading instruction to include the five areas of reading with a focus on reading/language comprehension in the early grades. Children with ASD may benefit from phonics instruction consistent with the NRP and offered through general education curriculum. For example, the NRP suggested teaching students how to identify sounds in words (i.e., phonemic awareness), map those sounds to each corresponding letter (i.e., phonics), and blend those sounds together to form words (NICHD, 2000). This approach is used in many comprehensive commercial reading programs (e.g., Reading Mastery, Open Court), and is similar to the nonverbal reading approach utilized in the Coleman et al. study (2005). Such approaches are direct and should be taught systematically by introducing all primary sound-letter relationships in a logical and sequential manner (e.g., teaching individual consonant and vowel letter sound relationships prior to blends and digraphs; Ehri, 2004).” (p.10-11)

Whalon, K.W., Al Otaiba, S., & Delano, M.E. (2009). Evidence-based reading instruction for individuals with Autism Spectrum Disorders. Focus on Autism and Other Developmental Disabilities, 24(1), 3–16.

“We conducted a search for scientific articles published from 2000 to 2019 using the keyword “autis*” in combination with the terms “reading comprehension” and “intervention” or “instruction” in Psyc Info and Scopus databases. After applying inclusion and exclusion criteria, a total of 25 studies were selected. The content analysis of these studies shows that when specific interventions are carried out, students with ASD are able to take advantage of the instruction they receive and compensate for difficulties. Understanding inferences and the main idea of the text are the most common reading comprehension topics, and direct instruction is the most widely-used intervention method in the reviewed studies. … In addition, reading comprehension is conditioned by pragmatic characteristics and language comprehension, such as understanding metaphors, jokes, and ironies, making inferences, understanding idioms, or understanding meanings whose interpretation depends on the context. These issues are challenging for students with ASD, even for those with preserved linguistic and cognitive abilities, as in Asperger Syndrome (AS) (level 1 ASD, according to the DSM-5 criteria) [10]. Due to the great heterogeneity in the presentation of the clinical forms of autism, the possible comorbid difficulties, or the age of onset of the first signs and their evolution [11,12], the reading comprehension difficulties can vary in their severity and intensity in students with ASD [13]. Some possible explanations for these difficulties in reading comprehension are the classic theoretical explanations for ASD [14]. For instance, the theory of weak central coherence [15] states that people with ASD have difficulties integrating elements they perceive in isolation into a whole, an essential skill for construction meaning in reading comprehension; the theory of executive dysfunction [16] explains some of the characteristics of ASD based on difficulties in processes such as inhibition, working memory, or planning, key processes in reading comprehension; also, the theory of mind [17] explains some of the difficulties people with ASD have in attributing intentions or mental states in others, a key skill for understanding narrative texts. … The results show that a large number of studies used direct instruction, some of them as the only technique [27, 30–33, 40, 41] and others as a part of the intervention [26]. Direct instruction consists of a teaching approach based on breaking down tasks into sequences of more concrete steps with the aim that students acquire the different skills worked in sequence. It is an approach that emphasizes the structuring of the teaching processes through scripts that guide the teaching process. The results of this review confirm that, according to previous reviews [14,20], this is a positive methodology for teaching school content to children with ASD, considering that these children need individualized attention, and that this systematic methodology is particularly well adapted to the order and structuring needs of students with ASD.” (p.1, 8)

Tárraga-Mínguez, R., Gómez-Marí, I., & Sanz-Cervera, P. (2021). Interventions for improving reading comprehension in children with ASD: A systematic review. Behavioral Sciences, 11(3), xx https://doi.org/10.3390/bs11010003

“Prior research indicates that reading comprehension skills in individuals with ASD align with oral language skills, as well as ASD symptomatology and social communication impairments (McIntyre et al., 2017; Ricketts et al., 2013; Solari et al., 2019). Higher-order cognitive and linguistic comprehension skills such as narrative production and inferencing are linked to proficient reading comprehension and have been shown to be challenging for many individuals with ASD (Norbury & Bishop, 2002; Tirado & Saldana, 2016). In this sample of chil- ~ dren and adolescents with ASD without ID, narrative and inference skills displayed differential patterns of growth. Narrative retelling skills followed a linear trajectory of improvement and standardized means increased from performance in the below average range at TP1 to the average range at TP3, which is an encouraging finding. This growth was not observed for inference skills for which standardized means were more than one standard deviation below average at TP1 and declined further by TP3. Lexical-semantic knowledge explained significant heterogeneity in initial narrative and inference skills, while ASD symptomatology explained additional variance in initial narrative skills and age contributed to variance in initial inference skills. Finally, reading comprehension skills at TP3 were below average and were significantly related to TP1 narrative and inference skills in this sample. Each of these findings is discussed in more detail below. … These findings suggest that narrative and inference skills, in addition to lexical-semantic knowledge, are important to target beginning in elementary grades to improve reading comprehension outcomes for children and adolescents with ASD without ID.” (p.10, 2)

McIntyre, N.S., Grimm, R.P., Solari, E.J., Zajic, M.C., & Mundy, P.C. (2020). Growth in narrative retelling and inference abilities and relations with reading comprehension in children and adolescents with autism spectrum disorder. Autism Dev. Lang. Impair, 5, doi: 10.1177/2396941520968028

“Students with ASD can learn to read, but their disability may provide distinctive challenges for comprehending text. For example, theory of mind, which is the ability to understand or take the perspective of others (Baron-Cohen, Leslie, & Frith, 1985), and weak central coherence, the ability to understand the context or see the bigger picture (Hill & Frith, 2003), have been used to explain the difficulties that students with ASD have with comprehension (Carnahan, Williamson, & Christman, 2011; McIntyre et al., 2017; Ricketts, Jones, Happé, & Charman, 2013). Some students with ASD may lack theory of mind, which can affect their ability to understand characters’ perspectives, emotions, and actions when reading a text (Carnahan, Williamson, & Haydon, 2009). Similarly, having weak central coherence may negatively affect understanding of literary elements such as plot because it requires knowledge of the all the characters and events in the text, as well as the ability to make connections across multiple pieces of information. Specifically, in reading comprehension, students with ASD may be focused on insignificant or irrelevant details of the narrative rather than the global picture (Carnahan et al., 2011).” (p.2)

Chang, Y-C., Menzies, H.M., & Osipova, A. (2021). Reading comprehension instruction for students with autism spectrum disorder. The Reading Teacher, 0(0), 1–10

“Studies conducted between 1980 and 2012 with K-12 students identified with autism spectrum disorders (ASD). Nine single-subject design studies, one quasi-experimental study, and two single-group design studies met the criteria for inclusion. Findings from the studies indicate that modifying instructional interventions associated with improved comprehension for students with reading difficulties may improve reading comprehension in students with ASD. Four studies implemented strategy instruction that included (a) question generation; (b) graphic organizers; and (c) making predictions. Two studies utilized anaphoric cueing instruction, three implemented explicit instruction, and three examined student grouping practices. Among the reviewed studies, the majority (n = 9) measured reading comprehension through researcher-developed probes, and two studies reported results from standardized measures.” (p.1303)

El Zein, F., Solis, M., Vaughn, S., & McCulley, L. (2014). Reading comprehension interventions for students with autism spectrum disorders: A synthesis of research. Journal of Autism and Developmental Disorders, 44(6), 1303-1322. doi: 10.1007/s10803-013-1989-2

“The validity of using standardised assessments with children with ASD is commonly queried in school contexts; however, standardised assessments can be administered validly with children with ASD (Reisinger, Steiman, Ferencz, & Sattler, 2014). Understanding the symptoms, common challenges and comorbidities associated with ASD can assist professionals in choosing appropriate assessment tools, as well as in preparing for, and conducting, an assessment in a manner that gives the best opportunity for a valid assessment. A typical assessment would include interviews with parents/caregivers, teachers, and the child (as appropriate to developmental level), observation, standardised assessment, and referral for medical/genetic/audiological examinations as indicated by observations or interview information (Reisinger et al., 2014).” (p.106)

Paynter, J. (2015). Assessment of school-aged children with autism spectrum disorder. Journal of Psychologists and Counsellors in Schools, 25(1), 104–115.

Can other educational domains areas be negatively affected?

“In a referred sample of 741 children, LD in written expression was found in 62% with ADHD and 60% with autism (Mayes & Calhoun, 2006a). Relatedly, most children with ADHD and most children with autism have dysgraphia or impaired handwriting legibility.” (p.69)

Mayes, S.D., Waschbusch, D.A., Calhoun S.L., & Mattison, R.E. (2020). Correlates of academic overachievement, nondiscrepant achievement, and learning disability in ADHD, Autism, and general population samples. Exceptionality, 28(1), 60-75. DOI: 10.1080/09362835.2020.1727324

“Meta-analysis (Finnegan & Accardo, 2018) of writing skills found handwriting of individuals with ASD is larger than the handwriting of typically developing peers. Individuals with ASD also scored lower on measures of legibility and spelling. Compared to TD peers, individuals with ASD wrote at a slower rate and wrote less. Content scores assessed on rubrics were significantly lower.” (p.74)

Finnegan, E.G. (2019). Literacy instruction for students with autism spectrum disorder in inclusive settings. DADD Online Journal, Journal of the Division on Autism and Developmental Disabilities, Council for Exceptional Children, 6(1), 72-88.

In summary, it is important to assess the emergent and early literacy skills of children with ASD - don't assume. At this stage there is no reason to believe that instructional methods that work well for children with language disorders (e.g., systematic explicit intensive approaches to phonics / phonological awareness, etc.) should not work for children with ASD. Although this answer focuses mainly on early print-related literacy skills, for children with ASD who do learn to decode, reading comprehension may still be compromised - some interesting new research is emerging and reported on in systematic reviews:

Direct Instruction has proved useful in a number of studies, as has a focus on comprehension strategy instruction.

“Children with autism spectrum disorder (ASD) often have comorbid learning difficulties in reading comprehension, an essential skill in accessing any area of the curriculum. The aim of this systematic review is to analyze the effectiveness of reading comprehension interventions in students with ASD. … After applying inclusion and exclusion criteria, a total of 25 studies were selected. The content analysis of these studies shows that when specific interventions are carried out, students with ASD are able to take advantage of the instruction they receive and compensate for difficulties. Understanding inferences and the main idea of the text are the most common reading comprehension topics, and direct instruction is the most widely-used intervention method in the reviewed studies. … The results show that a large number of studies used direct instruction, some of them as the only technique [27, 30–33, 40, 41] and others as a part of the intervention [26]. Direct instruction consists of a teaching approach based on breaking down tasks into sequences of more concrete steps with the aim that students acquire the different skills worked in sequence. It is an approach that emphasizes the structuring of the teaching processes through scripts that guide the teaching process. The results of this review confirm that, according to previous reviews [14,20], this is a positive methodology for teaching school content to children with ASD, considering that these children need individualized attention, and that this systematic methodology is particularly well adapted to the order and structuring needs of students with ASD.” (p.1, 8)

Tárraga-Mínguez, R., Gómez-Marí, I., & Sanz-Cervera, P. (2021). Interventions for improving reading comprehension in children with ASD: A systematic review. Behavioral Sciences, 11(3). https://doi.org/10.3390/ bs11010003

“As the number of students with Autism Spectrum Disorder (ASD) being prepared for statewide assessment rises, there is increased demand for effective instructional strategies to improve reading comprehension scores in these students. The authors synthesized the findings of 15 studies, which included 88 school-aged students identified with ASD. The studies were conducted between 1989 and 2015. Findings indicate that Direct Instruction (DI) and graphic organizers have positive effects, while cooperative learning, anaphoric cueing, and question generation show promise. Electronic supported text shows little to no effect on reading comprehension measures in students with ASD.” (p.187)

Finnegan, E., & Mazin, A. L. (2016). Strategies for increasing reading comprehension skills in students with autism spectrum disorder: A review of the literature. Education and Treatment of Children, 39(2), 187-219. doi: 10.1353/etc.2016.0007

“This research demonstrates that DI is a promising practice for students with ASD. … there appears to be a gap in the extant literature on using DI to teach language skills to high school students with ASD in a group format. … The purpose of this study was to determine the effectiveness of DI, and specifically the SRA Reading Mastery Signature Edition language program, in teaching high school students with ASD in a small group setting to answer ‘‘who,’’ ‘‘where,’’ and ‘‘what’’ questions. An additional purpose of this study was to determine whether any effects demonstrated during the intervention would maintain after instruction was removed. The results indicated that the DI curriculum, as modified, was effective in teaching all participants to answer ‘‘who’’ and ‘‘what’’ questions to mastery. In addition, the data revealed that the participants maintained these improvements at both the 2- and 4-week post-intervention follow-up assessments.” (p. 2969, 2976)

Cadette, J.N., Wilson C.L., Brady, M.P., Dukes, C., & Bennett, K.D. (2016). The effectiveness of Direct Instruction in teaching students with autism spectrum disorder to answer "wh-" questions. Journal of Autism and Developmental Disorders, 46(9), 2968-78.

“Several studies have been done showing the effectiveness of Direct Instruction on improving the reading comprehension skills of students with ASD (Bethune & Wood, 2013; Flores & Ganz, 2007, 2009; Ganz & Flores, 2009). Direct Instruction requires frequent, immediate corrective feedback from the teacher so can only be taught in small groups or in one-to-one settings.” (p.81)

Finnegan, E.G. (2019). Literacy instruction for students with autism spectrum disorder in inclusive settings. DADD Online Journal, 6(1), 72-88.

“DI curriculum has been used to teach language skills for young children who needed communication interventions. Researchers have shown DI improved language skills for children with developmental delays (DD) and autism spectrum disorders (ASD). Benner et al. (2002) investigated the difference between the DI program Language for Learning (LL; Engelmann & Osborn, 1999) and a traditional kindergarten curriculum. Students who received LL performed significantly better than comparison students in receptive language. Woldron-Soler, Martella, Marchand-Martella, and Tso (2002) implemented LL within an integrated preschool setting. Children with DD who received 15 weeks of instruction using LL demonstrated greater gains in receptive and expressive language skills than children who did not participate in the program. In addition, students who received LL showed increased gains in social skills. Other LL research with young children investigated variations in implementation of the program. For example, Tincani et al. (2005) compared the effects of slow-paced and fast paced teaching on the response opportunities, participation, accuracy, and off-task behavior of 4 pre-kindergarten students who were at-risk for school failure. Between the fast-paced and slow-paced instructional methods, there were significant differences between groups. The fast-paced group demonstrated four more responses per min. The fast-paced group provided three more correct responses and exhibited less off-task behavior than the slow-paced group. The groups did not differ in the percentage of academic responses. …

The current study extends the literature (e.g., Benner et al., 2002; Woldron-Soler et al., 2002; Flores et al., 2013) regarding DI for students with DD and ASD by investigating the effects of implementation of a Language for Learning program within an inclusive rural classroom setting in a manner that balanced the wide variety of diverse student characteristics, instructional learning styles, and achievement levels of students in the classroom. The researchers administered instruction in rotating stations as a way to individualize instruction based on unique student strengths and weaknesses. All students in the classroom received academic instruction, but the researchers also pulled students to receive intensive instruction based on learning needs. Students who required more intensive language interventions received DI. All students in this study made progress across all behaviors and also maintained progress after instruction ended. Teachers who provide instruction for students with significant language needs can implement instruction using DI procedures and focusing on language behaviors. Language behaviors involve teaching students to make action statements, make identity statements, answer “yes” and “no” questions, make descriptions using prepositions, make descriptions using opposites, and apply prepositions and opposites in discussion prompted by teacher questions. Interventions can occur during station teaching as a way to differentiate instruction.” (p. 3, 7)

Flores, M.M., Schweck, K.B.; Hinton, V. (2016). Teaching language skills to preschool students with developmental delays and autism spectrum disorder using Language for Learning. Rural Special Education Quarterly, 35(1), 3-12. DOI: 10.1177/875687051603500102

“Although several studies have documented strengths in word recognition for some students with autism spectrum disorder (ASD; for example, Newman et al., 2007), most investigators have concluded that a disproportionate number of students with ASD do not meet grade-level expectations in word recognition or comprehension (Asberg, Dahlgren, & Sandberg, 2008; Brown, Oram-Cardy, & Johnson, 2013; Estes, Rivera, Bryan, Cali, & Dawson, 2011; Huemer & Mann, 2010; Nation, Clarke, Wright, & Williams, 2006; Norbury & Nation, 2011; Ricketts, Jones, Happé, & Charman, 2013). …Findings of concern included frequency of use of paraprofessionals to provide primary instruction, teachers’ relatively low self-efficacy for teaching reading to students with ASD, and provision of less than the recommended instructional time for K-3 reading. … A second condition relates to instructional time and intensity. Beginning readers should be engaged in instruction for a sufficient amount of time to support progress. A common recommendation for K-3 programs is a dedicated instructional block of 90 to 120 min for all students (Allington, 2009; Foorman & Connor, 2010). In addition, students who are reading below grade level should receive more intensive instruction than other students (Allington, 2009, 2013; Griffiths & Stuart, 2013; Vaughn, Denton, & Fletcher, 2010). Instructional intensity may be enhanced by increasing instructional time and reducing group size (e.g., Mellard, McKnight, & Jordan, 2010; Vaughn et al., 2010).” (p. 337-8) … “On the positive side, teachers indicated that the vast majority of students with ASD participated in daily reading instruction and received more comprehensive instruction on the essential components of reading than the sight-word approach that has been used in the past. Of concern, though, were the findings that almost one third of students received primary instruction from a paraprofessional, a sizable percentage of teachers lacked confidence in their preparation and effectiveness in teaching reading to students with ASD, and a majority of students received less than the recommended instructional time for K-3 reading.” (p.343)

Spector, J.E., & Cavanaugh, B.J. (2015). The conditions of beginning reading instruction for students with autism spectrum disorder. Remedial and Special Education, 36(6), 337–346.

