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Failure to learn: Causes and consequences

Societies value learning. Although the emphasis placed upon it may vary across a community, there is a strong sense that both parents and governments acknowledge a responsibility to ensure the following generation is equipped to deal with the challenges that living in a community entails. Hence we have schools to assist parents in their role.

 So, where should we look when children fail to learn? School learning is a primarily cognitive activity which requires adequate capacity and intention on the part of the learner, and an environment enabling successful interactions to occur. Thus, there are numerous possibilities to account for failure to learn. Determination of cause can be considered from at least two perspectives.

The first approach is to ascertain who the various players (particularly policy makers, parents, and teachers) believe has the major responsibility for children’s learning. The degree to which parents hand responsibility to an education system for qualities such as life skills is always vexed. However, it is generally accepted that schools have the major role in ensuring success in the formal areas of education; in particular, literacy and numeracy.

Another approach is to determine, as precisely as possible, what factors generally produce success in children’s school learning career. While, survey information is based largely upon opinion, the second is best addressed through the accumulation of data. However, the influences on success are likely to be many, entangled, and interacting. What features in common do successful students have? Are there features in common among unsuccessful students? What are the various roles of intelligence, socioeconomic status, early childhood experiences, education systems, school organization, classroom practice, student motivation?

Perspectives vary, depending at least partly upon which feature is most strongly emphasized. For example, many argue that intelligence (the inherited component) is the major determinant of success (Herrnstein & Murray, 1994); whereas, others focus upon social class (Rothstein, 2004); early childhood experiences, especially language (Hart & Risley, 2003; Hirsch, 2013); a child’s motivation (Smith, 1992); character and perseverance (Tough, 2012;) the relationship with the teacher (Smith, 1992); or classroom instruction (Engelmann, 1980) as the crucial component.

Is There Cause For Concern About School Failure, Or Is It Simply A Case Of Being Critical For Its Own Sake?

There is a current public perception that either educational outcomes for students have been declining or that the education system is increasingly less able to meet rising community and employer expectations (Jones, 2012).

Image 1

Figure. Confidence in public schools (Jones, 2012)

Concerns about public education are not new; however, their focus in recent times has shifted. Concerns that have arisen over the last 20 years include apparent national and state test score declines, unflattering international achievement comparisons, the failure of funding increases to produce discernible results, high school dropout rates, and a perception that schooling and work are insufficiently closely aligned (Levin, 1998). The press has displayed increased interest in highlighting these issues, thus raising community awareness. Further, the expanding role for both national and international assessments has brought the issue further to public attention.

What Evidence Is There To Justify Concern?

It is solely a perception by the public that there are serious problems in the education system’s capacity to meet community expectations. In the past, some teacher organisations have argued that these issues should be left in the hands of teachers, and that the school performance of students is quite acceptable compared with that of other nations. Numerous surveys and reports have reached quite different conclusions. Further, concern has been expressed about the academic quality of those accepted into education faculties (Leigh & Ryan, 2006) and of the adequacy of the training of teachers receive to enable them to deal with the diverse needs of the student population.

The U.S. Department of Education reported in 1999 that across the nation 40% of fourth graders failed to demonstrate even partial mastery of the literacy levels required for school success, and among high-poverty schools that figure rose to 70%. Only 1 of 10 students in high-poverty schools read at the Proficient level on the National Assessment of Educational Progress (U.S. Department of Education, 1999). Similar results were presented in the Nation’s Report Card: Fourth-Grade Reading 2000 (U.S. Department of Education, 2001a) in the finding that only 32% of students could be considered proficient.

In the 2011 NAEP, results in writing only about one-quarter of the 8th and 12th graders performed at the proficient level or higher, and much lower for black and Hispanic students (Fleming, 2013). Fewer than one-third of American 8th graders were deemed proficient in science (Sparks, 2013), or could read well enough to comprehend their text books (National Center for Educational Statistics, 2011). In reading, results have shown some improvement since the nineties, but it is clearly difficult to elevate scores dramatically (National Center for Education Statistics, 2011).

Image 2

 In the OECD Programme for International Student Assessment (2009), the US can be seen to be performing below some nations with lesser GDPs (Tucker, 2011).

Image 3

On the 2011 Progress in International Reading Literacy Study (PIRLS), the results (only Grade 4 is assessed) were better than in 2006. The average score for U.S. fourth-grade students (556) was higher than the PIRLS scale average, which is set to 500. Of the 52 other education systems participating, 5 had higher average scores than the United States (Hong Kong-China, Florida (participating as an independent entity), the Russian Federation, Finland, and Singapore). Incidentally, Australian Year 4 students ranked 27th among the 53 nations involved, outperformed by other English-speaking nations such as England, the US and New Zealand. As this is the first time Australia has been involved in PIRLS, some consternation has followed the results.

In a report to the Office of Educational Research and Improvement, Snow (2002) noted that U.S. students are falling behind students in other comparable countries because underdeveloped basic skills limit their attainment in the challenging subject-specific demands of the secondary school curriculum.

Lyon (2001a) observed that of those who receive special assistance because of early reading problems, only 2% will complete a 4-year college program. Further, more than three quarters of the approximately 15% of children who prematurely leave school ascribe major significance to the difficulties experienced in learning to read. The extent of their basic skill deficit is evident in the U.S. Department of Education (1999) finding that 60% of the unemployed lack the basic skills required to successfully be trained for high tech positions.

Even the basic attainments of many high school graduates fall below community expectations. Most employers and college professors say that high school graduates generally display poor or only fair basic skills, such as written expression, spelling, and math (Johnson & Duffett, 2002). The American Management Association Survey on Workplace Testing (American Management Association, 2001) found that about one third of assessed applicants lacked the basic skills necessary to perform the jobs they sought, and 85% of the companies did not hire such applicants.

Even at the tertiary level, problems in the basic skill levels of entrants were of concern, noted The Condition of Education Report (U.S. Department of Education, 2002a). Whilst the problems are not restricted to entrants from minority groups, such candidates do tend to do less well than their peers. A report by the U.S. Department of Education (2002b) indicated that, on average, black tertiary students receive lower academic scores than do their white counterparts. Numerous universities have found it necessary to institute programs of teaching basic skills, literacy in particular, to their newly enrolled students. However, their attempts are not expected to have a great impact.

Partly because of these worrying issues in higher education, and also because of the increasingly diverse population in schools, there has been an elevated pressure on elementary and secondary schools to improve their instructional effectiveness.

How Do Some In The Education Profession Attribute Responsibility?

Wade and Moore (1993) asked teachers the question, “Who is to blame for students’ failure to learn?” That 65% of teachers blamed child characteristics, and 32% of teachers blamed the home situation would probably be a surprise to those parents who view schools as the major influence on learning. Only 3% of teachers blamed teachers or the school system for learning problems. Prawat (1992) found a common belief among teachers that “student interest and involvement constitutes both a necessary and sufficient condition for worthwhile learning” (p. 389). Nuthall (2004) reported a similar finding—that “Within the professional culture of teaching, it is commonly believed that if something is taught (which usually means explained or demonstrated), it is automatically learned. If it is not learned, then the problem lies in the inadequacy of the student’s ability, motivation, or persistence, not in the ineffectiveness of the instruction” (p. 274).

Alessi (1988) surveyed 50 school psychologists, proposing five possible factors that could explain lack of learning.

They were:

1. The curriculum

2. Ineffective teaching and/or behavior management practices

3. Ineffective school management practices

4. Lack of home-based support by parents

5. Physical and/or psychological problems affecting the child.

The school psychologists produced 5,000 reports on children’s learning problems in that school year. These were later coded to determine to what factors their reports assigned the students’ educational problems. The attributions in their reports as causes of failure to learn were:

1. Curriculum factors? None.

2. Inappropriate teaching and behavior management practices? None.

3. School administrative factors? None.

4. Parent and home factors? 10–20%.

5. Factors within the child? 100%.

These two findings are surprising given that schools are considered the teaching arm of the community. There is no question that a great deal of expectation rests on the school system. However, it could be that the task of success for all appears to those within it as an impossible attainment for a school system, at least with the resources the community is prepared to devote to the task. Perhaps the responses above are simply an understandably defensive response to a situation in which those in the education system come to terms with their inability to achieve all the community’s goals. Alternatively, it could be that teachers have a different perspective to that of the rest of the community regarding the process through which learning occurs.

Disturbing Children’s Naturally Unfolding Development

Rousseau believed that children had an innate developmental script which would lead them (though perhaps at differing rates) to competence. Thus, unfettered maturation would allow the child to develop knowledge unaided (Weir, 1990). His ideas gained scientific respectability in the 19th century when they were seemingly supported by a theory of evolutionary biology. This long since discredited theory asserted that the evolutionary journey from amoeba to human infant was replayed in every pregnancy, and the wisdom and knowledge of the parents (and of necessity, beyond) was present in the brain of the new generation. In Rousseau’s view humans were noble by nature; ignobility was evoked by societal interference. His argument that society should not interfere in the natural development of children generally was paralleled by his view of the role of education. “Give your pupil no lesson in words, he must learn from his experience” (Rousseau, 1964 cited in Weir, 1990, p. 28).

In more recent times, analogous expressions of the belief system including developmentalism, developmentally appropriate practice, and constructivism have been popular (Stone, 1996). The whole language philosophy that assigns to the teacher the role of concerned facilitator, and which decries teacher directed instruction as harmful or unproductive can be readily sourced to this romantic Rousseauian view of humans. “We cannot teach another person directly; we can only facilitate his learning” (Rogers, 1961, p. 27). Through providing a range of stimulating activities in a nonthreatening atmosphere it is presumed that the child’s natural tendency to learn will be elicited, and that learning will then occur. Emphasis is on creativity, imagination, and general problem solving rather than on prescribed skills and knowledge. This perspective has been widely promulgated through education faculties over the past 30 years through the whole language philosophy. Whole language has been the predominant education model in schools over that period (Hempenstall, 1997; Tunmer & Greaney, 2010; Turbill, 2002).