“Published instructional programs that incorporate explicit and systematic procedures in a scripted manner allow consistent implementation across instructors of varying skill levels. Scripted programs control instructional delivery, increasing fidelity of implementation (Cooke et al. 2011). According to Watkins and Slocum (2004), scripts accomplish two goals: 1. To assure that students access instruction that is extremely well designed from the analysis of the content to the specific wording of explanations, and 2. To relieve teachers of the responsibility for designing, field-testing, and refining instruction in every subject that they teach. (p. 42) Importantly, Cooke et al. (2011) compared scripted to nonscripted explicit instruction and found increased rates of on-task instructional opportunities during scripted instruction. Additionally, students indicated they enjoyed answering together (i.e., in unison) and instructors shared positive outcomes including greater student attention, consistent routine, and reduced likelihood of leaving out crucial concepts.” (p.56)

Plavnick, J., Marchand-Martella, N., Martella, R., Thompson, J., & Wood, A. L. (2015). A review of explicit and systematic scripted instructional programs for students with autism spectrum disorder. Review Journal of Autism and Developmental Disorders, 2, 55-66. doi:10.1007/s40489-014-0036-3.

“The Reading Mastery curriculum in particular has a powerful evidence base for its effectiveness with disadvantaged children, English Language Learners, and children with disabilities (Engelmann 1997; Gersten et al.1987; Kamps and Greenwood 2005; Kamps et al. 2008), but limited studies specifically targeting children with ASD. … Findings support the use of explicit and Direct Instruction curricula for high risk children who are struggling academically (Kame’enui and Simmons 2001; Kamps et al. 2008); and more specifically children with ASD at risk for learning problems (El Zein et al. 2014; Flores and Ganz 2009; Ganz and Flores 2009; Plavnick et al. 2014, 2016). Findings also support the use of the Reading Mastery curriculum to teach children with ASD basic phonemic awareness, decoding skills and word reading (Plavnick et al. 2016; Spector and Cavanaugh 2015).”

Kamps, D, Heitzman-Powell, L, Schwartz, I., Mason, R., Swinburne Romine, R., & Fleming, K. (2016). Effects of Reading Mastery as a small group intervention for young children with ASD. Journal of Developmental Physical Disabilities, 28, 703-722. DOI 10.1007/s10882-016-9503-3

“The results of this study also confirm the findings of previous research which has indicated that DI is an effective methodology for diverse groups of students, including those from low socioeconomic backgrounds (Goldman, 2000; Torgesen, Alexander, Wagner, Rashotte, Voeller, & Conway, 2001), students at-risk for academic failure (Carlson & Francis, 2002; Foorman, Francis, Fletcher, & Schatschneider, 1998; Frederick, Keel, & Neel, 2002; Grossen, 2004; Shippen, Houchins, Steventon, & Sartor, 2005), students with learning disabilities (Swanson, 1998; Torgesen et al.), and students with cognitive deficits (Bradford, Shippen, Alberto, Houchins, & Flores, 2006; Flores, Shippen, Alberto & Crowe, 2004; Gersten & Maggs, 1982).” (p.94) … Considering the success of the participants in this study as well as the overwhelming evidence of the efficacy of DI programs for a variety of individuals as well as emerging evidence for those with autism, it is worthwhile to explore and explain factors that most likely contributed to the efficacy of this program for individuals in this study. Programs developed from behavioral theory are perhaps the most effective for those with autism. For example, applied behavior analysis is generally regarded as the treatment of choice for individuals with autism since Lovaas’ seminal study in 1987. Since this time, significant research and litigation have been devoted to this type of therapy. DI is a specific set of academic curricula that is rooted in behavioral theory and has similarities to that of ABA. Research has supported that specific components which contribute to the efficacy of these programs is that they both focus on measurable behaviors and provide carefully designed instruction (Knight et al., 2013) which includes predictable instructional formats (Hume et al., 2012) with high rates of responding (Lamella & Tincani, 2012) and immediate feedback (Ranick, et al., 2013).” (p.95-96)

Head, C. (2016). The effects of Direct Instruction on reading comprehension for individuals with autism or intellectual disability. A dissertation submitted to the Graduate Faculty of Auburn University in partial fulfilment of the requirements for the Degree of Doctor of Philosophy Auburn, Alabama August 6, 2016. Retrieved from https://etd.auburn.edu/bitstream/handle/10415/5272/FINAL_DISS.pdf?sequence=2&isAllowed=y

“Rigorous studies included in the current review indicate that comprehensive NRP instruction is effective in improving reading outcomes when administered to relatively diverse groups of children with ASD. … We conducted a systematic review of the literature on reading instruction for children with ASD, following the recommendations of the National Reading Panel (NICHD, 2000). Our study provides an updated review for the years 2009–2017 along with an analysis of effect sizes and research quality using the Evaluative Method for Determining Evidence-Based Practices in Autism (Reichow et al. 2008). The 19 studies that met our inclusion criteria reported gains in phonics, reading accuracy, reading fluency, and/or reading comprehension skills. … One high-quality study investigated multi-component NRP [National Reading Panel] instruction as applied to a relatively large, diverse sample (Kamps et al. 2016). … Literacy instruction was delivered using a commercially available program [Reading Mastery] designed to target phonemic awareness, phonics, reading fluency, and reading comprehension skills. Over an extended period of 2 years, children who received instruction targeting these skills exhibited statistically significant, large gains in reading accuracy as compared to children in a control group. … Comprehensive literacy instruction encompassing all of the NRP Big Five was the focus of one adequate-quality study (Bailey et al. 2017). Similar to Kamps et al. (2016), participants in this study were required to meet relatively broad inclusion criteria: 5 to 12 years of age, confirmed diagnosis of ASD, no hearing or vision impairments, measurable language abilities, and ability to sustain attention to task for 15 min. Results showed that participants who received comprehensive NRP instruction achieved statistically significant gains in word and passage reading accuracy and comprehension relative to children in a control group, with each of these gains associated with a large effect size.4 This suggests that fully implemented (comprehensive) NRP instruction may be effective in promoting reading accuracy and reading comprehension skills for school-aged children with ASD. … Only comprehensive instruction incorporating a focus on all of the NRP Big Five was effective in improving both reading accuracy and comprehension skills in a diverse sample of children with ASD. Based on these adequate and high quality studies, we recommend that professionals consider using comprehensive NRP instruction incorporating phonemic awareness, phonics, vocabulary, reading fluency, and reading comprehension strategies when working with children with ASD.” (p.18, 19)

Bailey, B., & Arciuli, J. (2020). Reading instruction for children with autism spectrum disorders: A systematic review and quality analysis. Review Journal of Autism and Developmental Disorders, 7, 127–150. https://doi.org/10.1007/s40489-019-00185-8

“This study further demonstrates that students with ASD and DD can benefit from group instruction. One-on-one instruction in the form of discrete trial teaching represents the largest body of intervention research for this population (National Research Council, 2001). However, students in the current study successfully participated in DI which required sustained attention, frequent responding, and choral responses in a group format. This is significant since group instruction may provide for greater efficiency in meeting students’ needs in diverse classrooms. In addition, providing instruction to students with ASD and DD in a group format may also better prepare them for participation in group situations within general education classrooms” (p.46-7).

Flores, M. M., Nelson, C., Hinton, V., Franklin, T. M., Strozier, S. D., Terry, L., & Franklin, S. (2013). Teaching reading comprehension and language skills to students with autism spectrum disorders and developmental disabilities using Direct Instruction. Education and Training in Autism and Developmental Disabilities, 48(1), 41-48.

“Research shows that evidence-based practices have significant benefits for individuals with ASD [16]; and such practices are required by law [10]. However, there are many factors that influence the use of EBPs in schools, including the varying abilities and symptoms of individuals with ASD, limited ASD-specific training for teachers in public schools, and the large number of available treatment options, paired with limited large-scale reports on the effectiveness of such interventions. (p.2) … The five most highly reported academic practices were structured teaching (68%), direct instruction (61%), applied behavior analysis (59%), naturalistic teaching (51%) and TEACCH (50%)”. (p.6)

Ferreri, S.J., Witmer, S.E., & Shivers, C.M. (2016). Autism spectrum disorders and evidence based practices: A statewide exploration of public school programming. Austin Journal of Autism & Related Disabilities, 2(2), 1018. https://austinpublishinggroup.com/autism/fulltext/autism-v2-id1018.php

“Little research has been conducted reporting the effects of DI on language development. … This literature, though sparse, suggests DI is a promising practice, particularly for students who do not easily learn language skills incidentally, such as those with ASD. Direct Instruction, as noted above, is particularly suited for use with individuals with ASD who lack a considerable amount of common language concepts and who require intensive, explicit instruction to learn such skills. DI interventions have resulted in improvements in reading skills in children with such deficits. Specifically, DI has positively affected reading decoding (Fredrick et al. 2002; Shippen et al. 2005) and reading comprehension (Carlson and Francis 2002; Flores and Ganz 2007). DI has improved reading skills in children from elementary (Carlson and Francis 2002; Humphries et al. 2005) to middle school (Grossen 2004; Shippen et al. 2005). Additionally, DI has been used successfully with children with a variety of abilities, including autism (Flores and Ganz 2007), epilepsy (Humphries et al. 2005), learning disabilities and cognitive impairments (Carlson and Francis 2002), those with limited English proficiency (Carlson and Francis 2002), and students at risk (Carlson and Francis 2002; Grossen 2004).” (p.76) … The purpose of this study was to extend the research on the use of DI to the remediation of oral language skills in elementary children with ASD. … The students’ increases in expressive language skills are consistent with previous research regarding students with developmental delays (Waldron-Soler et al. 2002) and students with epilepsy and academic deficits (Humphries et al. 2005). However, this study extends the line of research in include students with ASD. Furthermore, the students in the current study maintained their performance after instruction ceased.” (p. 81)

Ganz, J.B., & Flores, M.M. (2009). The effectiveness of Direct Instruction for teaching language to children with autism spectrum disorders: identifying materials. Journal of Autism and Developmental Disorders, 39, 75–83.

“The current investigation builds upon prior research by evaluating the effectiveness of the complete DI Language for Learning curriculum for teaching language skills to children diagnosed with ASD during a one-to-one teaching arrangement.” (p.45) … Both statistical analyses and visual inspection of the data provides evidence that the Language for Learning curriculum is associated with an increase in responding to language. … Analysis of each group suggests that an increase in each participant’s language skills occurred following the implementation of the DI intervention. For each group, the percentage of correct responses immediately post-intervention was significantly higher than pre-intervention.” (p. 51-52)

Shillingsburg, M.A., Bowen, C.N., Peterman, R.K., & Gayman, M.D. (2015). Effectiveness of the Direct Instruction Language for Learning curriculum among children diagnosed with Autism Spectrum Disorder. Focus on Autism and Other Developmental Disabilities, 30(1), 44–56.

What’s happening about reading and non-verbal students with ASD?

“Although, generally there is a lack of research relating to the nonverbal ASD population, it is not known whether this cohort are very likely to fall into the ‘low functioning’ category of ASD . However, ‘low functioning’ is a common term for those children on the ASD spectrum who are identified as having poor language and cognitive abilities (O’Connor and Klein, 2004b). In the UK, children with ASD who fit into this broad category of ‘low functioning’ are likely to be educated in settings which form part of schools providing additional learning needs (ALN) education (Reed and Osbourne, 2014). Picture Exchange Communication Systems (Frost & Bondy 2002) along with other forms of alternative augmentative education are commonly used in ALN settings to support the communication skills of nonverbal and minimally verbal students. The results of the current study therefore have implications for such settings, as they would imply that there could be children who are able to read and comprehend to at least a single word level, who are being supported by the use of picture and/or symbol-based systems for the purposes of communication. Therefore limiting, rather than exploiting the potential for more advanced forms of communication to develop. … Further implications of the study are also clear in that not every child or young person with ASD who is nonverbal will lack the ability to recognise printed and/or understand their meaning. This means that many nonverbal children who are on the autism spectrum may have the beginnings of a reading skill which is currently undetected. Verbalisation is a common element of reading tests being used in ALN settings (Arnold & Reed, 2016b), by removing this element, the digital format of assessment used in this study promotes a form of assessment that not only measures the reading ages of nonverbal children, but also allows for comparison with their verbal cohorts. What schools choose to measure can be a reflection of what they choose to value. Assessment data forms part of school self-evaluation which informs the plans for school improvement. The school improvement plan will set out how resources are allocated, and which interventions are employed. Therefore, nonverbal ASD students who are not represented in the data, will also be prone to exclusion from more advanced forms of reading instruction and communication intervention. This is a crucial matter for the field of special education, as unless reasonable adjustments are made, nonverbal children and young people with ASD will continue to be excluded from interventions which could improve their chances of being successful readers and communicators in future. In which case they are likely to remain, as Tager-Flusberg (2013b) argue ‘the neglected end of the spectrum’.” (p. 17-19)

Arnold, S., & Reed, P. (2020. Measuring-the-comprehension-abilities-of-children-who-are-both-verbal-and-nonverbal. Pre-Print Jan 2020. https://www.researchgate.net/profile/Sharon-Arnold/publication/340129061_Measuring_the_comprehension_abilities_of_children_who_are_both_verbal_and_nonverbal_with_ASD_Extending_the_analysis_of_a_novel_digital_test_format/links/5e7a2269a6fdcc5499566616/Measuring-the-comprehension-abilities-of-children-who-are-both-verbal-and-nonverbal-with-ASD-Extending-the-analysis-of-a-novel-digital-test-format.pdf

“Keefe and Copeland (2011) argued that the belief that some individuals cannot acquire literacy skills can then lead to individuals being denied opportunities to acquire these skills. Mirenda (2003) also highlighted this issue and argued that students with ASD who have cognitive impairments may be excluded from literacy instruction due to mistaken beliefs that they do not have the capacity for acquiring literacy skills, yet show skills that are directly related to literacy learning such as interest in books, print awareness, and recognition of sight words. Mirenda advocated abandoning a “readiness” model and the assumption that spoken language was needed to benefit from instruction, and instead suggested a need for the use of multiple strategies formulated at the child’s level of literacy development, underpinned by assessment of the child’s strengths and needs. Several studies have demonstrated that children who have limited verbal communication skills can, and do, develop language and literacy skills when they are provided with high-quality literacy learning opportunities (e.g., Afacan et al., 2018; Allor et al., 2010; Erickson et al., 1997). These findings are consistent with the view that every child sits somewhere on a literacy learning continuum (Erickson, 2000), and that no child is “too anything” to learn to read and write (Yoder, 2001, p. 5). To better understand each child’s strengths and challenges in literacy-related skills, indepth assessment is required to help guide individualized literacy instruction.” (p.167)

Clendon, S., Paynter, J., Walker, S., Bowen, R., & Westerveld, M.F. (2021). Emergent literacy assessment in children with autism spectrum disorder who have limited verbal communication skills: A tutorial. Language, Speech, and Hearing Services in Schools, 52, 165–180.

Some other areas of research emphasise choosing interventions with:

• evidence of effectiveness,
• that address student self-management strategies, and
• maths interventions

“Identifying effective interventions to use with children who have ASD can be challenging for educators and parents alike, especially when various fads and “quick-fix” solutions may receive as much if not more press than evidence-based approaches. The current emphasis on implementing evidence based interventions leads educators and parents to seek out programs supported by data from empirical research. Although there is a growing body of quality research available on effective interventions for children with ASD, it is still fairly limited, especially given the increasing prevalence rates and wide range of educational, verbal, and social skill deficits associated with this disability.” (p.101)

Ryan, J.B., Hughes, E., Katsiyannis, A., McDaniel, M., & Sprinkle, C. (2014). Research-based educational practices for students with autism spectrum disorders. Teaching Exceptional Children, 47(2), 94–102.

“A recent review conducted by Root et al. (2017) concluded that CAI was an evidence-based practice for teaching academic content to students with autism spectrum disorders (ASD). Although the majority of the included studies addressed 130 literacy instruction (e.g., sight words reading, comprehension) to students with ASD, only a few specifically assessed using CAI to teach phonics and decoding (e.g., Travers et al., 2011; Whalen et al., 2010). Travers et al. (2011) compared teacher-led instruction on alphabet skills to an author-developed CAI program. The CAI program utilized discrete trial teaching and errorless learning in 10 minute lessons. Both interventions were effective in improving preschoolers’ alphabet skills. Whalen et al. (2010) used TeachTown: Basics (TeachTown Inc., 2016) with PreK-1st grade students with ASD for three months. TeachTown: Basics utilizes Applied Behavior Analysis principles to teach a wide range of early learning skills. Students in the intervention group showed improved skills in language and basic academic skills (including reading) compared to the control group, who received business-as-usual instruction.” (p. 130-131)

Snyder, S.M. (2020). An investigation of computer assisted reading instruction to teach phonics skills to young students with developmental disabilities. DADD Online Journal, Journal of the Division on Autism and Developmental Disabilities, Council for Exceptional Children, 7(1), 130-143.

“Most intervention research with school-age children with ASD has rightly examined the effectiveness of strategies aimed at improving social communication (Chang and Locke 2016; Watkins et al. 2015) and play (Kossyvaki and Papoudi 2016). However, a growing emphasis on ensuring access to the general education curriculum and improving post-school outcomes related to employment, higher education, and independent living necessitates both the use of effective intervention in schools to improve functional academic skills for this population and further research in this area (Wehman et al. 2014). … Four different areas of skills were targeted in literacy: (a) emergent literacy (i.e., letter identification), (b) phonics and fluency (i.e., word recognition, fluency), (c) reading comprehension (i.e., inferential skills), and (d) writing (i.e., composition, spelling). … The mean score across all the studies was high (M Tau-U = 0.78), but ranged from weak to very high with scores between 0.15 and 1.00. Regarding practices with some evidence, all interventions proved to have high to very high effectiveness. These interventions were self-regulated strategy development (Tau-U = 0.90), TouchMath (Tau-U = 0.87), direct instruction (Tau-U = 0.83), and test-taking instruction (Tau-U = 0.83). … ” (p. 311, 319, 320)

Alresheed, F., Machalicek, W., Sanford, A., & Bano, C. (2018). Academic and related skills interventions for autism: A 20-year systematic review of single-case research. Review Journal of Autism and Developmental Disorders, 5(4), 31-326.

“The MTSS model offers a flexible structure for teachers, IEP teams, and schools for delivering high quality instruction, research based practices, and effective support. The academic supports described above can be used in combination with behavioral supports (Leach, 2018). Many of the supports described will be beneficial to students who do not have ASD, which facilitates flexible grouping arrangements that are often necessary in GE classrooms. Teachers can group students according to need rather than disability category.” (p.82)

Finnegan, E.G. (2019). Literacy instruction for students with autism spectrum disorder in inclusive settings. DADD Online Journal, Journal of the Division on Autism and Developmental Disabilities, Council for Exceptional Children, 6(1), 72-88.

“Literacy skills in ASD are an important topic worthy of further attention. At present there are significant gaps in the literature describing the acquisition, development, and effective interventions for reading in children with ASD. We know that many children with ASD will encounter difficulties with literacy, and areas of strength (e.g., decoding), need (e.g., oral language impairment), or assumed “learning styles” can lead to unhelpful assumptions. As a result, speech pathology intervention may neglect to incorporate literacy goals tailored to meet an individual child’s learning profile. Until we have further evidence, we must draw upon the evidence-based practice frameworks by using the best available evidence combined with clinical reasoning and judgement (Hoffmann, Bennett, & Del Mar, 2013). The best available evidence at present includes an extensive literature base on typical development and language impaired populations (e.g., Catts, Herrera, Nielsen, & Bridges, 2015). This knowledge can be interpreted in conjunction with ASD knowledge and assessment of the individual child to formulate appropriate interventions that include literacy related goals and activities (see Lanter & Watson, 2008, for further recommendations).” (p.82)

Westerveld, M. F., Paynter, J., & Trembath, D. (2016). Reading instruction for children with ASD: Getting the story straight. Journal of Clinical Practice in Speech-Language Pathology, 18, 80-83.

“Many of the evidence-practices in special education have their beginnings in applied behavior analysis. For example, one prominent application of ABA in schools is Response to Intervention (RtI), which is a widely used, decision-making framework for preventing and addressing a variety of academic and behavioral challenges (Tilly, 2008). RtI shares key elements of ABA including direct measurement of behavior, interventions designed to produce significant improvements, and ongoing progress monitoring to assess acquisition, maintenance, and generalization of target skills (Fuchs & Fuchs, 2006). Other examples of techniques in use that are ABA rooted include examination of data to make individualized changes in intervention, functional behavioral assessment, and direct instruction methods. Therefore, it is logical and appropriate to seeks ways to formally embed ABA-based approaches into existing programming to benefit students and their teachers. Other examples of techniques in use that are ABA-rooted and have good classroom application include peer-mediated instruction, visual schedules, and priming.” (p.110)

Barnett, J.H., Zucker, S.H., & More, C. (2020). Applied behavior analysis in today’s schools: an imperative for serving students with autism spectrum disorder. DADD Online Journal, Journal of the Division on Autism and Developmental Disabilities, Council for Exceptional Children, 7(1), 108-117.

“The application of self-management procedures to academic behaviors has been identified as a gap in the published literature (Lee et al., 2007); however, since then, seven studies have been published targeting academic behaviors, such as a student’s ability to stay on task or improve the quality or volume of academic work. Findings of this review have indicated that self-management was highly effective for academic behaviors.” (p. 39)

Carr, M.E., Moore, D.W., & Anderson, A. (2014). Self-management interventions on students with Autism: A meta-analysis of single-subject research. Exceptional Children, 81(1), 28–44.

“In this study, we conducted a multilevel meta-analysis to determine whether the self-regulated strategy development (SRSD) approach to teaching writing to students with autism spectrum disorder (ASD) improves significantly the number of words written and overall quality of writing, whether the effects of SRSD were consistent or variable across studies, and whether the moderator of age could explain the potential variability in the number of words written and overall quality of writing. Results indicated that SRSD had large, statistically significant and meaningful effects on the number of words written and overall quality of writing.” (p.1)

Asaro-Saddler, K., Moeyaert, M., Xu, X., & Yerden, X. (2020). Multilevel meta-analysis of the effectiveness of self-regulated strategy development in writing for children with ASD. Exceptionality, 1-17. DOI: 10.1080/09362835.2020.1850457

“The purpose of the current meta-analysis was to investigate the effectiveness of self-regulated strategy development (SRSD) reading interventions for students with disabilities in school settings. We used the Council for Exceptional Children’s Standards for Evidence-Based Practices in Special Education (CEC-EBP) to evaluate experimental investigations that targeted reading comprehension using an SRSD reading intervention and included students with disabilities. Summary outcome measures presented in the analysis include the between-case standardized mean difference, percentage of non-overlapping data, and visual analysis. Although the results indicated SRSD to be generally effective, the small number of studies and the fact that only 2 studies met all of the CEC-EBP quality indicators prevent the strategy from presently being considered evidence based.” (p.1)

Sanders, S., Losinski, M., Ennis, R.P., White, W., Teagarden, J., & Lane, J. (2019). A meta-analysis of self-regulated strategy development reading interventions to improve the reading comprehension of students with disabilities. Reading & Writing Quarterly, 35(4), 339-353. DOI: 10.1080/10573569.2018.1545616

“Regardless of its limitations, research regarding mathematics instruction for students with ASD does provide some guidance for practitioners. Explicit instruction consisting of prompts and supplemented with positive consequences remains the standard for addressing the needs of students with disabilities (Browder et al., 2008). Instruction enhanced with video modeling, computer equipment, and peer tutoring—though promising—is relatively absent from the literature. Practitioners may refrain from using techniques that strain resources in favor of simpler, validated forms of instruction. The few studies involving word problems suggest that students with ASD are amenable to instruction in these areas.” (p. 458)

King, S.A., Lemons, C.J., & Davidson, K.A. (2016). Math interventions for students with Autism Spectrum Disorder: A best-evidence synthesis. Exceptional Children, 82(4), 443–462.

How important is early identification and intervention?

University of California - San Diego. (2019, April 29). Autism diagnoses prove highly stable as early as 14 months: Finding suggests earlier, effective identification can result in earlier, more effective treatment. ScienceDaily. www.sciencedaily.com/releases/2019/04/190429111803.htm

Pierce, K., Gazestani, V.H., Bacon, E., et al. (2020). Evaluation of the diagnostic stability of the early autism spectrum disorder phenotype in the general population starting at 12 months. JAMA Pediatrics, 2019 DOI: 10.1001/jamapediatrics.2019.0624

Elsevier. (2020, August 11). Early neural activity associated with autism: EEG measurements in infants predicted ASD symptoms in toddlers. ScienceDaily. www.sciencedaily.com/releases/2020/08/200811120144.htm

Dickinson, A., Daniel, M., Marin, A., Gaonkar, B., Dapretto, M., McDonald, N.M., & Jeste, S. (2020). Multivariate neural connectivity patterns in early infancy predict later autism symptoms. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, S2451-9022(20), 30140-3. DOI: 10.1016/j.bpsc.2020.06.003

“Early and effective intervention: Clinicians should respond appropriately to family or clinical concerns and results of screening to avoid delays in diagnosis and treatment. Intervention for the communicative, adaptive, and behavioral deficits associated with ASD should take place as soon as the need becomes evident. Intervention is most effective if it is early, intense, and involves the family. Research has demonstrated that interventions using principles of behavioral intervention are associated with skill acquisition and improved outcome. There is evidence that training parents to support developmental skill building is helpful. Primary care providers should help families learn to interpret evidence about interventions so they can make informed decisions about their child’s care. Many interventions, including many nutritional interventions, do not have evidence to support their use at this time. Families should be referred to community support resources and be included in the shared decision-making process.” (p.2)

Hyman, S.L., Levy, S.E., Myers, S.M., AAP Council on Children with Disabilities, Section on Developmental and Behavioral Pediatrics. (2020). Executive Summary: Identification, evaluation, and management of children with Autism Spectrum Disorder. Pediatrics, 145(1), e20193448

“Research investigating the emergent literacy skills of children on the spectrum during the preschool period has shown particular challenges in meaning-related skills (e.g. vocabulary and story retelling and comprehension) and relative strengths in print-related skills, including alphabet knowledge (Davidson and Ellis Weismer, 2014; Fleury and Hugh, 2018; Lanter et al., 2012; Westerveld and Roberts, 2017; Westerveld et al., 2017). While these uneven emergent literacy profiles may be related to children’s language abilities and/or cognitive skills (Westerveld et al., 2020b), emerging longitudinal research has confirmed the importance of these precursor literacy skills to future reading performance (Davidson and Ellis Weismer, 2014; Dynia et al., 2017; Westerveld et al., 2018), reinforcing the importance of early intervention.” (p. 2)

Westerveld, M. F., Wicks, R., & Paynter, J. (2021). Investigating the effectiveness of parent-implemented shared book reading intervention for preschoolers with ASD. Child Language Teaching and Therapy, 0265659021995522.

“Early intensive behavioral interventions as the mainstay for treatment has been shown to help young children with ASD gain skills and improve long-term outcomes (30). The gold standard treatment is Applied Behavior Analysis (30).” (p.72)

Chahin, S.S., Apple, R.W., Kuo, K.H., & Dickson, C.A. (2020). Autism spectrum disorder: Psychological and functional assessment, and behavioral treatment approaches. Translational Pediatrics (Neurodevelopmental and Neurobehavioral Disorders in Children), 9(1), S66-S75.

“The results of this review would seem to suggest that teaching staff might be able to learn how to effectively deliver early intervention, with a reasonable degree of fidelity, to young children with ASD in inclusive preschool environments. Further, the delivery of early intervention in these settings may improve outcomes for the participating children. However, many of the reviewed studies had minimally acceptable levels of quality based on the Goldstein et al. (2014) rating framework. Given the need for high-quality studies to guide evidence-based practice, the results of this review point to the need for additional and higher-quality studies. At the present time, any statements regarding the effectiveness of the early interventions included in this review must be viewed as tentative. Although these results suggest that a range of early intervention programs can be effective when implemented in inclusive preschool settings, further research is needed to establish the generality of the findings of this review. Specifically, there is a need for more high-quality studies that evaluate the long-term effectiveness of interventions and the long-term maintenance of both child and teacher outcomes.” (p.19)

Tupou, J., van der Meer, L., Waddington, H., & Sigafoos, J. (2019). Preschool interventions for children with autism spectrum disorder: A review of effectiveness studies. Review Journal of Autism and Developmental Disorders. Online First. https://doi.org/10.1007/s40489-019-00170-1

How well prepared are teachers to employ evidence-based literacy instruction with this cohort?

“Misconceptions about the brain and its relation to education are widespread. This can lead to the implementation of ineffective methods and the waste of precious resources. To examine the extent of belief in neuromyths, a survey about the brain in education was conducted. Respondents (n = 169) came from special education (n = 83) and general education (n = 78), and included preservice teachers (n = 34), in-service teachers (n = 63), higher education faculty (n = 39), and educational leaders (n = 33). The survey contained 15 Myths and 18 Facts, and overall, participants were able to correctly identify approximately 66% of all the Facts. On the other hand, on average, respondents responded correctly for only one third of the Myths. The most commonly misidentified Myths were related to motor coordination exercises to improve literacy skills, the right brain-left brain myth, and learning styles.” (p.16)

van Dijk, W., & Lane, H.B. (2020). The brain and the US education system: Perpetuation of neuromyths. Exceptionality, 28(1), 16-29. DOI: 10.1080/09362835.2018.1480954

“Less than half (38%) of Australian teachers feel prepared to teach students with special needs when they finish their formal training. This is despite 74% having trained to teach in mixed-ability settings as part of their studies. The latest Teaching and Learning International Survey (TALIS) shows teachers across the OECD felt professional development opportunities were particularly inadequate for teaching students with special needs. … According to the TALIS report, nearly 30% of teachers in Australia work in classes where at least 10% of students have special needs. The report adds to a body of research suggesting teachers feel unprepared to teach students with special needs in mixed-ability classrooms. … Depending on the data source, between 8% and 20% of school-age children have identified disabilities or special educational needs.”