A problem with this view is that it is based upon belief rather than data. The assumption is that the approach is necessarily correct, so data supporting the approach is unnecessary (Weaver et al., 1997). The dispute with those who focus upon instruction is not actually about technique; it is much more fundamental—about the nature of humans and how children learn.

When pressed, protagonists will argue that since some children do appear to thrive in unstructured settings, there must be a cause other than the instructional approach to explain the phenomenon of student failure. The extreme example of this philosophy in practice was Summerhill, established by A. S. Neill in 1921. In this school, students were free to determine in which, if any, activities they would like to engage. Through this freedom the child would naturally make choices in the best interests of his development. “My view is that the child is innately wise and realistic. If left to himself without adult suggestion of any kind, he will develop as far as he is capable of developing” (Neill, 1974, p. 20). Contrary to this belief, a study by Lepola, Salonen, and Vauras (2000) noted that there were no motivational differences between subsequently successful and unsuccessful students prior to school entry. Similar results were noted by Shaw (2008) and Reschly (2010). Strong motivation evolves out of reading success, and weakened motivation often follows a lack of such success (Morgan, 2008).

On a related concept, a whole industry has developed around the idea that a student’s self-esteem must first be strong if learning is to take place. The outcome of this belief is that time is used in class attempting to elevate self-esteem as a prerequisite to attendance towards academic issues. Again, this belief has flourished for a long time without empirical support. Results, now available from numerous large scale studies (Baumeister, Campbell, Krueger, & Vohs, 2004), do not indicate that attempting to raise self- esteem is helpful to students. In fact, there are findings indicating that artificially elevating self-esteem may lower subsequent academic performance and possibly elicit narcissism. At the very least, the activities waste precious time that may have been spent more productively in providing intensive instruction for struggling students. As one effective teacher commented, “When a child is struggling in my class, I don’t alter the way I smile—I alter his curriculum.”

Weir (1990) was critical of the progressive perspective because it allocated the responsibility for inadequate student achievement to the individual and the home. She believes that advocates of this approach have a responsibility to provide evidence for naturally unfolding development to justify the use of such indirect process-oriented education.

Nuthall (2004) commented “Within the professional culture of teaching, it is commonly believed that if something is taught (which usually means explained or demonstrated), it is automatically learned (Gess-Newsome & Lederman, 1999; Nuthall, 2001a; Oser & Baeriswyl, 2001). If it is not learned, then the problem lies in the inadequacy of the student's ability, motivation, or persistence, not in the ineffectiveness of the instruction (Fischler, 1994; Floden, 1996)” (p.277).

Delpit (1986; 1988) has written passionately about the problems of black students in the education system. She was especially concerned about the effects on minority groups of Rousseau’s modern incarnation— progressive education. Rather than this perspective being supportive of personal growth, she considers the approach disempowering. “Adherents of process approaches...create situations in which students ultimately find themselves held accountable for knowing a set of rules about which no one has ever directly informed them” (Delpit, 1988, p. 287).

The whole language model has been discredited by the results of theoretical and empirical research (Faust, & Kandelshine-Waldman, 2011; Hattie, 2009; Moats, 2000; Moats, 2007), and by neuroscience (Dehaene, 2009).

Are The Students Who Do Not Perform To Expectations Learning Disabled?

According to the Office of Educational Research and Improvement (2001), almost 40% of students nationally read below a basic level; that is, they struggle to comprehend even the simplest of texts. For minority groups, these figures are even more alarming—63% of African American fourth graders, 60% of children in poverty, and 47% of children in urban schools fell into this category. In New York state in 2001, only 30% of students passed the eighth- grade English test (Hartocollis, 2002), and nearly 65% of students were unable to compute at grade level (Campanile, 2002).

Apart from the debate about whether a learning disability category really exists or whether it serves a useful function (U.S. Department of Education, 2001b), there is consensus that such a category can account for the failure of no more than about 5% of the population (U.S. Department of Education, 1995). In fact, there is concern that the expanding learning disability category may serve to mask the major issue in educational failure. “Learning disabilities have become a sociological sponge to wipe up the spills of general education. It’s where children go who weren’t taught well” (Lyon, as cited in Colvin & Helfand, 1999). According to the Commission on Excellence in Special Education (2002), about 50% of those in special education programs are identified as having a specific learning disability, a category that has expanded by 300% since 1976. Of those students, 80% are so classified because they haven’t been effectively taught how to read. Further, few children placed in special education programs make adequate progress or close the gap on their peers in literacy and school attainment.

The Commission (2000) further reported that the failure of students with disabilities to complete high school occurs at twice the rate of their nondisabled peers, and enrolment rates in higher education remain 50% lower than enrolment among the general population. So, it appears that the educationally disadvantaged include those in the minority groups that one would anticipate—those in poverty, minority race groups, those with disability, and those with English as a second language. Yet, the high figures suggest that a proportion of struggling students do not arise from those groups, but appear unexpectedly.

When the head of the reading programs at the federal government’s National Institute of Child Health and Human Development, G. Reid Lyon, testified to the Senate Committee (Lyon, 1998), he pointed out that 50% of the children reading below the basic level in California were from the homes of parents who were college graduates. In fact, the children of college-educated parents in California scored lowest with respect to their national cohort. These data underscore the fact that reading failure is a serious problem and cannot simply be attributed to poverty, immigration, or the learning of English as a second language.

In mathematics, the TIMSS study observed that even bright students were lagging in comparison with those in high achieving countries. Interestingly, the countries that did very well in math and science had “a common, coherent, rigorous curriculum” (Schmidt et al., 2002, p. 16).

This is not to suggest that there aren’t students with learning disabilities. However, Johnson (2003) underlines Lyon’s (as cited in Colvin & Helfand, 1999) perspective in pointing out that the unrealistically elevated rates of diagnosis of learning disability make it unlikely that the level of intensive systematic intervention they require can be delivered. Effective levels of intervention for this group are more likely to be achieved if the quality of initial instruction in literacy reduces the number subsequently diagnosed with learning disability. For example, Johns (2001) reported that the number of pupils referred to special education programs in a Washington school was reduced by 30% after Reading First’s introduction. More recently are the early signs that the increasing use of the Response to Intervention model throughout the US is leading to a reduction in the number of students diagnosed as having a learning disability (Cortiella, 2011).

The Impact Of Research On Practice: A Long-Standing Problem For Education

A common feature in the debate about progressive education is that practices remain impervious to the outcomes of empirical research. The failure of research-based knowledge to have an impact upon educational decision makers has impeded growth in that profession for a long time (Carnine, 1995b; Hempenstall, 1996; Marshall, 1993; Stone, 1996). More than 30 years ago, Maggs and White (1982) wrote despairingly, “Few professionals are more steeped in mythology and less open to empirical findings than are teachers” (p. 131).

Lindsley (1992) was quite scathing in addressing the general question of why effective teaching tools aren’t widely adopted. He considered that teachers have been seduced by the natural learning approaches.

Most educators have bought the myth that academic learning does not require discipline—that the best learning is easy and fun. They do not realize that it is fluent performance that is fun. The process of learning, of changing performance, is most often stressful and painful (p. 22).

Gable and Warren (1993) noted that the potentially valuable role of behavioral science in education has been largely ignored by decision makers and even by many practitioners. They noted Carnine’s (1991) lament that decision makers lack a scientific framework and are inclined to accept proposals based on good intentions and unsupported opinions. Carnine (1995a) also points to teachers’ lack of training and direction in seeking out and evaluating research. For example, he estimates that fewer than 1 in 200 teachers are experienced users of the ERIC educational database.

Heward (2003) argues that the failure of the profession to attend to research has led to 10 misconceptions about teaching that have become entrenched and that distract teachers from effective approaches to teaching struggling students. The misconceptions are:

1. Structured curricula impede true learning.

2. Teaching discrete skills trivializes education and ignores the whole child.

3. Drill and practice limits students’ deep understanding and dulls their creativity.

4. Teachers do not need to (and/or cannot, should not) measure student performance.

5. Students must be internally motivated to really learn.

6. Building students’ self-esteem is a teacher’s primary goal.

7. Teaching students with disabilities requires unending patience.

8. Every child learns differently.

9. Eclecticism is good.

10. A good teacher is a creative teacher. (p. 7)

Fister and Kemp (1993) considered several likely obstacles to research- driven teaching, important among them being the absence of an accountability link between decision makers and student achievement. Such a link was unlikely until recently, when regular mandated state or national test program results became associated with funding. They also apportion some responsibility to the research community for failing to appreciate the necessity nexus between research and its adoption by the relevant target group. The specific criticisms included a failure to take responsibility for communicating findings clearly, and with the end-users in mind. Researchers have often validated practices over too brief a time-frame, and in too limited a range of settings to excite general program adoption across settings. Without considering the organizational ramifications (such as staff and personnel costs) adequately, the viability of even the very best intervention cannot be guaranteed. The methods of introduction and staff training in innovative practices can have a marked bearing on their adoption and continuation.

Meyer (1991, as cited in Gable & Warren, 1993) also blames the research community for choosing restricted methodology (e.g., single subject design), and for being too remote from classrooms. She argued that greater teacher interest will not eventuate until the credibility of research is improved. On the other hand, perhaps it is the tendency of empiricists to place caveats on their findings (as opposed to the wondrous claims of ideologues and faddists unconstrained by scientific ethics) that makes teachers and decision makers wary of empirical evidence.

Fister and Kemp (1993) argued that researchers often failed to meet their own criterion by not incorporating research-validated staff-training procedures and organizational analysis in their strategies for promoting program adoption. Their final criticism involved the rarity of the establishment of model sites exemplifying excellent practice. When prospective adoptees are able to see the reality rather than the rhetoric of a program they are more likely to take the (often uncomfortable) steps towards adoption. In addition, it is possible to discuss with on-site teachers the realities of being involved in the innovation.