Jarvis, J. (2019). Most Australian teachers feel unprepared to teach students with special needs. The Conversation, June 26. Retrieved from https://theconversation.com/most-australian-teachers-feel-unprepared-to-teach-students-with-special-needs-119227

“ … Washburn, Binks-Cantrell, Joshi, Martin-Chang, and Arrow (2016) found preservice teachers from Canada, England, New Zealand and the USA lacked knowledge of the component skills required for effective reading instruction. … [In Australia] it would appear that fewer than half of the coordinators for whom information was available had specific qualifications, publications, research interests or expertise related to early reading instruction. A similar observation was made in a NSW Government report investigating the quality of initial teacher education (BOSTES, 2014). This finding is of concern because the percentage of faculty members with advanced degrees has been identified as one of the contributing factors to the quality of teacher preparation programs (Feuer et al., 2013; Ingvarson et al., 2014) and, in much the same way that classroom teacher quality affects student achievement, it can be argued that teacher educator quality will affect teacher performance. In addition, the work of Joshi et al. (2009) and Washburn, Joshi, and Hougen (2012) showed that teacher educators themselves may have poor linguistic knowledge and this may be reflected in lack of knowledge of the pre-service teachers they work with. The apparent lack of expertise in early reading of some unit co-ordinators may thus be a contributor to poorer quality teacher education.” (p. 3, 13)

Meeks, L., & Stephenson, J. (2020). Australian preservice teachers and early reading instruction. Australian Journal of Learning Difficulties, 25, 65–82. DOI: 10.1080/19404158.2020.1743730

“Importantly, teachers and clinicians do not always employ research-based reading instruction methods when working with children with autism (Accardo & Finnegan, 2019). This may be due, in part, to a tendency for children with autism to be underestimated in terms of their ability to learn how to read and ties in with pseudoscientific theories about the underlying causes and effective treatment of reading difficulties (Griffiths et al., 2016; Mirenda, 2003; Wheldall & Beaman, 2000).” (p.226)

Arciuli, J., & Bailey, B. (2021). The promise of comprehensive early reading instruction for children with autism and recommendations for future directions. Language, Speech and Hearing Services in Schools, 52(1), 225-238.

“EBPs [Evidence-Based Practices ] are only effective if, and when implemented. Although teachers in this and other studies report high-frequency use of some EBPs, they report limited familiarity with and use of others (Brock et al., 2019; McNeill, 2020). Because students with ASD are not making adequate progress in their social communication development (Brock et al., 2019), focusing attention on how to support ECSE [Early Childhood Special Education ] teachers' implementation of key EBPs that are infrequently used but require minimal resources, may reduce the implementation gap. ECSE teachers must have multiple "tools" in their toolbox (Kasari & Smith, 2013), yet this study suggests that ECSE teachers' toolboxes are dependent on individual factors above and beyond the evidence-base of any given practice. Just as teachers should consider student and contextual fit of interventions, professional development providers and implementation researchers should explore tailoring their implementation supports to individual teachers based on their beliefs (Cook, 2020; Fishman et al., 2018). By doing so, teachers will be motivated to use effective interventions for young children with ASD to cultivate the skills that help them access the opportunities and activities they deserve (Goldstein et al., 1992).” (p.153-154)

Hugh, M.L. (2020). Exploring determinants of early childhood special educators' practice selections for young children with autism spectrum disorder. A dissertation submitted to the Faculty of the University of Minnesota in partial fulfilment of the requirements for the degree of Doctor of Philosophy. https://conservancy.umn.edu/bitstream/handle/11299/216385/Hugh_umn_0130E_21470.pdf?sequence=1&isAllowed=y

“The U.S. Department of Education (USDE, 2014) reported that more than 5.8 million children, or 8.4% of the total student population between the ages of 2 and 6, received services under IDEA Part B in 2012 (IDEA, 2004). Of these students receiving special education services, 40% were classified as having specific learning disabilities, 18% had speech or language impairments, 7% were diagnosed as having autism, and 7% were classified as having intellectual disabilities, with the remaining students falling into the categories of other health impairments, emotional disturbances, and all other disabilities combined (USDE, 2014). Despite the fact that federal legislation has required the use of teaching strategies that are evidence based (IDEA, 2004; Morrier, Hess, & Heflin, 2011), service delivery professionals do not consistently apply evidence-based strategies with students receiving special education services (Hess, Morrier, Heflin, & Ivey, 2008; Schreck & Mazur, 2008). While evidence-based practice has been an integral part of medicine since the beginning of the 20th century (Bernard, 1957), reliance on scientific evidence for selecting appropriate educational interventions has not kept pace with other health-related services (Vyse, 2005). For a variety of cultural, fiduciary, logistical, and educational reasons, there is a gap between the IDEA requirements to use empirically based teaching strategies and their actual implementation by educators and service delivery professionals (Fixsen & Blasé, 1993; Neef, 1995; Odom, Bratlinger, Gersten, Horner, Thompson, & Harris, 2005; Page, Iwata, & Reid, 1982; Shreck & Mazur, 2008).”

Zane, T., Weiss, M.J., Blanco, S., & Otte, L. (2015). Fads in special education. In Richard M. Foxx and James A. Mulick (Eds). Controversial therapies for autism and intellectual disabilities: Fad, fashion, and science in professional practice (2nd. ed). Ch 8, New York, Routledge.

Parent views on school support

“Many children on the autism spectrum struggle in their reading development. This study investigated parents’ views of challenges and facilitators to literacy learning at home and at school in children on the autism spectrum who were in their first year of schooling. Thematic analysis of semi-structured interviews with 37 parents revealed parents’ in-depth knowledge of their child’s strengths and interests, which they utilised to engage their child in literacy learning activities at home. Parents raised concerns about the support their children were receiving at school, with many describing challenges with teacher understanding of autism spectrum disorders, limited adaptation of the curriculum to suit the child’s learning needs and poor communication between school and home. The study challenges schools and educators to review and refine current practices to ensure individualised, learner-focused and inclusive pedagogies and practices to better support children on the autism spectrum.” (p.1)

O’Leary, K., Fluckiger, B., Paynter, J. & Westerveld, M. (2019). Parent perceptions of literacy learning of their young children on the autism spectrum in their first year of schooling. Australian Journal of Education, Early Online. doi: 10.1177/0004944119860639

So, what changes might we see in the future?

Earlier diagnosis made available through novel means?

Elsevier. (2020, August 11). Early neural activity associated with autism: EEG measurements in infants predicted ASD symptoms in toddlers. ScienceDaily. www.sciencedaily.com/releases/2020/08/200811120144.htm

Dickinson, A., Daniel, M., Marin, A., Gaonkar, B., Dapretto, M., McDonald, N.M., & Jeste, S. (2020). Multivariate neural connectivity patterns in early infancy predict later autism symptoms. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, S2451-9022(20), 30140-3. DOI: 10.1016/j.bpsc.2020.06.003

Leading to earlier intervention - as noted by Pierce et al. (2020)?

Northwestern University. (2020, August 11). AI-enhanced precision medicine identifies novel autism subtype: Tool lays groundwork for autism early diagnosis and intervention. ScienceDaily. Retrieved September 20, 2020 from www.sciencedaily.com/releases/2020/08/200811153921.htm

Luo, Y., Eran, A., Palmer, N., Avillach, P., Levy-Moonshine, A., Szolovits, P., & Kohane, I.S. (2020). A multidimensional precision medicine approach identifies an autism subtype characterized by dyslipidemia. Nature Medicine, 26(9), 1375-1379.

A closer link between research and practice to ensure children with ASD make the best possible start to their lives?

One can hope!

Dr Kerry Hempenstall, Senior Industry Fellow, School of Education, RMIT University, Melbourne, Australia.
Each of my articles is available as a PDF at https://tinyurl.com/y6vat4ut

Is teaching handwriting worth the trouble these days? It’s so old school. Next, they’ll be reintroducing writing on slates with chalk as was done in the middle of the last century. Who handwrites letters these days? It’s all keyboards. Kids are into tablets from Prep (kinder). So, it’s tempting to assert that all you need to teach kids is how to be a fluent keyboardist.

But wait. What if during the learning to read stage, the physical act of writing, rather than simply hitting a computer key, is more beneficial to early reading and spelling progress? Suppose it helps in somehow cementing letter-sound knowledge – an important early indicator of reading progress. That would be valuable enough for this focus to be. important. However, the act of handwriting appears to play a part in establishing a variety of writing skills, including spelling.

That is not to diminish the importance of learning keyboard skills as students’ writing development continues. Writing via keyboard has its own advantages  – ready editing, no white out tape needed, correction for many spelling and grammar errors (though far from all), easy cut-and-paste, readily save work digitally, etc.

So, how does teaching handwriting support early reading progress?

“ … historically, letter perception (a necessary precursor of reading) has been considered more of a passive behavior—that is, one that involves seeing the shapes of letters and hearing the sounds they represent. The potential importance of producing letters with the body, through handwriting, has generally not been considered as important. But what if—similar to learning about many other types of objects—learning about letters is facilitated by producing them? Then learning about written letters becomes an activity not only of seeing and hearing letters, but also of producing them by hand. A limited number of experimental studies have shown that, indeed, adults (James & Atwood, 2009; Longcamp et  al., 2008) and children (Li & James, 2016; Longcamp, Zerbato-Poudou, & Velay, 2005) learn symbols better if they write them by hand during learning than through other forms of practice, including visual, auditory, and even typing. In addition, correlational work demonstrates that early handwriting can have significant effects on literacy skills in young children (for a review, see Hall, Simpson, Guo, & Wang, 2015). How handwriting facilitates symbol learning in terms of underlying mechanisms, however, is a question that can be addressed only with brain-imaging studies.” (p. 503)

James, K. H. (2017). The importance of handwriting experience on the development of the literate brain. Current Directions in Psychological Science, 26(6), 502-508.

“Furthermore, based on an embodied theory of cognition [5], we hypothesize that VMM [visual-motor memory ] ability should affect written language recognition, as well as influencing written language production. In other words, VMM should also support reading abilities. Indeed, it is probable that more practised and procedural recall of letter/word forms while writing could aid pattern recognition when reading. This proposal is supported by evidence showing that the motor processes associated with writing reinforce a child's ability to recognize alphanumerical symbols [6]. Longcamp et al. [7] have demonstrated the importance of learning the motor representations of symbols for later visual recognition in adults. They taught participants new characters taken from the Gujarati or Bengali alphabets: half were trained using a typewriter and half by copying the characters by hand. Participants in the handwriting group were better able to recognize the new characters and retained this improved memory over time. Longcamp et al. [8] found improvement for character recognition in 5-year-olds when they learnt the letters through copying compared with typing, whereas Naka [9] showed that repeated writing of Chinese or Arabic characters by Japanese primary school children led to increased recall compared with just looking at the characters. Most recently, brain-imaging research has suggested that in pre-literate children the neural pathways associated with reading only activate in response to viewing letters if a child has previously been trained to print these letters free-form, as opposed to tracing their outline or typing them on a keyboard [10]. This implies that the activity of handwriting (and VMM) is advantageous for reading because it facilitates deeper knowledge of the component features that constitute a letter's form, aiding children's ability to distinguish and categorize letters. … There are a number of different models that attempt to capture the neural processes involved in writing and reading [11]. Nonetheless, most theorists agree that the complex skill of writing relies on a distributed set of cognitive processes that support the creation of orthographic representations. These representations are in turn used to activate the motor cortex and thereby generate hand movements [12,13].” (p.2)

Waterman, A.H., Havelka, J., Culmer, P.R., Hill, L.J.B., Mon-Williams, M. (2015). The ontogeny of visual-motor memory and its importance in handwriting and reading: A developing construct. Proceedings. Biological sciences / The Royal Society. 282(1798), 20140896 doi: 10.1098/rspb.2014.0896

“Handwriting is a complex skill that, despite increasing use of computers, still plays a vital role in education. It is assumed that children will master letter formation at a relatively early stage in their school life, with handwriting fluency developing steadily until automaticity is attained. The capacity theory of writing suggests that as automaticity develops, the proportion of working memory dedicated to the mechanics of handwriting is reduced, releasing capacity for the planning, composing and editing of content. This study examined the handwriting ability of 284 mainstream primary school children and explored possible associated factors. Correlations were found between poor handwriting, lower cognitive and literacy scores, and a longer duration for handwriting tasks. Giving children the opportunity to practise their handwriting sufficiently to increase the level of automaticity may release working memory to be applied to the cognitive demands of the task and may potentially raise their level of attainment.” (p.105)

McCarney, D., Peters, L., Jackson, S., Thomas, M., & Kirby, A. (2013). Does poor handwriting conceal literacy potential in primary school children? International Journal of Disability, Development and Education, 60(2), 105-118.

“A large body of data supports the view that movement plays a crucial role in letter representation and suggests that handwriting contributes to the visual recognition of letters. If so, changing the motor conditions while children are learning to write by using a method based on typing instead of handwriting should affect their subsequent letter recognition performances. In order to test this hypothesis, we trained two groups of 38 children (aged 3–5 years) to copy letters of the alphabet either by hand or by typing them. After three weeks of learning, we ran two recognition tests, one week apart, to compare the letter recognition performances of the two groups. The results showed that in the older children, the handwriting training gave rise to a better letter recognition than the typing training. … After training, we found stronger and longer lasting (several weeks) facilitation in recognizing the orientation of characters that had been written by hand compared to those typed. Functional magnetic resonance imaging recordings indicated that the response mode during learning is associated with distinct pathways during recognition of graphic shapes. Greater activity related to handwriting learning and normal letter identification was observed in several brain regions known to be involved in the execution, imagery, and observation of actions, in particular, the left Broca's area and bilateral inferior parietal lobules. Taken together, these results provide strong arguments in favour of the view that the specific movements memorized when learning how to write participate in the visual recognition of graphic shapes and letters.. … In fact, it has been reported that learning by handwriting facilitated subjects’ memorization of graphic forms (Naka & Naoi, 1995). Visual recognition was also studied by Hulme (1979), who compared children’s learning of a series of abstract graphic forms, depending on whether they simply looked at the forms or looked at them as well as traced the forms with their index finger. The tracing movements seemed to improve the children’s memorization of the graphic items. Thus, it was suggested that the visual and motor information might undergo a common representation process. Various data converge to indicate that the cerebral representation of letters might not be strictly visual, but might be based on a complex neural network including a sensorimotor component acquired while learning concomitantly to read and write (James & Gauthier, 2006; Kato et al., 1999; Longcamp et al., 2003; 2005a; Matsuo et al., 2003). Close functional relationships between the reading and writing processes might hence occur at a basic sensorimotor level, in addition to the interactions that have been described at a more cognitive level (e.g., Fitzgerald & Shanahan, 2000).” (p. 67).

Longcamp, M., Zerbato-Poudou, M.T., & Velay, J.L. (2005). The influence of writing practice on letter recognition in preschool children: A comparison between handwriting and typing. Acta Psychologia, 119, 67-79.

“In an age of increasing technology, the possibility that typing on a keyboard will replace handwriting raises questions about the future usefulness of handwriting skills. Here we present evidence that brain activation during letter perception is influenced in different, important ways by previous handwriting of letters versus previous typing or tracing of those same letters. Preliterate, five-year old children printed, typed, or traced letters and shapes, then were shown images of these stimuli while undergoing functional MRI scanning. A previously documented "reading circuit" was recruited during letter perception only after handwriting-not after typing or tracing experience. These findings demonstrate that handwriting is important for the early recruitment in letter processing of brain regions known to underlie successful reading. Handwriting therefore may facilitate reading acquisition in young children.” (p.32)

James, K.H., & Engelhardt, L. (2012). The effects of handwriting experience on functional brain development in pre-literate children. Trends Neurosci Educ. 1(1), 32-42.