Woodward (1993) pointed out that there is often a culture gulf between researchers and teachers. Researchers may view teachers as unnecessarily conservative and resistant to change, whereas teachers may consider researchers as unrealistic in their expectations and lacking in understanding of the school system and culture. Teachers may also respond defensively to calls for change because of the implied criticism of their past practices, and the perceived devaluation of the professionalism of teachers (in that other professions are determining their teaching practices). Leach (1987) argued strongly that collaboration between change-agents and teachers is a necessary element in the acceptance of novel practice. In his view, teachers need to be invited to make a contribution that extends beyond solely the implementation of the ideas of others. There are some positive signs that such a culture may be in the early stages of development. Viadero (2002a) reports on a number of initiatives in which teachers have become reflective of their own work, employing both quantitative and qualitative tools. She also notes that the American Educational Research Association has a subdivision devoted to the practice.

Hence there are at least three groups with whom researchers need to be able to communicate if their innovations are to be adopted. At the classroom level, teachers are the focal point of such innovations and their competent and enthusiastic participation is required if success is to be achieved. At the school administration level, principals are being given increasing discretion as to how funds are to be disbursed; therefore, time spent in discussing educational priorities and cost-effective means of achieving them may be time well-spent, bearing in mind Gersten and Guskey’s (1985) comment on the importance of strong instructional leadership. At the broader system level, decision makers presumably require different information and assurances about the viability of change of practice (cost/benefit being fundamental).

Perhaps because of frustration at the problems experienced in ensuring effective practices are employed across the nation, we are beginning to see a top-down approach, in which research- based educational practices are either mandated as in Great Britain (Department for Education and Employment, 1998) or a prerequisite for funding as in the 2001 No Child Left Behind Act (U.S. Department of Education, 2002c). Whether this approach will be successful in changing teachers’ practice remains to be seen. In any case, there remains a need to address teachers’ and parents’ concerns regarding classroom practice in a cooperative and constructive manner. Vilification, real or perceived, is likely to produce inertia or outright resistance. Over the past 20 to 30 years there has developed a consensus among empirical researchers about a number of issues crucial to education, and a great deal of attention is now directed at means by which these findings can find fruition in the classroom (Gersten, Chard, & Baker, 2000). Carnine (2000) asks why it is that education has appeared impervious to effective practices, and examines what it would take to make education more like medicine—a profession now (though it wasn’t always so) strongly wedded to research as a powerful contributor to practice. Perhaps it would be instructive to consider how other professions, like medicine, have addressed the issue of a research–practice synthesis.

The term “evidence-based medicine” was popularised during the 1990s. The intention was to enable practitioners to gain access to knowledge of the effectiveness and risks of different interventions before choosing whether or not to implement them, using as a guide reliable estimates of benefit and harm (Sackett, McRosenberg, Muir Gray, Haynes, & Richardson, 1996). The intent of evidence-based medicine is to make available to practitioners the complex information from a large number of individual studies. Practitioners would not have the time (and perhaps expertise) to enable the drawing of appropriate conclusions about risk–benefit estimates.

Donald (2002) described four main steps. First, pose a structured question about the target population, outcomes, and the intervention of interest. Second, perform a literature search for the data relevant to the question. Third, assess the data, based upon established criteria for methodological rigor and relevance to the question. Fourth, describe and analyze the resulting data to answer the relevant question.

The contrast with the manner in which a teacher is trained to address a student’s spelling problem is indeed stark. Unfortunately, in another parallel with education, fewer than 10% of studies are usually able to be included because of the methodological failings of much of the medical research. Despite the current imperfections, there is strong support within the medical profession for this direction, because it offers a cooperative system that will be in a constant cycle of improvement, thereby providing better health outcomes for their patients. It is further instructive to consider the profession’s preparedness to surrender their clinical creativity in the interests of their patients.

In a similar vein to the medical profession, the American Psychological Association (Chambless & Ollendick, 2001) introduced the term “empirically supported treatments” (ESTs) to clinical psychology as a means of focussing attention on the issue of effective psychotherapy. Through examination of research evidence, the Division 12 (Clinical Psychology) Task Force on Psychological Interventions arrived at three classes of interventions that could be applied to any treatment for any particular psychological problem. The criteria for a treatment to be considered well established was efficacy through two controlled clinical outcomes studies, or a large series of controlled single case design studies; the availability of treatment manuals to enhance treatment fidelity and reliability; and the provision of clearly specified client characteristics. A second level involved criteria for probably efficacious treatments—criteria requiring fewer studies, and/or a lesser standard of rigor. The third category comprised experimental treatments, those without sufficient evidence to achieve probably efficacious status.

Initially included as well-established treatments were 22 treatments for 21 different syndromes and seven probably efficacious treatments for seven disorders. With a couple of exceptions, all the well-established treatments were behavioral or cognitive–behavioral. The exceptions were family education programs for schizophrenia and interpersonal therapy for bulimia and for depression. Similarly, all but one probably efficacious treatment were behavioral, the exception being brief psychodynamic therapy.

The EST emphasis on empiricism also has obvious implications for other fields, such as education, in which decisions about the choice of approach have not previously been based upon any mutually agreed criteria. There are interesting similarities between the response of some psychotherapists to the EST initiative and that of some educators to the “reliable replicable research” criterion for federal funding in literacy programs in the USA.

Some of the objections raised have been that ESTs should be ignored because this effort has been the work of a powerful lobby of biased individuals within the APA. Critics view qualitative rather than quantitative research as the appropriate approach to research into psychotherapy. To be considered a well-established treatment requires a treatment manual, and their use (it has been argued) leads to poor quality psychotherapy by diminishing personal judgement. Another perspective rejects ESTs because every client has different needs, and the use of single treatments based upon problem analysis cannot meet their needs. Some have asserted that there is no discernible difference in efficacy among the various forms of psychotherapy, thus ESTs are not relevant. Finally, some consider EST research as irrelevant to clinical practice as it originates in controlled clinical settings, and does not translate well to the real world. The degree to which documented treatments can be implemented in settings outside of those from which they originated are now being assessed in large scale effectiveness studies under the auspices of the National Institute of Mental Health (NIMH).

The criticisms emanating from some in the education community (Goodman, 1998; Weaver, 1988) to the drive towards research-based practice bear remarkable similarity. “It seems futile to try to demonstrate superiority of one teaching method over another by empirical research” (Weaver, 1988, p. 220). Clearly, the education profession has some distance to travel before reaching the stage of these other professions. Unless education faculties begin to change their philosophies of practice and provide teachers with the knowledge and attitudes consistent with empiricism, student-beneficial changes emanating from within the profession are unlikely (Lyon, 1999; Mather, Bos, & Babur, 2001).

Anatomy Of Educational Decline

What Does Empirical Research Contribute to the Failure-To-Learn Discussion?

The problems with basic skills begin early but become entrenched. Contrary to the hope that initial slow progress is merely a maturational lag to be redressed by a developmental spurt at some later date, typically, even relatively minor delays tend to become increasingly major over time (Stanovich, 1993). It appears that problems in basic educational skills, commencing early in an individual’s life, can have snowballing negative effects, and the consequences are felt over a lifetime and in numerous domains of the individual’s life. By what mechanism might this occur?

Sequence of Events

Several studies, such as that by Farkas and Beron (2001), have noted that students entering school with underdeveloped vocabularies are highly likely to fail in their basic skill development, yet they also found the effects could be countered by intensive early school-based assistance. Lyon (2001b) pointed out that such vocabulary deficits are more likely among disadvantaged children whose parents may be unable to provide them with the early literacy experiences that provide many other students with a flying start. These experiences include reading to children, but even earlier major differences in language were noted by Hart and Risley (1995) in the amount and quality of conversation between parents and children from professional, working class, and welfare families.

Arguably, the area of literacy development, and in particular, initial progress in reading, represents the fulcrum upon which students’ educational progress balances. Of great concern is not only the continuing struggles of slow starters, but also the potentially widening gap between slow starters and fast starters. There is ample evidence (America Reads, 2001; Ceci, 1991) that students who do not make good initial progress in learning to read find it increasingly difficult to ever master the process. Stanovich (1986, 1988b, 1993) outlined a model in which problems with early phonological skills lead to a downward spiral where all other school skills and even higher cognitive skills are eventually affected by slow reading development. This effect may not apply to all students who struggle and should not be confused with a view that it is a student’s internal deficit that prevents their achievement of success.

Arguably, the area of literacy development, and in particular, initial progress in reading, represents the fulcrum upon which students’ educational progress balances.

Stanovich (1986) used the label Matthew Effect (after the Gospel according to St. Matthew) to describe how, commencing at the initial stages of reading, the rich tend to become richer and the poor become poorer. Children with a clear understanding of the sound structure of spoken words (phonological awareness) are well placed to make sense of our alphabetic system. Their rapid development of spelling-to-sound correspondences allows the development of independent reading, high levels of practice, and the subsequent fluency that is critical for comprehension and enjoyment of reading.

Moats (1996) also argued that it is largely the initial insensitivity to word structure that undermines students’ capacity to learn the code of written English without focussed instruction. This fundamental deficit consequently inhibits the learning of word meanings, reading comprehension, spelling, written expression, and even the motivation to engage in subsequent language- based learning. In their study, Chapman, Tunmer, and Prochnow (2000) reported a negative self-concept among struggling readers arising within the first two years of their schooling.

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Figure. Anatomy of educational decline (Hempenstall, 1996)

The decline for children without good phonological awareness is exacerbated because they do not participate in reading as much as do their peers. Allington (1984), in a study of Grade 1 students, noted vastly different reading-exposure ratios. In his study, the number of words read per week ranged from 16 in the less skilled group to 1,933 in the upper group. Exacerbating this problem of differential exposure is the finding that struggling readers are often presented with reading materials that are too difficult for them (Stanovich, 1986). Slow, halting, error-prone reading of difficult material, unsurprisingly, militates against comprehension and leads to avoidance of reading activities and further disadvantage.

There is evidence that vocabulary development from about Year 3 is largely a function of volume of reading (Nagy, 1998; National Reading Panel, 2000; Stanovich, 1988b). Nagy and Anderson (1984) estimate that, in school, struggling readers may read around 100,000 words per year; whereas, for keen mid-elementary students, the figure may be closer to 10,000,000, that is, a 100 fold difference. For out of school reading, Fielding, Wilson, and Anderson (1986) suggested a similar ratio—indicating that children at the 10th percentile of reading ability in their Year 5 sample read about 50,000 words per year out of school, while those at the 90th percentile read about 4,500,000 words per year.

Language skills such as vocabulary knowledge, general knowledge, syntactic skills, and possibly even memory, rely heavily on reading for their development. These skills impinge on most areas of the curriculum and hence what began as a narrow deficit becomes progressively larger, amplified by the negative motivational consequences of failure. A study by Juel (1988) reported a probability that a poor reader in Year 1 would still be so classified in Year 4 was 0.88, a finding supported by the Jorm, Share, MacLean, and Matthews (1984) longitudinal study. A performance difference in reading of 4 months in Year 1 had increased to 9 months in Year 2 in favour of the phonemically aware group (who had been matched in kindergarten on verbal IQ and sight word reading), over a low phonemic awareness group.

Lyon (1998) provides a sobering reminder of the importance of identifying and intervening early in a student’s educational career.

However, we have also learned that if we delay intervention until nine-years-of-age (the time that most children with reading difficulties receive services), approximately 75% of the children will continue to have difficulties learning to read throughout high school. To be clear, while older children and adults can be taught to read, the time and expense of doing so is enormous. (para 34)

The notion that even intellectual development can be markedly influenced by literacy attainment is not new, but empirical research is increasingly supportive (Ceci, 1991; Fletcher, Francis, Rourke, Shaywitz, & Shaywitz, 1993; Stanovich, 1993). Further support from a longitudinal study in New Zealand is provided by Share, McGee, and Silva (1989), and Share and Silva (1987). They matched reading disabled and nondisabled groups on their vocabulary scores attained at age 3. At age 11, marked differences were noted in vocabulary, listening comprehension, and general language skills in favour of the nondisabled group. Using a hierarchical multiple regression, they demonstrated that the changes in IQ between ages 7 and 13 were predicted by changes in reading over that period. Growth in reading ability between the ages of 7 and 13 accounted for a significant proportion of the IQ score variability even after attributing variability due to IQ and reading ability at age 7.

The Hoskyn and Swanson (2000) meta-analysis also offers support for this perspective, noting the development of generalised cognitive deficits in older children with a history of significant reading problems. This apparent cognitive decline is thought to be consequent upon the absence of normal language stimulation (e.g., vocabulary) provided by facile and regular reading.

There are also other psychological consequences. Behavior problems in children with learning difficulties are about 3 times the average by the time they reach 8 years of age (Mash & Wolfe, 2002). Young boys, in particular, are at 3 times the risk of displaying high levels of depressed mood than the average (Maugban, 2003). By the time they reach high school, struggling readers report neither the confidence nor (in many cases) the desire to engage in reading. Their capacity to cope with the curriculum is compromised by poor literacy and a sense of hopelessness, anxiety, and low motivation (Peterson, Caverly, Nicholson, O’Neal, & Cusenbary, 2003).

Binder (1996) describes as “cumulative dysfluency” the gradual loss of contact with the curriculum that eventuates when students whose basic skill deficits should have been evident to astute observers in the early grades are left to their own devices, or enrolled in ineffectual programs. As complexity increases in secondary curriculum subjects such as science and history, some students reach a ceiling—the requisite advanced abilities in comprehension and reasoning failing to develop in concert with the demands. Lewis and Paik (2001) make a similar observation that adequate development of basic skills is essential if students are to find success at whatever the grade and in any school subject. Dr. Grover Whitehurst, Director of the Institute of Education Sciences, U.S. Department of Education (2003), noted, “Statistically, more children suffer long-term life- harm from problems in learning to read than from parental abuse, accidents, and all other childhood diseases and disorders combined” (para 1).

The implications of these findings are both disturbing and instructive. That there is increasing agreement about a specific locus and sequence of much inadequate reading progress is encouraging. Early intervention has the potential to preclude failure with its attendant personal and social cost. That an initially modular insensitivity or inexperience rapidly broadens into generalised language, intellectual, and motivational deficits is worrying for those attempting to alleviate the reading problems of students in mid- elementary school and beyond. In these cases, the consequences of the reading failure may remain even if the cause of the reading problem has been successfully addressed. For teachers trying to provide effective remedial literacy assistance to such pupils, the Matthew effect helps explain (a) why progress is often painfully slow, (b) a lack of significant change in general classroom performance consequent upon improved reading, (c) why only presenting a dedicated phonemic awareness program with older children may not necessarily have a powerful impact.

Some further study outcomes: Does catchup occur?

“This survey showed the difficulty of closing students’ gaps in the middle years (from 4th to 8th grade). Fewer than 10%” of far off track students (more than one standard deviation below benchmark in 4th grade) caught up in the four years to 8th grade. Between 8th grade and 12th grade only 6% of those far off track students in 8th grade reached benchmark by 12th grade”.

Dougherty, C. (2014). Catching up to college and career readiness: The challenge is greater for at-risk students. ACT Research & Policy, May 2014. 1-12. Retrieved from http://www.act.org/research/policymakers/pdf/CatchingUp-Part3.pdf


“As early as first grade, a pattern is established whereby children with strong early reading skills engage in reading more than their less skilled peers. Through reading, they strengthen not only their reading skills but also reading-related and cognitive skills such as spelling, vocabulary, listening comprehension, and declarative knowledge. The roots for this productive habit can be seen in early exposure to print through caregiver shared reading experiences and effective early reading instruction in which strong decoding skills are established. Some researchers have conceptualized this relationship between strong reading skills, engagement in reading, and development of reading-related and cognitive abilities as a ‘‘virtuous circle’’ (Snowling & Hulme, 2011). Other researchers have described the process by which children who fail to establish early reading skills find reading to be difficult and unrewarding, avoid reading and reading-related activities, and fail to develop reading-related and cognitive abilities as a ‘‘vicious circle’’ that is disastrous for their cognitive development and school achievement (Pulido & Hambrick, 2008). An early start in learning to read is crucial for establishing a successful path that encourages a ‘‘lifetime habit of reading’’ (Cunningham & Stanovich, 1997, p. 94) and for avoiding the decline in motivation for reading that can have devastating effects on reading growth and cognitive development over time” (p.209-210).

Sparks, R. L., Patton, J., & Murdoch, A. (2014). Early reading success and its relationship to reading achievement and reading volume: Replication of ‘10 years later’. Reading and Writing, 27(1), 189-211.


“A major goal of Tier 2 or secondary intervention is to allow the majority of students with learning (e.g., reading) difficulties to attain grade-level expectations. If students with below-grade- level performance are to catch up with normally developing students, their rate of growth must be accelerated; simply learning at an average rate will only maintain the deficit. Thus, Tier 2 interventions must be intensive enough to not only improve students’ performance, but to actually enable students with learning difficulties to progress at rates that are faster than the learning rates of average students. At the same time, these interventions must be feasible for teachers to implement and sustain” (p.433).

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.


‘‘Direct instructional time is proportional to their [children’s] deficiency. The greater the need, the more time they get.’’ Further, they caution that ‘‘catch up growth’’ requires more time and better quality instruction. Ikeda and colleagues cautioned that in most schools within the Iowa Heartland district, ‘‘interventions were not sufficiently rigorous to impact reading performance’’ (p.20).

Al-Otaiba, S., Calhoon, M. B., & Wanzek. J. (2010). Response to intervention: Treatment validity and implementation challenges in the primary grades and beyond to middle school. In Thomas E. Scruggs, Margo A. Mastropieri (Eds.). Advances in learning and behavioral disabilities, Volume 23; Learning and Literacy. Emerald Publishing.


“A child with a reading disability who is not identified early may require as many as 150 – 300 hours of intensive instruction (at least 90 minutes a day for most school days over a 1 – 3 year period) if he is going to close the reading gap… between himself and his peers. And, of coursethe longer identification and effective reading instruction is delayed, the longer the child will require to catch up” (p.259)

Shaywitz, S. (2003). Overcoming dyslexia: A new and complete science-based program for reading problems at any level. New York: Alfred A. Knopf.


Intervention Research

Many researchers (Adams, 1990; Ball, 1993; Ball & Blachman, 1991; Blachman, 1994; Bradley & Bryant, 1983; Byrne & Fielding-Barnsley, 1989; Catts, 1991; Cunningham, 1990; Felton, 1993; Foorman, Francis, Novy, & Liberman, 1991; Hatcher, Hulme, & Ellis, 1994; Juel, 1993; Simmons, 1992; Stanovich, 1986, 1988a, 1992, 1993; Torgesen, 1998; Torgesen, Wagner, & Rashotte, 1994) have noted the cost- beneficial effects of early intervention and stressed the importance of primary prevention for a variety of reasons— from pragmatism to social justice.

Although early intervention has long been regarded as logical—even programs as intensive as Head Start for disadvantaged children have not achieved the outcome success that was sought. The reasons may relate to the varying quality of educational programs offered, and to the difficulty in overcoming very early language disadvantage. Even recent efforts to overcome some of the deficits of former initiatives have been less successful than hoped, with initial positive effects washing out by the end of 3rd Grade, according to a Head Start Impact Study (Puma et al., 2012). A possible reason for this involves the increasingly recognised expectation that, for some students, interventions must be early, intensive, and of longer duration than has previously been offered (Vaughn, Denton, & Fletcher, 2010).

In the Condition of Education (U.S. Department of Education, 2002a) report it was noted that there has been an increase in enrolment rates for 3- to 5-year-old children in childhood education programs, and there has also been a recognition that these programs, when well designed, can help compensate children for a language disadvantage in early childhood (Hart & Risley, 1995). This initiative involves increasing the educational elements in preschool programs that have formerly been considered an inappropriate forum for such activities. The intention was to elicit a national impetus to begin systematically teaching children important early learning skills, even before they are old enough to read. Such early intervention initiatives are crucial if the community expectations are to be met. Without such large-scale programs, the trajectory for students with early disadvantage is sadly predictable.