“Digital writing devices associated with the use of computers, tablet PCs, or mobile phones are increasingly replacing writing by hand. It is, however, controversially discussed how writing modes influence reading and writing performance in children at the start of literacy. On the one hand, the easiness of typing on digital devices may accelerate reading and writing in young children, who have less developed sensory-motor skills. On the other hand, the meaningful coupling between action and perception during handwriting, which establishes sensory-motor memory traces, could facilitate written language acquisition. In order to decide between these theoretical alternatives, for the present study, we developed an intense training program for preschool children attending the German kindergarten with 16 training sessions. Using closely matched letter learning games, eight letters of the German alphabet were trained either by handwriting with a pen on a sheet of paper or by typing on a computer keyboard. Letter recognition, naming, and writing performance as well as word reading and writing performance were assessed. Results did not indicate a superiority of typing training over handwriting training in any of these tasks. In contrast, handwriting training was superior to typing training in word writing, and, as a tendency, in word reading. The results of our study, therefore, support theories of action-perception coupling assuming a facilitatory influence of sensory-motor representations established during handwriting on reading and writing.” (p. 136)

Kiefer, M., Schuler, S., Mayer, C., Trumpp, N.N., Hille, K., Sachse, S. (2015). Handwriting or typewriting? The influence of pen or keyboard-based writing training on reading and writing performance of preschool children. Adv. Cogn. 11(4), 136-46.

“Reading and writing are related but separable processes that are crucial skills to possess in modern society. The neurobiological basis of reading acquisition and development, which critically depends on phonological processing, and to a lesser degree, beginning writing as it relates to letter perception, are increasingly being understood. Yet direct relationships between writing and reading development, in particular, with phonological processing is not well understood. The main goal of the current preliminary study was to examine individual differences in neurofunctional and neuroanatomical patterns associated with handwriting in beginning writers/readers. In 46 5-6 year-old beginning readers/writers, ratings of handwriting quality, were rank-ordered from best to worst and correlated with brain activation patterns during a phonological task using functional MRI, and with regional gray matter volume from structural T1 MRI. Results showed that better handwriting was associated negatively with activation and positively with gray matter volume in an overlapping region of the pars triangularis of right inferior frontal gyrus. This region, in particular in the left hemisphere in adults and more bilaterally in young children, is known to be important for decoding, phonological processing, and subvocal rehearsal. We interpret the dissociation in the directionality of the association in functional activation and morphometric properties in the right inferior frontal gyrus in terms of neural efficiency, and suggest future studies that interrogate the relationship between the neural mechanisms underlying reading and writing development.” (p.155)

Gimenez, P., Bugescu, N., Black, J.M., Hancock, R., Pugh, K., Nagamine M, Kutner E, Mazaika P, Hendren R, McCandliss BD, Hoeft F. (2014). Neuroimaging correlates of handwriting quality as children learn to read and write. Frontiers in Human Neuroscience, 8, 155.

“What do these studies tell us about the importance of handwriting for letter learning? First, that handwriting and letter perception recruit the same network of activation in the literate brain, but before people become literate, handwriting serves to recruit this same network, implying that handwriting experience plays a crucial role in the formation of the brain network that underlies letter recognition. Further, we showed that perhaps the crucial aspect of handwriting for the development of this network is the variability in form that results from early handwriting in the young child. These findings have numerous important implications for literacy development. First, and obviously, handwriting (printing in the case of young children) is important for letter understanding and therefore for literacy development. Second, it does not matter how well a child prints his or her letters; in fact, it may be better if the child produces a lot of different versions of the same letter. Third, for children who have difficulty printing letters, viewing and tracing variable instances of a given letter may be very helpful for their letter categorization—an early step in letter learning—and subsequent literacy development.” (p.6)

James, K. H. (2017). The importance of handwriting experience on the development of the literate brain. Current Directions in Psychological Science, 26(6), 502-508.

“Writing helps in many ways. First the physical act of forming the letters forces the child to look closely at the features that make one letter different from another. … Second, writing letters (left to right) trains the ability to read left to right. Third, saying each sound as the letter is written helps anchor the sound-to-letter connection in the memory” (p.239).

McGuinness, D. (2004). Growing a reader from birth: Your child's path from language to literacy. New York: W.W. Norton and Co.

“Writing is an immensely important and equally complex and sophisticated human skill commonly ascribed a fundamental role in children’s cognitive and language development, and a milestone on the path to literacy. Nevertheless, compared to the vast field of reading research, there has been less scientific attention devoted to the act and skill of writing. … A large body of research in neuroscience, biopsychology and evolutionary biology demonstrates that our use of hands for purposive manipulation of tools plays a constitutive role in learning and cognitive development, and may even be a significant building block in language development. Furthermore, brain imaging studies (using fMRI, i.e., functional Magnetic Resonance Imaging) show that the specific hand movements involved in handwriting support the visual recognition of letters. Considering the fact that children today or in the near future may learn to write on the computer before they master the skill of handwriting, such findings are increasingly important. In this article we present evidence from experiments in neuroscience and experimental psychology that show how the bodily, sensorimotor – e.g., haptic – dimension might be a defining feature of not only the skill of writing but may in fact be an intrinsic factor contributing to low-level reading skills (e.g., letter recognition) as well, and we discuss what a shift from handwriting to keyboard writing might entail in this regard.” (p.386).

“A cursory and cross-disciplinary glance at the current state of writing research yields the impression that writing is mainly, if not exclusively, a mental (e.g., cognitive) process (MacArthur, Graham, & Fitzgerald, 2006; Torrance, van Waes, & Galbraith, 2007; Van Waes, Leijten, & Neuwirth, 2006). Cognitive approaches to the study of writing focus predominantly on the visual component of the process, and how it relates to cognitive processing. However, as evidenced by research in neuroscience, and as phenomenologically experienced by the writer him- or herself, writing is a process that requires the integration of visual, proprioceptive (haptic/kinaesthetic), and tactile information in order to be accomplished (Fogassi & Gallese, 2004). In other words, the acquisition of writing skills involves a perceptual component (learning the shape of the letter) and a graphomotor component (learning the trajectory producing the letter’s shape) (van Galen, 1991). Research has shown that sensory modalities involved in handwriting, e.g., vision and proprioception, are so intimately entwined that strong neural connections have been revealed between perceiving, reading, and writing letters in different languages and symbol/writing systems. (James & Gauthier, 2006; Kato et al., 1999; Longcamp, Anton, Roth, & Velay, 2003, 2005a; Matsuo et al., 2003; Vinter & Chartrel, 2008; Wolf, 2007).” (p.389)

Mangen, A., & Velay, J-L. (2010). Digitizing literacy: Reflections on the haptics of writing, Advances in Haptics, In Mehrdad Hosseini Zadeh (Ed.), InTech. DOI: 10.5772/8710. Retrieved from: http://www.intechopen.com/books/advances-in-haptics/digitizing-literacy-reflections-on-the-haptics-of-writing

“In parallel, children (and adults) under alphabetization also learn to draw letters of the alphabet. Indeed, writing requires fine motor coordination of hand gestures, a process guided by online feedback from somatosensory and visual systems (Margolin, 1984). In particular, gestures of handwriting are thought to be represented in the dorsal part of the premotor cortex, rostral to the primary motor cortex responsible for hand movements, i.e., a region first coarsely described by Exner as the “graphic motor image center” (see Roux et al., 2010 for a review). Exner's area is known to be activated when participants write letters but not when they copy pseudoletters (Longcamp et al., 2003). Moreover, direct brain stimulation of the same region produces a specific inability to write (Roux et al., 2009). Importantly, this region is activated simply by visual presentations of handwritten stimuli (Longcamp et al., 2003, 2008), even when they are presented unconsciously (Nakamura et al., 2012). Additionally these activations take place in the premotor cortex contra-lateral to the dominant hand for writing (Longcamp et al., 2005). These results suggest that literacy training establishes a tight functional link between the visual and motor systems for reading and writing. In fact, it has been proposed that reading and writing rely on distributed and overlapping brain regions, each showing slightly different levels of activation depending on the nature of orthography (Nakamura et al., 2012). As for the reciprocal link between the visual and motor components of this reading network, brain-damaged patients and fMRI data from normal subjects consistently suggest that top-down activation of the posterior inferior temporal region constitutes a key component for both handwriting (Nakamura et al., 2002; Rapcsak and Beeson, 2004) and reading (Bitan et al., 2005; Nakamura et al., 2007). … “Perhaps the most spectacular case in point, and the one we choose to focus on in this article, is the spontaneous link between the motor and visual systems during literacy acquisition. This link is revealed in the beginning of the alphabetization process by the classic emergence of spontaneous mirror writing, i.e., writing letters in both orientations indistinctly (Cornell, 1985). Indeed our primate visual system presents a mirror invariant representation of visual stimuli, which enables us to immediately recognize one image independently of left or right viewpoints (Rollenhagen and Olson, 2000; Vuilleumier et al., 2005; Biederman and Cooper, 2009). This generates a special difficulty to distinguish the left-right orientation of letters (e.g., b vs. d) (Orton, 1937; Corballis and Beale, 1976; Lachmann, 2002; Lachmann et al. in this special issue). One account for the emergence of mirror writing is that writing gestures can be “incorrectly” guided by mirror invariant visual representations of letters, a framework referred to as “perceptual confusion” (see Schott, 2007 for a review on this topic.In complement, recent studies demonstrate that after literacy acquisition, mirror invariance is lost for letter strings (Kolinsky et al., 2011; Pegado et al., 2011, 2014) and that the VWFA shows mirror discrimination for letters (Pegado et al., 2011); see figure upper part. Interestingly, in this special issue, Nakamura and colleagues provide evidence for the causal role of the left occipito-temporal cortex (encompassing the VWFA) in mirror discrimination by using transcranial magnetic stimulation. However, it is still an open question whether this region becomes completely independent to discriminate the correct orientation of letters or if it still depends on inputs from phonological, gestural, and/or vocal representations.” (p. 1, 3)

Pegado, F., Nakamura, K., & Hannagan, T. (2014). How does literacy break mirror invariance in the visual system? Front. Psychol. 5, 703. doi: 10.3389/fpsyg.2014.00703

“In this debate about the importance of motor conditions when learning to read and write, the results of the present study are in agreement with those showing that writing letters facilitates their memorization and their subsequent recognition (Hulme, 1979; Naka and Naoi, 1995)” (p. 75).

Longcamp, M., Zerbato-Poudou, M.T., & Velay, J.L. (2005). The influence of writing practice on letter recognition in preschool children: a comparison between handwriting and typing. Acta Psychologia, 119, 67-79.

“Thus, replacing handwriting by typing during learning might have an impact on the cerebral representation of letters and thus on letter memorization. In two behavioral studies, Longcamp et al. investigated the handwriting/typing distinction, one in pre-readers (Longcamp, Zerbato-Poudou et al., 2005b) and one in adults (Longcamp, Boucard, Gilhodes, & Velay, 2006). Both studies confirmed that letters or characters learned through typing were subsequently recognized less accurately than letters or characters written by hand. In a subsequent study (Longcamp et al., 2008), fMRI data showed that processing the orientation of handwritten and typed characters did not rely on the same brain areas. Greater activity related to handwriting learning was observed in several brain regions known to be involved in the execution, imagery, and observation of actions, in particular, the left Broca’s area and bilateral inferior parietal lobules. Writing movements may thus contribute to memorizing the shape and/or orientation of characters. However, this advantage of learning by handwriting versus typewriting was not always observed when words were considered instead of letters. In one study (Cunningham & Stanovich, 1990), children spelled words which were learned by writing them by hand better than those learned by typing them on a computer. … Current brain imaging techniques show how neural pathways can be differentially activated from handling different writing systems: logographic writing systems seem to activate very distinctive parts of the frontal and temporal areas of the brain, particularly regions involved in what is called motor perception. For instance, experiments using fMRI have revealed how Japanese readers use different pathways – when reading kana (an efficient syllabary used mainly for foreign and/or newer words, and for names of cities and persons), the activated pathways are similar to those used by English readers. In contrast, when reading kanji – an older logographic script influenced by Chinese – Japanese readers use pathways that come close to those used by the Chinese (Wolf, 2007)” (p.389).

Mangen, A., & Velay, J-L. (2010). Digitizing literacy: Reflections on the haptics of writing, Advances in Haptics, In Mehrdad Hosseini Zadeh (Ed.), InTech. DOI: 10.5772/8710. Retrieved from: http://www.intechopen.com/books/advance ... of-writing

“Current brain imaging techniques show how neural pathways can be differentially activated from handling different writing systems: logographic writing systems seem to activate very distinctive parts of the frontal and temporal areas of the brain, particularly regions involved in what is called motor perception. For instance, experiments using fMRI have revealed how Japanese readers use different pathways – when reading kana (an efficient syllabary used mainly for foreign and/or newer words, and for names of cities and persons), the activated pathways are similar to those used by English readers. In contrast, when reading kanji – an older logographic script influenced by Chinese – Japanese readers use pathways that come close to those used by the Chinese (Wolf, 2007).” (p.389)

Mangen, A., & Velay, J-L. (2010). Digitizing literacy: Reflections on the haptics of writing, Advances in Haptics, In Mehrdad Hosseini Zadeh (Ed.), InTech. DOI: 10.5772/8710. Retrieved from: http://www.intechopen.com/books/advances-in-haptics/digitizing-literacy-reflections-on-the-haptics-of-writing

“Reading and writing are related but separable processes that are crucial skills to possess in modern society. The neurobiological basis of reading acquisition and development, which critically depends on phonological processing, and to a lesser degree, beginning writing as it relates to letter perception, are increasingly being understood. Yet direct relationships between writing and reading development, in particular, with phonological processing is not well understood. The main goal of the current preliminary study was to examine individual differences in neurofunctional and neuroanatomical patterns associated with handwriting in beginning writers/readers. In 46 5-6 year-old beginning readers/writers, ratings of handwriting quality, were rank-ordered from best to worst and correlated with brain activation patterns during a phonological task using functional MRI, and with regional gray matter volume from structural T1 MRI. Results showed that better handwriting was associated negatively with activation and positively with gray matter volume in an overlapping region of the pars triangularis of right inferior frontal gyrus. This region, in particular in the left hemisphere in adults and more bilaterally in young children, is known to be important for decoding, phonological processing, and subvocal rehearsal. We interpret the dissociation in the directionality of the association in functional activation and morphometric properties in the right inferior frontal gyrus in terms of neural efficiency, and suggest future studies that interrogate the relationship between the neural mechanisms underlying reading and writing development.” (p.155)

Gimenez, P., Bugescu, N., Black, J.M., Hancock, R., Pugh, K., Nagamine, M., Kutner, E., Mazaika, P., Hendren, R., McCandliss, B.D., & Hoeft, F. (2014). Neuroimaging correlates of handwriting quality as children learn to read and write. Frontiers in Human Neuroscience, 8, 155

“The implication of the direct path finding is that instruction in word recognition skills will transfer more to handwriting than instruction in handwriting skills will transfer to word recognition. Instructional research is therefore needed to evaluate whether covariances or direct paths best characterize the relationships between handwriting and word recognition in literary instruction. This research is especially needed because multisensory approaches to language remediation (e.g., Birsch, 1999) tend to assume that integrating handwriting with word recognition instruction facilitates the learning of word recognition. However, the results for the direct paths in both structural models yield evidence of bidirectional, reciprocal relationships between word recognition and spelling. Training spelling should influence word recognition and training word recognition should influence spelling” (p.45). … This phenotypic study (see Berninger, Abbott, et al., 2001, for additional details about method and findings) provides additional support for the claim that reading and writing systems draw on common as well as on unique processes (cf. Berninger et al., 1994; Fitzgerald & Shanahan, 2000). (p.48)

Berninger, V.W., Abbott, R.D., Abbott, S.P., Graham, S., & Richards, T. (2002). Writing and reading: Connections between language by hand and language by eye. Journal of Learning Disabilities, 35, 39-56.

“Handwriting is a perceptual-motor skill, acquired through repetitive practice (Feder & Majnemer, 2007), and is often presented as an example of a motor skill acquired via procedural learning processes (Dayan and Cohen, 2011 and Wilhelm et al., 2012). Handwriting production is most often characterized by performance speed (also termed ‘production fluency’, often assessed using text-copying tasks e.g., Graham et al., 2006, Hatcher et al., 2002 and Sumner et al., 2014) and legibility. Studies have found that handwriting legibility develops quickly during first-grade (ages 6- to 7-years), reaching a plateau by second-grade (Overvelde & Hulstijn, 2011). By third-grade, handwriting becomes automatic, organized, and available as a tool to facilitate the development of ideas. However, handwriting is not a straightforward motor skill (Cheng-Lai et al., 2013 and Planton et al., 2013), and has been linked with reading development (Berninger, 2009). Measures of motor proficiency that correlate with handwriting production in school aged children show an indirect effect on handwriting via reading related skills, such as orthography (Berninger, 2009 and Abbott and Berninger, 1993), underscoring reading as a mediator of the association between motor proficiency and handwriting production. … Previous studies have established that fine-motor perceptual performance predicts reading (Cameron et al., 2012, Grissmer et al., 2010, Pagani et al., 2010 and Son and Meisels, 2006) beyond the long-established contribution of executive function (Duncan et al., 2007). For example, in an analysis of several longitudinal, large-scale databases, Grissmer et al. (2010) found that performance on a copy design test in kindergarten predicted reading in fifth-grade, beyond early reading, attention, family, and child characteristics. In the current study ILT speed measurements were associated with handwriting and reading. Perhaps this association is related to the finding that similar brain regions are involved in learning perceptual-motor, motor, linguistic, and other cognitive skills. Furthermore, impaired functioning of some of these regions or networks may underlie deficits in handwriting and reading (Nicolson & Fawcett, 2011)”. (p. 265)

Julius, M.S., Rivka, M.,Shecter-Nissim, Z., & Adi-Japha, E. (2016). Children's ability to learn a motor skill is related to handwriting and reading proficiency. Learning and Individual Differences, 51, 265–272.

Handwriting’s impact on other writing skills.

“The meta-analysis by Santangelo and Graham (2015) has already shown that students with handwriting instruction would perform significantly better on writing quality, writing productivity, and writing fluency compared to their peers without handwriting instruction. The practical importance of handwriting instruction is further supported through the current meta-analysis, as we found the consistency of the relationship between handwriting fluency and writing. Although the contribution of handwriting fluency varied across different writing measures, handwriting fluency was identified as a significant factor of students’ performance on writing quality, writing fluency, and substantive quality. … Through the two studies related to the relationship of handwriting, keyboarding and writing measures, we stressed the need for incorporating handwriting as an essential part of instruction in classrooms. Handwriting and keyboarding both significantly positively associated with the development of writing, for a variety of writing measures. This further supports the simple view of writing, which emphasizes the contribution of transcription skills on text generation. Besides, handwriting did no worse than keyboarding on writing quality and actually significantly related to keyboarding performance, particularly on speed.” (p. 57, 59)

Feng, L., Lindner, A., Ji, X.R., Joshi, R.M. (2019). The roles of handwriting and keyboarding in writing: A meta-analytic review. Reading & Writing, 32, 33–63.

“Based on the Writer(s)-within-Community Model, this article focuses on the role of handwriting in writers’ composing process. With the goal of highlighting the importance of researching and promoting handwriting, we provide an extensive summary of current evidence on the topic. It is well established that an important condition for skilled writing is handwriting automaticity. As here reviewed, there are at least four reasons why poor and slow handwriting can interfere with writing: it has a negative impact on the reader, creates a mismatch between ideas generation and recording, imposes heavy demands on working memory, and turns writing into a painful experience. Grounded on this, we make the case for providing child and adolescent writers with explicit and systematic practice in handwriting through evidence-based practices. The best practices at the letter (e.g., alphabet exercises), word/sentence (e.g., copying exercises), and text (e.g., authentic writing tasks) levels are reviewed. We conclude that the integration of handwriting practices into the educational program of beginning and developing writers is particularly important. It may allow the creation of solid basis for other writing abilities to flourish and therefore contribute to the emergence of capable and motivated writers.” (p. 311)

Limpo, T., & Graham, S. (2020). The role of handwriting instruction in writers’ education. British Journal of Educational Studies, 68(3), 311-329. DOI: 10.1080/00071005.2019.1692127

“Handwriting continues to be the main way of authoring text in the classroom and is the standard method of communication used in most examinations (McMaster & Roberts, 2016; Santangelo & Graham, 2016). This remains the situation despite the growing use of technology (such as tablets and laptops) within educational settings. This means that children who struggle in acquiring age-appropriate handwriting skills are at a considerable disadvantage in a number of different ways. For example, children who struggle with the mechanics of handwriting (so that the skill is not automated) may have reduced cognitive capacity for other mentally-demanding tasks such as generating creative ideas (Medwell, Strand, & Wray, 2009). Furthermore, a ‘presentation effect’ has been noted, whereby pieces of writing with the same content are scored more harshly when the writing is less legible (Graham, Harris, & Herbert, 2011; Santangelo & Graham, 2016). More generally, the process of handwriting has been shown to play an important role in the development of children’s cognitive and literacy skills (Frolek Clark & Luze, 2014; Graham, Struck, Santoro, & Berninger, 2006; Longcamp et al., 2008; Longcamp, Zerbato-Poudou, & Velay, 2005; Mangen & Velay, 2010; McCarney, Peters, Jackson, Thomas, & Kirby, 2013; Waterman, Havelka, Culmer, Hill, & Mon-Williams, 2014). It is therefore unsurprising that handwriting ability has been found to predict academic attainment (Dinehart, 2015; McCarney et al., 2013).” (p. 1, 2)

Shire, K.A., Atkinson, J., Williams, E.A., Pickavance, J., Magallón, S., Hill, L.J.B., Waterman, A.H., Sugden, D.A., & Mon-Williams, M. (2020). Developing and implementing a school-led motor intervention for children with handwriting difficulties. Journal of Occupational Therapy, Schools, & Early Intervention, DOI: 10.1080/19411243.2020.1837047

“Studies of typically developing children have found that the quality of handwriting shows a rapid development between ages six and seven, reaches a plateau between ages seven and eight and improves further in that handwriting becomes automated and organized between ages eight and nine (Feder & Majnemer, 2007). Automation is important for handwriting and other academic skills (e.g., reading, arithmetic). For example, if handwriting is unautomated, there will be a reduction in both the quality and quantity of text (Connelly & Hurtst, 2001; LaBerge & Samuels, 1974). Handwriting ability becomes automated when the process can be quickly and precisely executed without the need for conscious attention (Connelly & Hurtst, 2001; LaBerge & Samuels, 1974). Acquisition of a new skill is generally associated with a decrease in the need for effortful control over performance, which leads to the development of automation.” (p.1498)

Stievano, P., Michetti, S., McClintock, S.M., Levi, G., & Scalisi, M.G. (2016). Handwriting fluency and visuospatial generativity at primary school. Reading and Writing, 29, 1497–1510.

“Collectively, the research findings supported prior research showing the value of teaching handwriting for transfer to other written language skills such as spelling and some aspects of composing early in written language development of English speaking beginning writers (e.g. Berninger et al., 1997; Graham et al., 2000; Jones & Christensen, 1999). Specifically, the research findings provided evidence for the Slingerland method, which has been used by many teachers over the years, for teaching handwriting linked to spelling and composing. Moreover, a method of providing handwriting instruction embedded in other literacy activities, which previously was thought to be needed only for students with specific learning disabilities, has been shown to benefit typically developing writers in the general education classroom, as originally envisioned by Slingerland (1974). … Additional research is needed on (a) how long to teach one format—manuscript or cursive— before introducing the other format, and (b) how long to continue the review and practice of handwriting and related skills throughout the elementary and middle school grades. Indeed some cultures and educational systems begin with cursive format. A limitation of the current research is that it may be specific to schools and cultures that introduce manuscript in kindergarten and first grade and defer cursive instruction until later grades (typically third), whereas in some schools and cultures cursive is introduced first. Therefore future research should investigate the best ways to teach handwriting with transfer to spelling and composing in mind to beginning writers and readers (a) within the context of educational practices of specific different countries and written languages, and (b) for students of diverse socioeconomic backgrounds, not just middle class as in the current studies, and ethnic backgrounds, not just primarily of European heritage as in the current studies. These studies did not address whether manuscript or cursive should be taught first but rather the advantage of teaching the same format for at least two years until mastered sufficiently to support sustained handwriting.” (p. 311-312)

Wolf, B., Abbott, R. D., & Berninger, V. W. (2017). Effective beginning handwriting instruction: multi-modal, consistent format for 2 years, and linked to spelling and composing. Reading and Writing, 30(2), 299-317. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5300752/pdf/nihms805554.pdf

“Accumulating evidence indicates handwriting automaticity is related to the development of effective writing skills. The present study examined the levels of handwriting automaticity of Australian children at the end of kindergarten and the amount and type of writing instruction they experienced before entering first grade. The current study involved 177 kindergarten children enrolled in 23 classrooms from seven government-funded primary schools in Western Australia. Individual child level data (e.g., handwriting automaticity and word-reading skills) were collected and teachers were asked to complete a survey assessing the amount of time and types of writing activities developed in their classrooms (e.g., teaching basic skills and teaching writing processes). Hierarchical linear models were conducted to examine total variance attributable to child and classroom levels. Results showed a total variance of approximately 20% in children’s handwriting automaticity attributable to differences among classrooms when gender and word-reading skills were controlled for. Large variability was noted in the amount and type of writing instruction reported by a subset of participating teachers. Handwriting automaticity was associated with the teaching of revising strategies but not with the teaching of handwriting. Implications for writing development and writing instruction are discussed.” (p.1)

Malpique, A.A., Pino-Pasternak, D., & Valcan, D. (2017). Handwriting automaticity and writing instruction in Australian kindergarten: An exploratory study. Reading and Writing, In Press. 1-24. See at https://link.springer.com/epdf/10.1007/s11145-017-9753-1?author_access_token=IMwCbRL1y3KSBow2-RRtvve4RwlQNchNByi7wbcMAY49l4mCr4kPaAkkrzDd4s_jBpTaZzj9DHkua_iROqHYuwdTcPwBdonmpfTP1A_0C2Ju8m4-IJTmsCYtc5oYqYml2ZVjpvaSCMjMBfbyUk1Myw==

‘Off to a good start’ is not enough to assume that children’s ongoing written literacy learning will develop and progress without sustained, direct handwriting instruction. This finding is underscored consistently by others in the research community (Graham, 2009; Moats, n.d.). Our findings corroborate those reported by others. There is something to be said about handwriting that demonstrates control of execution that suggests more than a matter of neatness. Far more important is its connection to fluency and in turn, the ability to unlock the higher order and more complex skills associated with text generation, in Berninger’s (1999) simple view of writing model.” (p.56)

Roessingh, H., & Nordstokke, D. (2019). Handwriting at Grade 3: More than a matter of ‘neatness’ Language and Literacy, 21(3), 38-63.

“This meta-analysis examined true- and quasi-experimental intervention studies conducted with K-12 students to determine if teaching handwriting enhanced legibility and fluency and resulted in better writing performance. When compared to no instruction or non-handwriting instructional conditions, teaching handwriting resulted in statistically greater legibility (ES = 0.59) and fluency (ES = 0.63). Motor instruction did not produce better handwriting skills (ES = 0.10 for legibility and −0.07 for fluency), but individualizing handwriting instruction (ES = 0.69) and teaching handwriting via technology (ES = 0.85) resulted in statistically significant improvements in legibility. Finally, handwriting instruction produced statistically significant gains in the quality (ES = 0.84), length (ES = 1.33), and fluency of students’ writing (ES = 0.48). The findings from this meta-analysis provide support for one of the assumptions underlying the Simple View of Writing (Berninger et al., Journal of Educational Psychology, 94, 291–304, 2002) frontal gyrus text transcription skills are an important ingredient in writing and writing development” (p. 225)

Santangelo, T., & Graham, S. (2016). A comprehensive meta-analysis of handwriting instruction. Educational Psychology Review, 28, 225–265.

“The most striking result was the strength of relations between handwriting fluency and both macro-organization and productivity for the fourth grade sample. We imagined that handwriting fluency might place a strong constraint on all aspects of writing for first-grade students, but did not expect it to be as strongly related to written composition for fourth-grade students. However, Graham et al. (1997) reported standardized path coefficients in the range of .5–.7 from handwriting fluency to composition quality as well as composition fluency for large samples of students from first through sixth grade. What might explain the striking relations between handwriting fluency and written composition, including macro aspects of organization of writing for fourth grade students? One possibility is that an individual who is fluent at handwriting fluency has more attentional resources that can be devoted to planning and composing when writing compared to an individual who is not fluent at handwriting and must devote attentional resources to this aspect of writing. Flowers and Hayes (1980) provided an apt description of the processing demands of writing: As a dynamic process, writing is an act of dealing with an excessive number of simultaneous demands or constraints. Viewed this way, a writer in the act is a thinker on full-time cognitive overload (p. 33, cited by Torrance & Galbraith, 2006). A large literature that includes both correlational and experimental methods supports this explanation of relations between handwriting fluency and higher-level aspects of writing (Alves, Castro, Sousa, & Stromqvist, 2007; Chanquoy & Alamargot, 2002; Christensen, 2005; Connelly, Campbell, MacLean, & Barnes, 2006; Connelly, Dockrell, & Barnett, 2005; Dockrell, Lindsay, & Connelly, 2009; Graham et al., 1997; McCutchen, 2006; Olive, Alves, & Castro, in press; Olive & Kellogg, 2002; Peverly, 2006; Torrance & Galbraith, 2006). The argument that handwriting fluency affects higher level aspects of writing because of capacity limitations is analogous to that made to explain the relation between fluent decoding and comprehension” (p.216-7).

Wagner, R. K., Puranik, C. S., Foorman, B., Foster, E., Wilson, L. G., Tschinkel, E., & Kantor, P. T. (2011). Modeling the development of written language. Reading and Writing, 24(2), 203–220.

“In addition, results of instructional studies imply causal relationships between handwriting and other written language skills. Teaching automatic letter writing improved compositional fluency: Students wrote texts that were longer (Berninger, Abbott, Whitaker, Sylvester, & Nolen, 1995) and were completed in less time (Berninger, Vaughan, Abbott, Abbott, Brooks, Rogan, et al., 1997; Berninger, Rutberg, Abbott, Garcia, Anderson-Youngstrom, Brooks, et al., 2006; Graham, Harris, & Fink, 2000). Teaching handwriting has also shown transfer to improved word reading (e.g., Berninger, Dunn, Lin, & Shimada, 2004; Berninger et al., 1997, 2006; Dunn & Miller, 2009)” (p. 494).

Todd, L. R., Berninger, V.W., Stock, P., Altemeier, L., Trivedi, P., & Maravilla, K. R. (2011). Differences between good and poor child writers on fMRI contrasts for writing newly taught and highly practiced letter forms. Reading and Writing, 24(5), 493-516.

“There is a strong relationship between orthographic–motor integration related to handwriting and students' ability to produce creative and well‐structured written text. This relationship is thought to be due to the cognitive load which results when attention is required by writers to write letters and words on the page. Lack of automaticity in orthographic–motor integration means that writers do not have sufficient cognitive resources to accomplish the more demanding aspects of text production such as ideation, text monitoring, and pragmatic awareness. A systematic handwriting program can significantly improve the quality of written text by young children experiencing problems with orthographic–motor integration. This study investigated the effectiveness of a handwriting program in remediating older students' problems in orthographic–motor integration and consequently enhancing their written language skills. Two groups of students in Grades 8 and 9 were provided with either practice in handwriting or daily completion of a written journal. There were no differences between the two groups at pre‐test. However, at post‐test, the handwriting group had significantly higher scores in orthographic–motor integration as well as for the length and quality of the text they wrote.” (p. 441)

Christensen, C.A. (2005). The role of orthographic–motor integration in the production of creative and well‐structured written text for students in secondary school. Educational Psychology, 25(5), 441-453.