The value of empirical research since the beginning of Head Start has been in narrowing the focus of early intervention for reading—from a broad range of “readiness” activities to a specific emphasis on (a) phonemic awareness as a screening tool and a possible intervention focus, and (b) the critical role of systematic, explicit phonics in initial reading instruction (National Reading Panel, 2000). Further, the evidence indicates the value of effective systematic instruction as a means of enhancing the learning of basic skills for all students, not only for those with disadvantage.

Why Systematic Instruction Is Important

What lessons have we learned in recent times about how to substantially improve education rather than simply engage in the process of frequent change? Education has always been at the mercy of new ideas, but without broad-scale assessment and scientific data analysis it was not easy to detect whether any changes enhance or inhibit student progress. Even the belief that education can influence a student’s life trajectory is often questioned (Jencks et al., 1972). The Coleman Report (Coleman et al., 1966) and other studies deflated many in the educational community when it was reported that what occurred in schools had little impact on student achievement. It was argued that the effects on educational outcomes of socio-economic status (SES), genetic inheritance, early childhood experiences, and subsequent family environment vastly outweigh school effects. That being the case, there would be little point in stressing a particular curriculum model over any other since the effects would be negligible compared to other variables outside a school’s control.

From the whole language perspective, student progress is largely self-determined, and thus teachers should act not as instructors, but as facilitators (Schickendanz, 1986; Smith, 1973; Weaver, 1988). Within this model, teachers are expected to react appropriately to student-initiated direction, rather than expect students to respond to a curriculum presented in a preplanned manner. One response to such a belief is to seek the provision of large sums of money to reduce class sizes so that teachers have more time to devote to each student in this manner. However, an evaluation (Jepsen & Rivkin, 2002) of a large scale initiative in California (costing over $1 billion per year) indicated that a class reduction of 10 students per grade increased the number of students exceeding national median tests score by only about 4 percentage points in mathematics and 3 percentage points in reading. These modest gains disappeared when large numbers of inexperienced teachers were employed to achieve the requisite class-size reductions.

Comparing Structured Teaching to Unstructured Approaches

Image 5

Table from Gauthier and Dembele (2004).

In contrast to the lack of empirical evidence for the unstructured perspectives(Kirschner, Sweller, & Clark, 2006; Sweller, Kirschner, & Clark, 2007), there is a strong body of research exemplified in the Sanders and Rivers (1996) finding that students who were in classes with effective teachers for 3 years in a row achieved 50% more learning than those in classes with poor teachers over the same period. A related finding was that children in 1st-year classes in which teachers lacked strong classroom management skills were at far greater risk of subsequent aggressive behavior.

Hanushek (1992) found that a very high quality teacher will achieve for students a learning gain of 1.5 grade level equivalents; whereas, a poor teacher may produce a gain of only 0.5 grade level equivalents. Thus, variation in the quality of teachers may produce a difference of up to a full year’s learning growth. In Australia, Hill and Rowe (1996) observed that differences among classrooms within schools were greater than differences among schools. They pointed out that these differences between classrooms are important foci in improving school performance. What individual teachers do in those classes is pivotal for student learning (Rupley, 2011).

Auguste, Kihn, and Miller (2010) reported that students at the 50th percentile would differ by more than 50 percentile points after three years, depending on the quality of their teachers (teachers among the top 20% vs those among the bottom 20%).

Image 6

Figure. Cumulative effect of teacher quality over three years

Student Contribution And Teacher Contribution

 An admittedly simplistic way of viewing the interaction between what the student brings to the table and what is supplied by the education system is to view the contributions in terms of box sizes, as below. Learning is likely to occur when there is sufficient capital in the learning setting, whether provided by the student or the system.

The student brings (in no particular order) intelligence, attitude, motivation, resilience, attendance, prior learning, parent influence, and sibling and peer history. The capital produced by the interaction of these qualities may be strong, average, or weak.

The system brings curriculum, teacher quality, infrastructure. Similarly, the system qualities may be strong, average, or weak.

Image 7

Figure. Why some students do well in the absence of effective instruction, while others languish.

A range of studies direct our attention to classroom instructional processes as a major variable impinging on student achievement. This position is not new. During the 1970s Engelmann (1980) and Skillman, Garcia, and Witcher (1977) argued that a student’s failure to learn is a consequence of a failure to teach effectively. Rosenshine (1979) used the expression direct instruction to describe a set of instructional variables relating teacher behavior and classroom organization to high levels of academic performance for elementary school students. High levels of achievement were related to a number of variables—among them being the amount of content covered and mastered, the amount of student academic engaged time, an academic focus rather than an affective emphasis, teacher-centered rather than student- centered classrooms, low cognitive level questions, a high success rate (above 80%), and immediate and academically oriented feedback to students. These were features noted among teachers who achieved results above those of their peers. However, they did not indicate the proportion of the variance in student achievement attributable to instruction compared with that of other variables such as socioeconomic status.

Through further research and powerful statistical methods such as multilevel structural equation modelling, it has become apparent that system input into, for example, the financial aspects of teaching - salaries, special tax incentives, and higher degrees, have not been shown to strongly influence student achievement (Wenglinsky, 2000). A major school influence on student achievement is now, clearly, classroom practice. According to Hattie (2009), what students bring to their learning accounts for 50% of the variation of achievement; but even so, 30% of the variation is still down to teaching variables. Wenglinsky (2003) reported a total standardized effect for teacher variables as 0.70, larger than the total standard effect of background measures (0.56). Based upon his analysis of empirical findings available since the 1970s, Jencks has altered his earlier view, and now argues for the potential of education to significantly reduce inequality in student achievement (Jencks & Phillips, 1998). Despite the evidence for this link, a great deal of policy continues to be devoted to issues outside of the classroom (Lyon & Fletcher, 2001; Wenglinsky, 2000).

The notion that SES is the major impediment to reducing the achievement gap has been criticised as not being based on evidence:

“This paper demonstrates that the emphasis on students’ socioeconomic status (SES) in research and policy circles in Australia is unwarranted. The bivariate relationships between SES and educational outcomes are only moderate and the effects of SES are quite small when taking into account cognitive ability or prior achievement. These two influences have much stronger relationships with students’ outcomes than SES and their effects cannot be attributed to the influence of SES at earlier points of time. The theoretical explanations for socioeconomic inequalities in education (e.g. schools and cultural factors) are problematic and are not supported by empirical work. The much weaker than assumed effects of SES has implications for research and policy.”

Marks, G.N. (2016). Is SES really that important for educational outcomes in Australia? A review and some recent evidence. The Australian Educational Researcher, First Online 10 December 2016.

There have been many studies highlighting the importance of effective teaching, and what qualities comprise it. For a detailed review of research in this area, see Archer and Hughes (2011). An example of such findings is below:

The results of this study suggest that effective teachers whose students score high on standardized tests in urban school settings actively engage their students in learning in a teacher-centered classroom. These teachers are consistent in following set rules and procedures resulting in instructional flow as students stay on task. The teachers have developed rapport with their students through good verbal and nonverbal communication skills. Their focus on instruction seems to be linked with seamless classroom management. These teachers are committed to helping students learn through the use of repetition as a means of ensuring student understanding of concepts and skills(Thompson, Ransdell, & Rousseau, 2005, p. 22).

A major concern with educational attainment is the gap between the affluent and the middle class, compared with those less advantaged— those from low-income and minority groups. Social objectives of equality cannot be achieved whilst there are glaring gaps in the attainments of different segments of a society. A generally accepted social value is that such groups should be assigned sufficient assistance to enable their full participation in the economic and social riches of the nation. This goal has resisted attainment over a long period, though in recent times there has been a concerted multilevel attack on inequality at the school and preschool levels. Such initiatives have been partly driven and informed by the failure to make much headway with the teaching models most prevalent during the last 20 years.

In fact, the achievement levels of minority and low-income students declined during the 1990s in comparison with those of other students (Haycock, 2001; Office of Educational Research and Improvement, 2001). The reading performance of the nation’s fourth graders may appear to have remained relatively stable across the last two decades. However, whilst the 2000 national average reading scale score was similar to that of 1992, the reading of higher performing students improved and that of the lower performing students declined, thereby increasing the gulf between them (Office of Educational Research and Improvement, 2001). In more recent times (e.g., 2011 NAEP scores) low performing minority and low-income students have reduced this gap slightly in some states.It has been suggested that this may be due to the effect of the extra assistance provided to this group through Reading First and No Child Left Behind legislation, though other reports found no such direct effect (Reardon, Valentino, & Shores, 2012). There is also the recent increased use of Response to Intervention models which may also have an impact, although it may be too soon to detect any effect. A concern now being expressed is that these students remain under-represented in the more proficient groups. This excellence gap has widened over the past decade (Plucker, Burroughs, & Song, 2010).

Adding to the early disadvantage suffered by low-income and minority children is the finding that they are far more likely to be saddled with lower quality teachers (Peske & Haycock, 2006; Wayne, 2002). This is especially unfortunate, as such children are more vulnerable to teaching differences than are students from higher socioeconomic status (Coleman, 1990; Goldhaber & Anthony, 2004). That is, minority children are more severely affected by poor teaching than are other children. In fact, they are significantly more influenced by a range of educational factors than are their more advantaged peers. These include smaller class size and the presence of full day programs (Yan & Lin, 2004).

Despite this depressing outcome, there are pockets of hope, emanating from schools and districts that address the issue of teaching effectiveness. A year long study in Boston noted that the best 30% of teachers evoked in their students 6 times the learning growth as did the lowest 30% of teachers (Boston Public Schools, 1998). Similar research in Tennessee and Texas highlighted the cumulative nature of these effects and their presence regardless of student background or attainment levels (Sanders & Rivers, 1996).

Of course, there were also other important elements in the comprehensive reform of schools serving disadvantaged students. According to the Report of the Education Trust (1999), successful schools ensured increased time was devoted to reading and math. This direction parallels that of Marks, McMillan, and Ainley (2004) who noted that while the effect of socioeconomic background on important educational outcomes is often strongly emphasised, its influence is considerably smaller than produced by early achievement in basic skills—literacy in particular. A recognition that many teachers have had little training in effective teaching practice ensured that funds were made available to enable carefully focused professional development. In order for school and district accountability, comprehensive monitoring of student progress and consequences for inadequate teaching were incorporated. The provision of additional school and home-based student support helps ensure that students at risk do not remain unassisted. These elements of effective school reform have their most powerful effect in ensuring effective practices are employed in the classroom.