“Evidence is accumulating that handwriting has an important role in written composition. In particular, handwriting automaticity appears to relate to success in composition. This relationship has been little explored in British contexts and we currently have little idea of what threshold performance levels might be. In this paper, we report on two linked studies that attempted to identify performance levels in handwriting automaticity for children at two ages, below which their success in writing composition might be considered to be at risk. We conclude by suggesting interpolated levels for children at different ages, although we recognise the tentative nature of these suggestions.” (p. 34)

Medwell, J., & Wray, D. (2014). Handwriting automaticity: The search for performance thresholds. Language and Education 28(1), 34-51.

“Handwriting speed is important to the quantity and quality of children's essays. This article reviews research on adult essay writing and lecture note taking that extends this finding to adult writers. For both children and adults, research suggests that greater transcription speed increases automaticity of word production, which in turn lessens the burden on working memory (WM) and enables writers to use the limited capacity of WM for the metacognitive processes needed to create good reader-friendly prose. These findings suggest that models of writing, which emphasize the metacognitive components of writing primarily, should be expanded to include transcription (handwriting automaticity and spelling). The article also evaluates the implications of fluent handwriting to WM, given that even the most fluent handwriting can consume some WM resources and recent research and theory has highlighted the importance of WM to quality writing. Finally, the implications of handwriting and WM to assessment and instruction are discussed.” (p.197)

Peverly, S.T. (2006). The importance of handwriting speed in adult writing. Developmental Neuropsychology, 29(1), 197-216.

“The development of handwriting speed and legibility in 900 children in Grades 1–9 was examined. Each student completed 3 writing tasks: copying a paragraph, writing a narrative, and writing an essay. The children's speed of handwriting on the copying task typically increased from one grade to the next, but the pace of development was uneven during the intermediate grades and leveled off in Grade 9 as speed began to approximate adult speeds. In contrast, improvement in handwriting legibility on the 3 writing tasks was primarily limited to the intermediate grades. Girls' handwriting was more legible than boys' handwriting, and the girls wrote faster in Grades 1, 6, and 7. Right-handers were also faster than left-handers, but there was no difference in the legibility of their written products. Finally, handwriting speed contributed significantly to the prediction of legibility on the narrative and expository writing tasks, but the contribution was small, accounting for only 1% of the variance.” (p. 42)

Graham, S., Weintraub, N., Berninger, V., & Shafer, W. (1998). Development of handwriting speed and legibility in grades 1-9. Journal of Educational Research, 92, 42-52.

“The accumulated evidence also supports the proposition that handwriting and spelling play an important role in writing development (Graham, 2006b). First, handwriting and spelling are easier or less cognitively demanding for more skilled than less skilled writers. Second, there is a large body of research demonstrating that handwriting and spelling improve with age. For example, we found that children’s handwriting fluency improves 10 letters or more per minute each year up to high school (Graham, Berninger, Weintraub, & Schafer, 1998). Third, individual differences in handwriting and spelling predict how well students write. In a study with 600 children, we found these two skills accounted for 25% and 42% of the variance in writing quality at the primary and intermediate grades, and 66% and 41% of the variance in writing output at these same grade levels, respectively (Graham, Berninger, Abbott, Abbott, & Whitaker, 1997). Fourth, eliminating these skills through dictation has a positive impact on the writing of specific groups of writers. For instance, MacArthur and Graham (1987) reported that students with LD produced qualitatively better text when dictating stories versus writing them by hand. Finally, there is a small body of studies showing that handwriting or spelling instruction can enhance writing performance. We found that providing extra instruction in these skills to young struggling writers increased how much they wrote and resulted in improved sentence construction skills (Graham, Harris,&Fink, 2000; Graham, Harris, & Fink-Chorzempa, 2002). Graham (2006b) also offered a tentative proposition that sentence construction skills shape writing development. There is some evidence that skilled writers produce more complex sentences than less skilled writers, although these findings do not hold for all comparisons (e.g., good versus poor readers). Developing writers’ sentences become increasingly complex with age, although this finding varies by writing task. Sentence skills are correlated with writing performance (at least in some studies), but this appears to vary by genre. Lastly, efforts to improve sentence construction skills of developing writers can enhance their writing performance, if the right type of instruction is provided. For example, Saddler and Graham (2005) reported that sentence combining instruction had a positive impact on the quality of text produced by struggling writers.” (p.61)

Graham, S., & Harris, K.R. (2009). Almost 30 years of writing research: Making sense of it all with The Wrath of Khan. Learning Disabilities Research and Practice, 24(2), 58–68.

So, cursive or manuscript? Does it matter?

“Unlike some European countries such as Italy and France that teach cursive writing from the beginning of formal schooling, in the United States manuscript writing (printing) is taught from kindergarten to second grade, and cursive is not introduced until third grade; and typically cursive writing is not taught after fourth grade. Thereafter, most children use only manuscript printing or a mix of manuscript and cursive (Graham, Berninger, & Weintraub, 1998)” (p.495)…. “Alphabetic languages with grapheme-phoneme correspondences may have been invented because writers discovered that written symbols associated with speech sounds require less brain resources and can be produced more efficiently (i.e., requiring activation of fewer brain regions and needing less energy to function). This link between letter writing and phonological access may explain why children improved in reading real words and orthographic coding when taught word decoding and letter writing in tandem compared to when taught decoding alone without letter writing instruction (Berninger, Dunn, Lin, & Shimada, 2004; Dunn & Miller, 2009). Automatic letter writing, with its automatic access to phonology (lexical names and sublexical phonemes) may also facilitate learning of word spelling. … Understanding writing development is complex because writing brains are dynamically constructed as brains interact with the environment (Berninger & Richards, 2002; James & Gauthier, 2006). In addition, writing involves many other cognitive processes besides transcription (Alamargot & Chanquoy, 2001; Fayol, 1994, 1999, 2008; Fayol, Jisa, & Mazur-Palandre, 2008; Hayes, 2009; Hayes & Chenoweth, 2006; Hayes & Flower, 1980).” (p.511-512).

Richards, T., Berninger, V., Stock, P., Altemeier, L., Trivedi, P., & Maravilla, K. (2011). Differences between good and poor child writers on fMRI contrasts for writing newly taught and highly practiced letter forms. Reading and Writing, 24(5), 493-516.

“Additional research is needed on (a) how long to teach one format—manuscript or cursive—before introducing the other format, and (b) how long to continue the review and practice of handwriting and related skills throughout the elementary and middle school grades. Indeed some cultures and educational systems begin with cursive format. A limitation of the current research is that it may be specific to schools and cultures that introduce manuscript in kindergarten and first grade and defer cursive instruction until later grades (typically third), whereas in some schools and cultures cursive is introduced first. Therefore future research should investigate the best ways to teach handwriting with transfer to spelling and composing in mind to beginning writers and readers (a) within the context of educational practices of specific different countries and written languages, and (b) for students of diverse socioeconomic backgrounds, not just middle class as in the current studies, and ethnic backgrounds, not just primarily of European heritage as in the current studies. These studies did not address whether manuscript or cursive should be taught first but rather the advantage of teaching the same format for at least two years until mastered sufficiently to support sustained handwriting. This should be kept in mind in interpreting and generalizing the results.” (p.312)

Wolf, B., Abbott, R.D., & Berninger, V.W. (2017). Effective beginning handwriting instruction: Multi-modal, consistent format for 2 years, and linked to spelling and composing. Reading and Writing, 30(2), 299–317.

“There is increasing evidence that mastering handwriting skills play an important role on academic achievement. This is a slow process that begins in kindergarten: at this age, writing is very similar to drawing (i.e. scribbles); from there, it takes several years before children are able to write competently. Many studies support the idea that motor training plays a crucial role to increase mental representations of the letters, but relatively little is known about the specific relation between handwriting skills and teaching practices. This study investigated the efficacy of cursive writing teaching. The sample comprised 141 students attending eight classes of the first grade of primary school, all with typical development, not exhibiting any cognitive or sensory disabilities, nor displaying motor disorders that could significantly hinder the execution of the writing task. We tested whether the development of academic writing skills could be effectively supported by training strategies focusing on cursive writing. All rules and characteristics of the letters were explained by demonstrating the correct writing movements, based on the idea that movement learning becomes more valuable when children begin to connect the letters in order to write individual words. Growth models on pre-, post- and follow-up measures showed that performance on prerequisites and writing and reading skills were better overall among the children in the intervention group as compared to control group.” (p.1)

"...Nevertheless, we believe that working on the quality of the practice is fundamental; otherwise it would be highly improbable for writing feature rates to increase without negatively affecting readability. Concerning this feature of education, further investigation is needed to better understand the relation between handwriting practice and the development of writing abilities during primary school. Moreover, our study introduces an innovative fact not previously dealt with in recent literature: that children who adopted the cursive type as the only handwriting type showed a higher writing rate than pupils using more types. This fact contrasts with the literature which states that the cursive type decreases writing rates [51]. We also observed that pupils using cursive as the only handwriting type had better results in producing orthographically correct words than students using more types. As shown by other studies [20], it seems that the grapho-motor component affects word production management, especially for writers in the learning phase. In addition, we observed that children who only learned the cursive type made faster improvements in reading. This fact may be explained by a major focus of active resources on the lexical access task. The very nature of the cursive type may help students to easily memorize and recall a word unit, since in the cursive type the letters of a word are linked one to another, while in print type they are separated [35].

In conclusion, like other studies [10,11,35], our work tends to demonstrate how, upon training, writing and reading abilities improve in terms of written letter rate (students write faster), orthography (words are written correctly), and reading (students read and understand better). However, writing quality is a parameter to be investigated thoroughly in further studies. Considering writing type, we can observe how students who learn every type simultaneously do not achieve results as good as those achieved by cursive-only students. This finding supports the idea that the development of writing abilities in primary school is better favored by the teaching of a single type of handwriting, namely cursive handwriting. Furthermore, teaching of the cursive type generates improvement in graphic and orthographic word production by the end of the school year. A remarkable feature to be taken into account is the rapid improvement of basic skills in the intervention group as compared to the control group" (p.14)

Semeraro, C., Coppola, G., Cassibba, R., & Lucangeli, D. (2019). Teaching of cursive writing in the first year of primary school: effect on reading and writing skills. PLoS One, 14(2), e0209978. https://doi.org/10.1371/journal.pone.0209978.

“Reading and writing are major interrelated skills that partly determine academic achievement. The question of how to teach these abilities is an important issue for researchers and practitioners alike. In the present study, we explored the impact of handwriting learning on letter knowledge and reading. We compared three groups of schoolchildren from Quebec and France, who differed in the handwriting style they learned in first grade. In the manuscript group, pupils were exposed to only one type of allograph in reading and writing. In the cursive group, pupils learned to write in cursive, but encountered printed letters in books. In the mixed group, pupils learned to write in both cursive and manuscript. The results showed that the manuscript and mixed groups performed better than the cursive group on measurements of letter knowledge. The mixed group achieved the highest reading scores.” (p. 88)

Bara, F., Morin M. F., Alamargot, D., & Bosse, M. L. (2016). Learning different allographs through handwriting: The impact on letter knowledge and reading acquisition. Learning and Individual Differences, 45, 88–94.

“Dr. Berninger said the research suggests that children need introductory training in printing, then two years of learning and practicing cursive, starting in grade three, and then some systematic attention to touch-typing. Using a keyboard, and especially learning the positions of the letters without looking at the keys, she said, might well take advantage of the fibers that crosscommunicate in the brain, since unlike with handwriting, children will use both hands to type. “What we’re advocating is teaching children to be hybrid writers,” said Dr. Berninger, “manuscript first for reading — it transfers to better word recognition — then cursive for spelling and for composing. Then, starting in late elementary school, touch-typing.””

Klass, P. (2016). Why handwriting is still essential in the keyboard age. NY Times, June 20, 2016 http://buildingrti.utexas.org/sites/default/files/documents/WhyHandwritingIsStillEssentialintheKeyboardAge_NY_TIMES.pdf

“Fast and accurate visual recognition of single characters is crucial for efficient reading. We explored the possible contribution of writing memory to character recognition processes. We evaluated the ability of adults to discriminate new characters from their mirror images after being taught how to produce the characters either by traditional pen-and-paper writing or with a computer keyboard. After training, we found stronger and longer lasting (several weeks) facilitation in recognizing the orientation of characters that had been written by hand compared to those typed. Functional magnetic resonance imaging recordings indicated that the response mode during learning is associated with distinct pathways during recognition of graphic shapes. Greater activity related to handwriting learning and normal letter identification was observed in several brain regions known to be involved in the execution, imagery, and observation of actions, in particular, the left Broca's area and bilateral inferior parietal lobules. Taken together, these results provide strong arguments in favor of the view that the specific movements memorized when learning how to write participate in the visual recognition of graphic shapes and letters.” (p.802)

Longcamp, M., Boucard, C., Gilhodes, J. C., Anton, J. L., Roth, M., Nazarian, B., et al. (2008). Learning through hand-or typewriting influences visual recognition of new graphic shapes: behavioral and functional imaging evidence. J. Cogn. Neurosci. 20, 802–815. doi: 10.1162/jocn.2008.20504

Writing to spell/Spelling to write

Spelling and handwriting are different processes; however, they are learned simultaneously, and numerous studies have shown that they interact. Besides the commonly reported presence of a spelling deficit, previous studies have indicated that handwriting difficulties can also be detected in children with dyslexia. Despite this, this issue has not been sufficiently explored. The goal of the study was to investigate the potential handwriting difficulties met by children with dyslexia and how they might relate to spelling difficulties and to basic graphic skills. Twenty children with dyslexia were compared with a chronological age-matched group and reading level-matched group. Participants completed a spelling-to-dictation task of words and pseudowords, an alphabet writing task, and two graphic tasks. Results showed that children with dyslexia were less accurate and slower in preparing and executing the written response than typically developing peers, but they showed the spelling level expected given their reading ability. Children with dyslexia also performed similarly to children with the same reading level in the alphabet and graphic tasks, with both groups being slower and less fluent than the control age group. Altogether, the results suggest the existence of a delay in the development of handwriting and graphic fluency related to the level of reading and spelling skills rather than the presence of a core deficit affecting fine motor skills in dyslexia. In this sense, it seems that reduced literacy skills can affect the development of other skills that are usually enhanced with handwriting practice, such as fine motor skills.” (p.565)

Martínez-García, C., Afonso, O., Cuetos, F. et al. (2021). Handwriting production in Spanish children with dyslexia: Spelling or motor difficulties? Reading & Writing, 34, 565–593. https://doi-org.ezproxy.lib.rmit.edu.au/10.1007/s11145-020-10082-w

“The present study adds to the growing literature showing strong orthographic learning resulting from spelling practice (Conrad, 2008; Shahar-Yames and Share, 2008; Ouellette, 2010). The question remains, beyond individual modality differences, what explains the strong orthographic learning that occurs through spelling practice? Ouellette and Sénéchal (2008) have suggested that the benefit of spelling lies in its highly analytical nature that forces the child to consider each and every sound in a word. In producing the spelling, the child then must focus on each and every letter in their production. The result is that children attend to both the phonology and orthography of the word in more detail than they would need to during reading. Consequently, orthographic learning through spelling may result in representations that are more complete than would be created through reading (Conrad, 2008). As discussed by Perfetti and Hart (2002), while reading may proceed with partial representations, accurate spelling cannot. The analytic nature of spelling also promotes student engagement which can further benefit learning (Ouellette et al., 2013)” (p..

Ouellette, G., & Tims, T. (2014). The write way to spell: Printing vs. typing effects on orthographic learning. Frontiers in Psychology, 5(117), 1-11. http://journal.frontiersin.org/Journal/10.3389/fpsyg.2014.00117/abstract

“This study also lends support to the hypothesis that strong links between the reading and writing systems exist at the word level (word recognition - spelling) and at the text level (comprehension composition)” (p.48).

Berninger, V.W., Abbott, R.D., Abbott, S.P., Graham, S., & Richards, T. (2002). Writing and reading: Connections between language by hand and language by eye. Journal of Learning Disabilities, 35, 39-56.