An increasing number of schools (particularly those attempting to redress disadvantage) are taking advantage of the research into effective teaching practices and Response to Intervention, and have adopted Direct Instruction Programs.

When Thaddeus Lott became principal of Wesley Elementary, a school in an area of extreme disadvantage, only 18% of third graders were at or above grade level in reading comprehension on the Iowa Test of Basic Skills. Within 5 years that proportion had increased to 85%. In 1996, 100% of the third graders passed the Texas Assessment of Academic Skills in reading (Palmaffy, 1998).

In poverty-ridden City Springs Elementary School, literacy levels have improved from among the district’s lowest to its fifth highest (Viadero, 2002b). In some of the most disadvantaged schools in Houston, Direct Instruction reading with pupils in kindergarten, first, and second grade, under the auspices of the Rodeo Institute for Teacher Excellence, have produced consistent and strongly accelerated growth throughout the program duration (Viadero, 2002b). For example:

Image 8A

Image 8B

 Figures from Gauthier, C., & Dembélé, M. (2004).

This decade could be the beginning of one of the most exciting periods in education history, as the sleeping giant of educational knowledge, ignored for so long, begins to influence education systems around the world. These effects may become evident at both a macro/policy level and at a micro/classroom level (these two have not always been attuned). There may develop increased funding and demand for higher quality research—more longitudinal studies, better designs, evaluations of larger scale implementations. Despite similar budgets for health and education, the US D.O.E. spends about $80 million annually in educational research; whereas, the Department of Health and Human Services provides about $33 billion for health research (Haan Foundation, 2012).

The evidence of subsequently improved outcomes for students in general, and for the disadvantaged in particular, may lead to a greatly increased attractiveness to both prospective teachers and budding researchers, thereby enhancing the quality of the education profession.

Is all this an optimist’s pipe dream? Hmm, let’s hope not.

References

Adams, M. J. (1990). Beginning to read: Thinking and learning about print. Cambridge, MA: MIT Press.

Alessi, G. (1988). Diagnosis diagnosed: A systemic reaction. Professional School Psychology, 3, 145–151. Retrieved from www.ldonline.org/ld_indepth/assessment/ed_problems.html

Allington, R. L. (1984). Content coverage and contextual reading in reading groups. Journal of Reading Behavior, 16, 85–96.

America Reads. (2001). Starting out right: A guide to promoting children’s reading success. Retrieved from http://www.ed.gov/inits/americareads/educators_early.html

American Management Association. (2001). AMA Survey on workplace testing: Basic skills, job skills, psychological measurement—Summary of key findings. New York: Author.

Archer, A.L., & Hughes, C.A. (2011). Explicit instruction: Effective and efficient teaching. New York: The Guilford Press.

Auguste, B., Kihn, P., & Miller, M. (2010). Closing the talent gap: Attracting and retaining the top-third graduates to careers in Teaching. McKinsey & Co. Retrieved from http://www.ptec.org/document/ServeFile.cfm?ID=10526&DocID=2026&Attachment=1

Ball, E. W. (1993). Phonological awareness. What’s important and to whom? Reading and Writing: An Interdisciplinary Journal, 5, 141–159.

Ball, E. W., & Blachman, B. A. (1991). Does phoneme awareness training in kindergarten make a difference in early word recognition and developmental spelling. Reading Research Quarterly, 25, 49–66.

Baumeister, R. F., Campbell, D., Krueger, J. I., & Vohs, K. D. (2004, December 20). Exploding the self-esteem myth. Scientific American. Retrieved from http://www.sciam.com/print_version.cfm?articleID=000CB565-F330-11BEAD0683414B7F0000

Binder, C. (1996). Behavioral fluency: Evolution of a new paradigm. The Behavior Analyst, 19, 163–197.

Blachman, B. A. (1994). What we have learned from longitudinal studies of phonological processing and reading, and some unanswered questions: A response to Torgesen, Wagner, & Rashotte. Journal of Learning Disabilities, 27, 287–291.

Boston Public Schools. (1998). High school restructuring. Boston: Author.

Bradley, L., & Bryant, P. (1983). Categorizing sounds and learning to read—A causal connection. Nature, 301, 419–421.

Byrne, B., & Fielding-Barnsley, R. (1989). Phonemic awareness and letter knowledge in the child’s acquisition of the alphabetic principle. Journal of Educational Psychology, 81, 313–321.

Campanile, C. (2002, July 11). Two-thirds flunk math. New York Post. Retrieved from http://www.nypost.com/news/regionalnews/52299.htm

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. (1995a). The professional context for collaboration and collaborative research. Remedial and Special Education, 16(6), 368–371.

Carnine, D. (1995b). Trustworthiness, use- ability, and accessibility of educational research. Journal of Behavioral Education, 5, 251–258.

Carnine, D. (2000). Why education experts resist effective practices (and what it would take to make education more like medicine). Washington, DC: Thomas B. Fordham Foundation. Retrieved from www.edexcellence.net/publications/edexpertsresist.html

Catts, H. W. (1991). Early identification of reading disabilities. Topics in Language Disorders, 12(1), 1–16.

Ceci, S. (1991). How much does schooling influence general intelligence and its cognitive components? A reassessment of the evidence. Developmental Psychology, 27, 703–722.

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

Chapman, J. W., Tunmer, W. E., & Prochnow, J. E. (2000). Early reading-related skills and performance, reading self-concept, and the development of academic self- concept: A longitudinal study. Journal of Educational Psychology, 92(4), 703–708.

Coleman, J. S. (1990). Equality and achievement in education. Boulder, CO: Westview Press.

Coleman, J., Campbell, E., Hobson, C., McPartland, J., Mood, A., Weinfeld, F. D., et al. (1966). Equality of educational opportunity. Washington, DC: Department of Health, Education, and Welfare.

Colvin, R. C., & Helfand, D. (1999, December 12). Special education a failure on many fronts. LA Times. Retrieved from http://www.latimes.com/news/state/reports/specialeduc/lat_special991212.htm

Commission on Excellence in Special Education. (2002). A new era: Revitalizing special education for children and their families. Retrieved from http://www.ed.gov/inits/commissionsboards/whspecialeducation/

Cortiella, C. (2011). The state of learning disabilities. New York: National Center for Learning Disabilities

Cunningham, A. (1990). Explicit versus implicit instruction in phonemic awareness. Journal of Experimental Child Psychology, 50, 429–444.

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

Delpit, L. D. (1986). Skills and other dilemmas of a progressive black educator. Harvard Educational Review, 56, 379–385.

Delpit, L. D. (1988). The silenced dialogue: Power and pedagogy in educating other people’s children. Harvard Educational Review, 58, 280–298.

Department for Education and Employment. (1998). The national literacy strategy: Framework for teaching. London: Crown.

Donald, A. (2002). A practical guide to evidence- based medicine. Medscape Psychiatry & Mental Health eJournal, 7(2). Retrieved from http://www.medscape.com/viewarticle/430709

Engelmann, S. (1980, February). Toward the design of faultless instruction: The theoretical basis of concept analysis. Educational Technology, 20(2), 28–36.

Farkas, G., & Beron, K. (2001, March). Family linguistic culture and social reproduction: Verbal skill from parent to child in the preschool and school years. Presentation at the session on Consequences of Child Poverty and Deprivation, at the Annual Meetings of the Population Association of America, Washington, DC. Retrieved from http://www.pop.psu.edu/general/pubs/working_papers/psu-pri/wp0105.pdf

Faust, M., & Kandelshine-Waldman, O. (2011) The effects of different approaches to reading instruction on letter detection tasks in normally achieving and low achieving readers Reading and Writing: An Interdisciplinary Journal, 24(5), 545–566.

Felton, R. H. (1993). Effects of instruction on the decoding skills of children with phonological processing problems. Journal of Learning Disabilities, 26, 583–589.

Fielding, L. C., Wilson, P. T., & Anderson, R. C. (1986). A new focus on free reading: The role of trade books in reading instruction. In T. E. Raphael (Ed.), Contexts of school based literacy (pp. 149–160). New York: Random House.

Fister, S., & Kemp, K. (1993). Translating research: Classroom application of validated instructional strategies. In R. C. Greaves & P. J. McLaughlin (Eds.), Recent advances in special education and rehabilitation (pp. 107–126). Boston: Andover Medical.

Fleming, N. (2013). NAEP shows most students lack writing proficiency. Education Week, January 13, 2013. Retrieved from http://www.edweek.org/ew/articles/2012/09/14/04naep.h32.html

Fletcher, J. M., Francis, D. J., Rourke, B. P., Shaywitz, S. E., & Shaywitz, B. A. (1993). Classification of learning disabilities. Relation to other childhood disorders. In G. R. Lyon, D. B. Gray, J. F. Kavanagh, & N. A. Krasnegor (Eds.), Better understanding of learning disabilities: New views from research and their implications for education and public policies (pp.153–170). Baltimore: Brooks Pub.

Foorman, B., Francis, D., Novy, D., & Liberman, D. (1991). How letter-sound instruction mediates progress in first grade reading and spelling. Journal of Educational Psychology, 83, 456–469.

Gable, R. A., & Warren. S. F. (1993). The enduring value of instructional research. In R. Gable & S. Warren (Eds.), Advances in mental retardation and developmental disabilities: Strategies for teaching students with mild to severe mental retardation (pp. 1–7). Philadelphia: Jessica Kingsley.

Gauthier, C., & Dembélé, M. (2004). Quality of teaching and quality of education: A review of research findings. UNESCO Background paper prepared for the Education for All Global Monitoring Report 2005 The Quality Imperative. Retrieved from http://unesdoc.unesco.org/images/0014/001466/146641e.pdf

Gersten, R., & Guskey, T. (1985, Fall). Transforming teacher reluctance into a commitment to innovation. Direct Instruction News, 11–12.

Gersten, R., Chard, D., & Baker, S. (2000). Factors enhancing sustained use of research-based instructional practices. Journal of Learning Disabilities, 33, 445–457.

Goldhaber, D. D., & Anthony, E. (2004). Can teacher quality be effectively assessed? Washington, DC: Urban Institute Press. Retrieved from http://www.urban.org/UploadedPDF/410958_NBPTSOutcomes.pdf

Goodman, K. S. (Ed.). (1998). In defense of good teaching. York, ME: Stenhouse.

Haan Foundation. (2012). The federal education research project. Retrieved from http://www.haan4kids.org/fed_proj/

Hanushek, E. A. (1992). The trade-off between child quantity and quality. Journal of Political Economy, 100(1), 84–117.

Hart, B., & Risley, T. R. (1995). Meaningful differences in the everyday experiences of young American children. Baltimore: Paul H. Brookes.

Hart, B., & Risley, T. R. (2003, Spring). The early catastrophe: The 30 million word gap. American Educator. Retrieved from http://www.aft.org/american_educator/spring2003/catastrophe.html

Hartocollis, A. (2002, July 11). Reading scores drop sharply in 8th Grade. New York Times. Retrieved from http://www.nytimes.com/2002/07/11/education/11SCOR.html?pagewanted=print&position=top

Hatcher, P., Hulme, C., & Ellis, A. (1994). Ameliorating reading failure by integrating the teaching of reading and phonological skills: The phonological linkage hypothesis. Child Development, 65, 41–57.

Hattie, J. (2009). Visible Learning; a synthesis of over 800 meta-analyses relating to achievement. London; Routledge

Haycock, K. (2001, March). Helping all students achieve: Closing the achievement gap. Educational Leadership, 58(6). Retrieved from http://www.ascd.org/readingroom/edlead/0103/haycock.html

Hempenstall, K. (1996). The gulf between educational research and policy: The example of Direct Instruction and Whole Language. Behaviour Change, 13, 33–46.

Hempenstall, K. (1996). The Matthew Effects in reading: Why initial delays in reading become increasingly pervasive. Paper presented at the Annual State Conference of the Australian Association for Cognitive and Behaviour Therapy, Monash U.

Hempenstall, K. (1997). The whole language- phonics controversy: An historical perspective. Educational Psychology, 17, 399–418.

Herrnstein, R., & Murray, C. (1994). The Bell Curve: Intelligence and class structure in American life. New York: The Free Press.

Heward, W. L. (2003). Ten faulty notions about teaching and learning that hinder the effectiveness of special education. The Journal of Special Education, 36, 186–205. Retrieved from http://www.coe.ohio-state.edu/wheward/publications.htm

Hill, P., & Rowe, K. J. (1996). Multilevel modelling in school effectiveness research. School Effectiveness and School Improvement, 7(1), 1–34.

Hoskyn, M., & Swanson, H. L. (2000). Cognitive processing of low achievers and children with reading disabilities: A selective meta-analytic review of the published literature. School Psychology Review, 29, 102–119.

Jencks, C. S., & Phillips, M. (1998). America’s next achievement test. The American Prospect, 9(40). Retrieved from http://www.prospect.org/print/V9/40/jencks-c.html

Jencks, C. S., Smith, M., Acland, H., Bane, M. J., Cohen, D., Ginits, H., et al. (1972). Inequality: A reassessment of the effect of family and schooling in America. New York: Basic Books.

Jepsen, C., & Rivkin, S. (2002). Class size reduction, teacher quality, and academic achievement in California Public Elementary Schools. San Francisco: Public Policy Institute of California.

Johns, B. H. (2001). Atlanta Journal-Constitution. Monday, October 29.

Johnson, J., & Duffett, A. (2002). Reality check, 2002. Public Agenda. Retrieved from http://www.publicagenda.org/specials/teachers/teachers.htm

Johnson, K. A. (2003). Time to refocus special education on reading achievement. Mackinac Center for Public Policy. Retrieved from http://www.mackinac.org/5000

Jones, J.M. (2012). Confidence in U.S. public schools at new low. Gallup Politics. Retrieved from http://www.gallup.com/poll/155258/Confidence-Public-Schools-New-Low.aspx

Jorm, A., Share, D., McLean, R., & Matthews, R. (1984). Phonological recoding and learning to read: A longitudinal study. Applied Psycholinguistics, 5, 201–207.

Juel, C. (1988). Learning to read and write: A longitudinal study of 54 children from first through fourth grades. Journal of Educational Psychology, 80, 437–447.

Juel, C. (1993). The spelling-sound code in reading. In S. Yussen & M. Smith (Eds.), Reading across the life span (pp. 95–109). New York: Springer-Verlag.

Kirschner, P.A., Sweller, J., & Clark, R.E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86.

Leach, D. J. (1987). Increasing the use and maintenance of behaviour-based practices in schools: An example of a general problem for applied psychologists? Australian Psychologist, 22, 323–332.

Leigh, A., & Ryan, C (2006). Teacher quality: How and why has teacher quality changed in Australia, Teacher, December, pp. 14-19.

Lepola, J., Salonen, P., & Vauras, M. (2000). The development of motivational orientations as a function of divergent reading careers from pre-school to the second grade. Learning and Instruction, 10, 153–177.

Levin, B. (1998). Criticizing the schools: Then and now. Education Policy Analysis Archives, 6(16). Retrieved from http://epaa.asu.edu/epaa/v6n16.html

Lewis, L., & Paik, S. (2001). Add it up: Using research to improve education for low-income and minority students. Washington, DC: Poverty & Race Research Action Council. Retrieved from http://www.prrac.org/additup.pdf

Lindsley, O. R. (1992). Why aren’t effective teaching tools widely adopted. Journal of Applied Behaviour Analysis, 25, 21–26.

Lyon, G. R. (1998). Overview of reading and literacy initiatives. Statement to Committee on Labor and Human Resources. Retrieved from http://www.nichd.nih.gov/publications/pubs/jeffords.htm

Lyon, G. R. (1999). The NICHD research program in reading development, reading disorders, and reading instruction. Washington, DC: National Center for Learning Disabilities.

Lyon, G. R. (2001a). Measuring success: Using assessments and accountability to raise student achievement. Subcommittee on Education Reform Committee on Education and the Workforce U.S. House of Representatives Washington, DC. Retrieved from http://www.nrrf.org/lyon_statement3-01.htm

Lyon, G. R. (2001b, July 30). Summary comments White House Early Childhood Cognitive Development Summit. Education News Org. Retrieved from http://www.educationnews.org/white_house_early_childhood_cogn.htm

Lyon, G. R., & Fletcher, J. M. (2001, Summer). Early warning system: How to prevent reading disabilities. Education Matters, 1(2), 22–29. Retrieved from http://www.educationnext.org/20012/22.html

Maggs, A., & White, R. (1982). The educational psychologist: Facing a new era. Psychology in the Schools, 19, 129–134.

Marks, G., McMillan, J., & Ainley, J. (2004, April 20). Policy issues for Australia’s education systems: Evidence from international and Australian research. Education Policy Analysis Archives, 12(17). Retrieved from http://epaa.asu.edu/epaa/v12n17

Marshall, J. (1993). Why Johnny can’t teach. Reason, 25(7), 102–106.

Mash, E. J., & Wolfe, D. A. (2002). Abnormal child psychology. Belmont, CA: Wadsworth Thomson Learning.

Mather, N., Bos, C., & Babur, N. (2001). Perceptions and knowledge of preservice and inservice teachers about early literacy instruction. Journal of Learning Disabilities, 34, 472–482.

Maugban, B. (2003). Reading problems and depressed mood. Journal of Abnormal Child Psychology, 31, 210–229.

Moats, L. (2000). Whole language high jinks: The illusion of balanced reading instruction. Thomas B. Fordham Foundation. Retrieved from http://www.ldonline.org/article/6394/?theme=print

Moats, L. (2007). Whole language lives on: The illusion of balanced reading instruction: How to tell when scientifically-based reading instruction isn’t. Thomas B. Fordham Foundation. Retrieved from http://www.k12.wa.us/Reading/ReadingFirst/pubdocs/Moats2007.pdf

Moats, L. C. (1996). Implementing effective instruction for students with LD: A challenge for the future. In S. C. Cramer & W. Ellis (Eds.), Learning disabilities: Lifelong issues (pp. 87–93). Baltimore: Brookes Publishing Co.

Nagy, W. (1998). Increasing students’ reading vocabularies. Presentation at the Commissioner’s Reading Day Conference, Austin, TX.

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

National Center for Education Statistics (2011). National Assessment of Educational Progress (NAEP). U.S. Department of Education, Institute of Education Sciences. Retrieved from http://nces.ed.gov/nationsreportcard/pdf/main2011/2012457.pdf

National Center for Educational Statistics. (2012). Highlights from PIRLS 2011: Reading Achievement of U.S. Fourth-Grade Students in an International Context. U.S. Department of Education, Institute of Education Sciences. Retrieved from http://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2013010)

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.

Neill, A. S. (1974). Summerhill. Middlesex: Penguin.

Nuthall, G. (2004). Relating classroom teaching to student learning: A critical analysis of why research has failed to bridge the theory-practice gap. Harvard Educational Review, 74, 273–306.

Office of Educational Research and Improvement. (2001). The nation’s report card: Fourth-Grade reading 2000. Washington, DC: U.S. Dept. of Education. Retrieved from http://nces.ed.gov/nationsreportcard/pubs/main2000/2001499.asp

Palmaffy, T. (1998). No excuses: Houston educator Thaddeus Lott puts failing schools to shame. Washington, DC: The Heritage Foundation. Retrieved from http://www.noexcuses.org/articles/shame.html

Peske, H. G., & Haycock, K. (2006). Teaching inequality: How poor and minority students are shortchanged on teacher quality. Washington, DC: The Education Trust. Retrieved from http://www.edtrust.org/dc/publication/teaching-inequality-how-poor-and-minority-students-are-shortchanged-on-teacher-qualit

Peske, H., & Haycock, K. (2006). Teaching inequality: How poor and minority students are shortchanged on teacher quality. Washington, DC: The Education Trust.