“Our study has some implications for educational practice. The legibility of children’s writing impacts their educational experiences and outcomes (e.g., Feder and Majnemer, 2007), and thus it is important for educators to understand the causes and possible steps to remediating poor legibility. The present study shows clearly that handwriting legibility improves with spelling ability more so than with the handwriting practice that accrues with years of schooling and maturation. Moreover, our study suggests that it is learning to write the specific orthographic patterns of a given language that is particularly beneficial to handwriting development. Thus, it seems advisable for educators to focus on handwriting legibility, not only in dedicated handwriting lessons, but also during spelling instruction, and for bilingually educated children, and second language/orthography learners, handwriting should be a focus during spelling instruction in both taught languages. In addition, during dedicated handwriting practice, it would be beneficial to include spelling patterns of the language(s) of education. That is, taking the Welsh-English example, while handwriting skills acquired in the context of Welsh literacy lessons should generalize to some extent to handwriting quality in English, our results suggest that English spelling practice may confer even stronger benefits on handwriting in English. Finally, when children present with poor handwriting, this may be a signal to teachers of underlying spelling difficulties.” (p.16)

Caravolas, M., Downing, C. R., Hadden, C. L., & Wynne, C. (2020). Handwriting legibility and its relationship to spelling ability, age, and orthography-specific knowledge: Evidence from monolingual and bilingual children. Frontiers in Psychology, 11, 1097.

“(Traditional spelling programs) do not focus on making the spelling image of a word memorable through the use of all senses by simultaneously presenting grouped words orally, visually and through the motor movements of writing (Hulme 1981; Montgomery 1981; Moats & Farrell 1999) (p.328).

Post, Y. V., & Carreker, S. (2002). Orthographic similarity and phonological transparency in spelling. Reading and Writing. An Interdisciplinary Journal, 15, 317–340.

“However, transcription, including handwriting, is necessary for translating higher-order cognitive processes to spell words and create written text. The brain is a mediating variable during handwriting, spelling, and composing, but other child variables (e.g., interest and motivation) and environmental variables (e.g., instruction) also matter in writing acquisition (Berninger & Richards, 2009). Explicit instruction in letter writing helps developing writers learn to spell words, which are used to communicate ideas and construct the written text to express and elaborate upon ideas (Berninger & Fayol, 2008; Berninger et al., 2009b, c; Hayes, 2009; Hayes & Berninger, 2009).” (p.512)

Richards, T., Berninger, V., Stock, P., Altemeier, L., Trivedi, P., & Maravilla, K. (2011). Differences between good and poor child writers on fMRI contrasts for writing newly taught and highly practiced letter forms. Reading and Writing, 24(5), 493-516.

“In a series of studies, Hulme and Bradley (Bradley, 1981; Hulme & Bradley, 1984; see also Prior, Frye, & Fletcher, 1987) demonstrated the superiority of the Simultaneous Oral Spelling method, in which children learn to spell a word by pronouncing a word written and spoken for them, pronouncing the name of each letter while writing the word, and then repeating the whole word again (see Bradley, 1980, 1981). In a test of the efficacy of the components of the Simultaneous Oral Spelling method, Hulme and Bradley (1984) found that for a normally achieving group of young children, the motoric element of the method seemed to be the important factor (children performed better when writing the words than when using letters on cards to spell them); whereas for an older group of reading-disabled children, the combination of writing and letter naming seemed to be critical. Hulme (1981; Hulme, Monk & Ives, 1987) has carried out an extensive series of studies demonstrating that the motoric activity involved in tracing or writing various stimuli can facilitate young children's memory performance (see also Endo, 1988). These results are congruent with the work on word learning and led Hulme et al. (1987) to tentatively conclude that "It is, perhaps, not unreasonable to speculate that the motor activity involved in learning to write may be beneficial to the development of basic reading skills’” (p. 159).

“ … spelling is usually conceived of as a task that requires a more complete and precise orthographic representation than that required by reading (see Ehri, 1987; Stanovich, 1992). Thus, it may be that reading does not expose subtle differences in the quality of the orthographic lexicon in the same way that spelling does, perhaps because the advantages of redundancy are greater in the former task and thus the existence of precise orthographic representations is less critical” (p.162).

Cunningham, A. E., & Stanovich, K. E. (1990). Early spelling acquisition: Writing beats the computer. Journal of Educational Psychology, 82, 159-162.

Are we doing enough effective writing instruction?

“The teachers’ responses raised some concerns about the quality of writing instruction third- and fourth-grade students receive, as teachers reported spending only 15 min a day teaching writing and students spend only 25 min a day at school writing. While teachers indicated they used a variety of evidence based writing practices in their classroom, a majority of these were applied infrequently. Further, three out of every four teachers reported that their college teacher preparation programs provided no or minimal instruction on how to teach writing.” (p.929)

Brindle, M., Graham, S., Harris, K.R., & Hebert, M. (2016). Third and fourth grade teacher’s classroom practices in writing: A national survey. Reading & Writing, 29, 929–954.

“Teachers should consider explicitly teaching transcription skills for struggling beginning writers using research-based interventions. In this study, students received a research-based early writing intervention that comprised a variety of handwriting and spelling activities, which likely contributed to students’ improved writing performance. However, research-based intervention may not be sufficient for all students all of the time. In this study, data indicated the need for multiple instructional decisions, about 90% of which were to either increase a student’s goal or change instruction. We strongly recommend that teachers collect ongoing progress-monitoring data and use those data to make instructional decisions based on students’ responsiveness to intervention.” (p.14)

Jung, P-G., Kristen L. McMaster, K.L., & del Mas, R.C. (2016). Effects of early writing intervention delivered within a data-based instruction framework. Exceptional Children, 1–17. DOI: 10.1177/0014402916667586

“Research indicates that little time is devoted to writing and teaching writing in primary classrooms. Cutler and Graham (2008) found Years 1–3 teachers allocated more time teaching basic writing skills (e.g., grammar, spelling, and handwriting) than teaching writing processes (e.g., planning and revising). In the time dedicated to basic-skills instruction, teachers reported spending less time teaching handwriting (46 min) than teaching grammar usage and spelling per week (80 min and 74 min, respectively). Similar findings were reported by Dockrell, Marshall and Wyse (2016) when investigating primary-school (K-2) teachers’ practices in the UK, with teachers allocating more time teaching basic writing skills (e.g., spelling and vocabulary) than teaching writing processes (e.g., planning and revising). Malpique et al. (2017) also found that kindergarten children were spending below the recommended 30 min of daily writing practice in kindergarten Australian classrooms and that teachers were spending significantly more time teaching basic writing skills, such as spelling. Statistically significant variations in the amount of writing instruction have been consistently reported across studies, and these findings have been corroborated by limited observational studies (Coker Jr et al., 2018).”  … research with primary students (Graham, Bollinger et al., 2012) suggests that writing instruction in early education should include the teaching of basic writing skills and the teaching of writing processes in the same instructional protocol. Considering the variability in the amount of time for writing and teaching writing, findings from the present study suggested a lack of uniformity in writing instruction in Australian primary classrooms, with potential consequences on students’ writing development. Simultaneously, these findings corroborate the WWC model (Graham, 2018) and the premise that there is variability across writing communities and within writing communities in which writing is developed, potentially associated with community members’ knowledge, beliefs and values about writing (Graham, 2019). Experimental studies are clearly needed to examine the extent to which variability in time for writing and teaching writing is explained by teachers’ beliefs and knowledge about writing instruction.” (p 788, 800)

Malpique, A. A., Pino-Pasternak, D., & Roberto, M. S. (2020). Writing and reading performance in Year 1 Australian classrooms: Associations with handwriting automaticity and writing instruction. Reading and Writing, 33(3), 783-805.

“The multicomponent nature of writing demands that teachers have a comprehensive toolkit of instructional strategies to meet the individual needs of children who experience difficulty with writing. Findings of this review indicate that such tools do exist and that a number of intervention options are supported by high-quality research and strong evidence of effects. These findings are encouraging given the importance of early intervention in preventing long term negative consequences of writing difficulties. In addition to a toolkit of research-based early writing interventions, it is essential to identify students with writing difficulties accurately, diagnose problems, and monitor progress to provide timely and appropriate interventions. … Practitioners may be especially interested in the finding that explicit transcription instruction (handwriting and spelling) leads to improved writing composition. Indeed, such foundational skills–based instruction might be needed for students who struggle with writing, to free up cognitive attention needed to engage in the more complex writing tasks that are currently required in school. These skills are often underemphasized in state standards and popular curricula (e.g., those that use a writer’s workshop approach) yet are essential for many students’ attainment of writing proficiency.” (p.3777)

McMaster, K.L., Kunkel, A., Shin, J., Pyung-Gang Jung, P-G., & Lembke, E. (2018). Early writing intervention: A best evidence synthesis. Journal of Learning Disabilities, 51(4), 363–380.

Does teacher training include evidence-based writing instruction?

“We contacted a random sample of 900 elementary teachers (grades K-5) in the United States to inquire about their use of writing to support students’ learning of classroom content or concepts. Characteristics (i.e., grade level, public v. private school, school locale, school enrollment) of the 150 teachers who responded to our survey were not statistically different from the entire sample surveyed. More than two-thirds (67%) of responding teachers reported receiving minimal to no college preparation on how to use writing to support their students’ learning.” (p. 1)

Gillespie Rouse, A., Kiuhara, S.A. & Kara, Y. (2021). Writing-to-learn in elementary classrooms: A national survey of U.S. teachers. Reading and Writing, https://doi-org.ezproxy.lib.rmit.edu.au/10.1007/s11145-021-10148-3

Writing issues in learning disabilities

“There is a general consensus that writing is a challenging task for students with learning disabilities (LD). To identify more precisely the extent and depth of the challenges that these students experience with writing, the authors conducted a meta-analysis comparing the writing performance of students with LD to their typically achieving peers. From 53 studies that yielded 138 effect sizes, the authors calculated average weighted effect sizes, showing that students with LD obtained lower scores than their peers on the following writing outcomes: writing quality (–1.06); organization (–1.04); vocabulary (–0.89); sentence fluency (–0.81); conventions of spelling, grammar, and handwriting (–1.14); genre elements (–0.82); output (–0.87); and motivation (–0.42).” (p. 1)

Graham, S., Collins, A.A., & Rigby-Wills, H. (2016). Writing characteristics of students with learning disabilities and typically achieving peers: A meta-analysis. Exceptional Children, 1–20, DOI: 10.1177/0014402916664070

“When the focus of the analysis narrows to just weaker writers, the evidence from this meta-analysis does not support the claim that the process writing approach is an effective method for improving quality of writing. The average weighted ES in five studies was 0.29, and not statistically different than zero. … We are not suggesting that the process approach to writing as it was characterized in this review be abandoned. First, we think that this is unlikely to happen. Second, there is much to like about the process approach. This includes its emphasis on the critical role of process in writing, collaboration, personal responsibility, authentic writing tasks, and a supportive learning environment. Instead, we suggest that advocates of process writing instruction integrate other effective writing practices into this approach. There is some empirical evidence that this is a fruitful avenue to pursue. For example, impressive improvements in the writing of average and struggling writers were obtained when the amount of explicit and systematic instruction provided in process writing classrooms was increased (Curry, 1997; Danoff, Graham, & Harris, 1993; MacArthur, Schwartz, & Graham, 1991). These studies involved teaching strategies for planning and revising. Other studies are needed to determine if incorporating other evidence-based practices, such as sentence combining (Graham & Perin, 2007) or spelling and handwriting instruction (Graham, 2010), into the process writing instruction further enhances the power of this approach.” (p.404-405)

Graham, S., & Sandmel, K. (2011). The process writing approach: A meta-analysis. The Journal of Educational Research, 104(6), 396-407.

“Reduced handwriting and graphic fluency and speed might be related to differences in the amount of time that children in the different groups spend writing. As they need more time to complete writing tasks, children with dyslexia may in fact accomplish less amount of handwriting practice than CA children in the same period of time. It is also conceivable that children with dyslexia are exposed to fewer activities involving spelling and writing, either at school or at home. For example, curricular adaptations may be in place that limit the amount of writing that this group of children is demanded to produce in the classroom (e.g., they may be exempt of copying question headings or allowed to use a computer for certain activities). At home, children with low spelling or writing skills are likely to write for pleasure less often, just as reading ability has been shown to be positively related with reading for pleasure (Twist, Schagan, & Hogson, 2007). If, as suggested by some authors (Lust & Donica, 2011), handwriting practice not only increases handwriting fluency but also contributes to enhance other fine motor abilities, then reduced graphic abilities can be expected in children that engage substantially less with writing.” (p.586)

Martínez-García, C., Afonso, O., Cuetos, F. et al. (2021). Handwriting production in Spanish children with dyslexia: Spelling or motor difficulties? Reading & Writing, 34, 565–593. https://doi-org.ezproxy.lib.rmit.edu.au/10.1007/s11145-020-10082-w

And a final word from Berninger:

“Brain Imaging Studies At the end of the 5-year longitudinal study, fifth graders who were right-handed and did not wear braces participated in functional magnetic resonance imaging (fMRI) studies. Children’s brains were scanned while they generated ideas for a composition they wrote when they left the scanner. Differences between good writers and poor writers were observed during idea generation, especially in brain regions associated with working memory (Berninger et al., in press), and during spelling—both in temporary storage of novel words while letter patterns are analyzed in learning new words and in long-term storage of written words with links to other language codes (Richards et al., 2009). Of interest, good, but not poor, spellers activated in primary sensori-motor regions of the brain, consistent with the construct of a graphomotor envelope, analogous to intonational contours for spoken words, which may play an important role in learning to spell via word production (Richards et al., 2009). During sequential finger movements, after controlling for motor movements, brain regions associated with cognitive, metacognitive, language, and working memory functions were robustly activated in good writers but not in poor writers (Berninger, Richards et al., in press; Richards et al., in press). Handwriting (requiring sequential strokes or key presses), spelling (requiring sequential letter production), and composing (requiring sequential word, sentence, and text production) were significantly correlated with the same five brain regions (left superior parietal, right inferior frontal orbital, right precuneus, and right and left inferior temporal) on this sequential finger movement task (Richards et al., in press), consistent with Lashley’s (1951) claim that serial organization of behavior plays an important role in higher-order human cognition. On the fMRI tasks given to good and poor 11-year-old writers only one has been found to be associated with the gender differences—left inferior parietal region during planning of sequential finger movements, which was correlated with behavioral measures of handwriting and spelling. Boys underactivated compared to girls in left inferior parietal region. These and additional studies are extending knowledge of how the writing brain differs from the reading brain (see Berninger & Richards, 2002, Chapters 6 and 9).

Current and Future Directions The research is being extended in both theoretical and practical directions. On the theoretical front, I am exploring these questions: What are ideas? How do ideas in implicit memory outside conscious awareness get translated into explicit memory in conscious awareness in working memory? Why do some students have difficulty translating ideas into language? What does grade-appropriate writing for different genre look like at the word, sentence, and text levels based on children’s writing protocols rather than normed, psychometric tests? How can on-line experimental methods introduced by Fayol and colleagues inform our understanding of time sensitive language production units (e.g., language bursts described by Hayes & Chenoweth, 2006)? … “ … when writing by pen and by keyboard were compared on alphabet writing, sentence constructing, and text composing, children wrote more words and wrote words faster (Berninger, Abbott et al., 2008) and expressed more ideas (Hayes & Berninger, in press) when composing text by pen than by keyboard from second to sixth grade; but for letter writing and sentence constructing, the keyboard often showed advantages (Berninger, Abbott et al., 2008). Children with learning disabilities need explicit instruction in handwriting as well as keyboarding and both accommodations in the form of using a laptop and ongoing explicit instruction in all aspects of writing from planning to translating to reviewing and revising (Berninger, 2006a, 2008a; Berninger, Abbott et al., 2008).” (p.77)

Berninger, V.W. (2009). Highlights of programmatic, interdisciplinary research on writing. Learning Disabilities Research and Practice, 24(2), 69–80.