Peterson, C. L., Caverly, D. C., Nicholson, S. A., O’Neal, S., & Cusenbary, S. (2003). Building reading proficiency at the secondary level: A guide to resources. Austin, TX: Southwest Educational Development Laboratory. Retrieved from http://www.sedl.org/pubs/reading16/buildingreading.pdf

Plucker, J.A., Burroughs, N., & Song, R. (2010). Mind the (other) gap! The growing excellence gap in K-12 education. (Bloomington: Indiana University Center for Evaluation and Education Policy).

Prawat, R. S. (1992). Teachers’ beliefs about teaching and learning: A constructivist perspective. American Journal of Education, 100, 354–395.

Puma, M., Bell, S., Cook, R., Heid, C., Broene, P., Jenkins, F., Mashburn, A., & Downer, J. (2012). Third grade follow-up to the Head Start Impact Study. Final report, OPRE Report 2012-45. Retrieved from http://www.acf.hhs.gov/sites/default/files/opre/head_start_report.pdf

Reardon, S.F., Valentino, R.A., & Shores, K.A. (2012). Patterns of literacy among U.S. students. The Future of Children, 22(2), 1-37. Retrieved from http://futureofchildren.org/futureofchildren/publications/docs/22_02_02.pdf

Reardon, S.F., Valentino, R.A., & Shores, K.A. (2012). Patterns of literacy among U.S. students. The Future of Children, 22(2), 1-37. Retrieved from http://futureofchildren.org/futureofchildren/publications/docs/22_02_02.pdf

Report of the Education Trust. (1999). Dispelling the myth: High poverty schools exceeding expectations. Washington, DC: Education Trust. Retrieved from http://www.edtrust.org/main/documents/dispell.pdf

Reschly, A.L. (2010): Reading and school completion: Critical connections and Matthew Effects. Reading & Writing Quarterly: Overcoming Learning Difficulties, 26(1), 67-90.

Rogers, C. (1961). On becoming a person. Boston: Houghton Mifflin.

Rosenshine, B. V. (1979). Content, time, and direct instruction. In P. L. Peterson & H. J. Walbert (Eds.), Research on teaching: Concepts, findings, and implications (pp. 28–56). Berkeley, CA: McCutchan.

Rothstein, R. (2004). Class and schools: Using social, economic, and educational reform to close the black-white achievement gap. The Economic Policy Institute and Teachers College Press. Retrieved January 1, 2005, from http://www.epinet.org/content.cfm/books_class_and_schools

Rupley, W.H. (2011). Research on teacher quality: Improving reading and writing instruction. Reading & Writing Quarterly: Overcoming Learning Difficulties, 27(3), 179-182.

Sackett, D., McRosenberg, W., Muir Gray, J. A., Haynes, R. B., & Richardson, W. S. (1996). Evidence-based medicine: What it is and what it isn’t. British Medical Journal, 312, 71–72. Retrieved from http://cebm.jr2.ox.ac.uk/ebmisisnt.html#coredef

Sanders, W., & Rivers, J. (1996). Cumulative and residual effects of teachers on future student academic achievement. Knoxville: University of Tennessee Value-Added Research and Assessment Center.

Schickendanz, J. A. (1986). More than the ABC’s: The early stages of reading and writing. Washington, DC: NAEYC.

Schmidt, W., Houang, R., & Cogan, L. (2002, Summer). A coherent curriculum: The case of mathematics. American Educator. Retrieved from http://www.aft.org/american_educator/summer2002/curriculum.pdf

Share, D. L., & Silva, P. A. (1987). Language deficits and specific reading retardation: Cause or effect? British Journal of Disorders of Communication, 22, 219–226.

Share, D. L., McGee, R., & Silva, P. (1989). IQ and reading progress: A test of the capacity notion of IQ. Journal of the American Academy of Child and Adolescent Psychiatry, 28, 97–100.

Shaw, S. R. (2008). An educational programming framework for a subset of students with diverse learning needs: Borderline intellectual functioning. Intervention in School and Clinic, 43, 291-299.

Simmons, D. C. (1992). Perspectives on dyslexia: Commentary on educational concerns. Journal of Learning Disabilities, 25, 66–70.

Skillman, L., Garcia, L., & Witcher, C. (1977). Direct Instruction model implementation manual II. Guidebook for supervisors. Eugene: Follow Through Project, Division of Teacher Education, University of Oregon.

Smith, F. (1973). Psychology and reading. New York: Holt, Rinehart, & Winston.

Smith, F. (1992). Learning to read: The never-ending debate. Phi Delta Kappan, 74, 432–441.

Snow, C. E. (2002). Reading for understanding: Toward an R&D program in reading comprehension. Santa Monica, CA: RAND.

Sparks, S.D. (2013). Most 8th graders fall short on NAEP science test. Education Week. Jan 27, 2013. Retrieved from http://www.edweek.org/ew/articles/2012/05/10/31naep_ep.h31.html

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, 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. (1992). Speculation on the causes and consequences of individual differences in early reading acquisition. In P. Gough, L. Ehri, & R. Treiman (Eds.), Reading acquisition (pp. 307–342). Mahwah, NJ: Lawrence Erlbaum Associates.

Stanovich, K. E. (1993). Does reading make you smarter? Literacy and the development of verbal intelligence. Advances in Child Development and Behavior, 24, 133–180.

Stone, J. E. (1996). Developmentalism: An obscure but pervasive restriction on educational improvement. Education Policy Analysis Archives, 4. Retrieved from http://olam.ed.asu.edu/epaa/v4n8.html

Sweller, J., Kirschner, P.A., & Clark, R.E. (2007). Why minimally guided teaching techniques do not work: A reply to commentaries. Educational Psychologist, 42(2), 115–121.

Thompson, S., Ransdell, M.F., & Rousseau, C.K. (2005). Effective teachers in urban school settings: Linking teacher disposition and student performance on standardized tests. Journal of Authentic Learning, 2(1) 22-36. Retrieved from http://dspace.sunyconnect.suny.edu/bitstream/handle/1951/6596/thompson.pdf?sequence=1

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/ld_indepth/reading/torgeson_catchthem.html

Torgesen, J. K., Wagner, R. J., & Rashotte, C. A. (1994). Longitudinal studies of phonological processing and reading. Journal of Learning Disabilities, 27, 276–286.

Tough, P. (2012). How children succeed: Grit, curiosity, and the hidden power of character. Boston, MA: Houghton Mifflin Harcourt.

Tucker, M.S. (2011). Standing on the shoulders of giants: An American agenda for education reform. National Center on Education and the Economy. Retrieved from http://www.ncee.org/wp-content/uploads/2011/05/Standing-on-the-Shoulders-of-Giants-An-American-Agenda-for-Education-Reform.pdf

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

Turbill, J. (2002, February). The four ages of reading philosophy and pedagogy: A framework for examining theory and practice. Reading Online, 5(6). Retrieved from http://www.readingonline.org/international/inter_index.asp?HREF=turbill4/index.html

U.S. Department of Education (2002c, January). No Child Left Behind Act, 2001. Retrieved from http://www.ed.gov/offices/OESE/esea/

U.S. Department of Education. (1995). Seventeenth annual report to Congress on the implementation of the Individuals with Disabilities Education Act. Washington, DC: U.S. Government Printing Office.

U.S. Department of Education. (1999). The 1998 NAEP reading report card for the nation, NCES 1999-459. P. L. Donahue, K. E. Voelkl, J. R. Campbell, & J. Mazzeo (Eds.). Washington, DC: Author.

U.S. Department of Education. (2001a). The nation’s report card: Fourth-Grade reading 2000, NCES 2001-499. P. L. Donahue, R. J. Finnegan, A. D. Lutkus, N. L. Allen, & J. R. Campbell (Eds.). Washington, DC: U.S. Government Printing Office.

U.S. Department of Education. (2001b). OSEP, Fuchs, D., Fuchs, L. S., Mathes, P. G., Lipsey, M. W., & Roberts, P. H. (2001). Is “learning disabilities” just a fancy term for low achievement? A meta-analysis of reading differences between low achievers with and without the label. The Learning Disabilities Summit: Building a Foundation for the Future. Washington, DC: U.S. Government Printing Office. Retrieved from http://www.ldaofky.org/LD/Is%20LD%20just%20another%20term%20for%20low%20achievement.pdf

U.S. Department of Education. (2002a). The Condition of Education 2002, NCES 2000602. Washington, DC: U.S. Government Printing Office.

U.S. Department of Education. (2002b). Profile of undergraduates in U.S. postsecondary institutions: 1999–2000, NCES 2002–168. L. Horn, K. Peter, & K. Rooney (Eds.). Washington, DC: U.S. Government Printing Office.

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.

Viadero, D. (2002a). Research: Holding up a mirror. Editorial Projects in Education, 21(40), 32–35.

Viadero, D. (2002b). Studies cite learning gains in Direct Instruction schools. Editorial Projects in Education, 21(31), 15.

Wade, B., & Moore, M. (1993). Experiencing special education. Buckingham: Open Univ. Press.

Wayne, A. (2002, June 13). Teacher inequality: New evidence on disparities in teachers’ academic skills. Education Policy Analysis Archives, 10(30). Retrieved from http://epaa.asu.edu/epaa/v10n30/

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

Weaver, C., Patterson, L., Ellis, L., Zinke, S., Eastman, P., & Moustafa, M. (1997). “Big Brother” and reading instruction. Retrieved from http://www.m4pe.org/elsewhere.htm

Weir, R. (1990). Philosophy, cultural beliefs and literacy. Interchange, 21(4), 24–33.

Wenglinsky, H. (2000). How teaching matters. Princeton, NJ: Milken Foundation and Educational Testing Service. Retrieved from www.ets.org/research/pic/teamat.pdf

Wenglinsky, H. (2003, June 30). Using large- scale research to gauge the impact of instructional practices on student reading comprehension: An exploratory study. Education Policy Analysis Archives, 11(19). Retrieved July 4, 2003, from http://epaa. asu.edu/epaa/v11n19/

Whitehurst, G. (2003). Children of the code: A social-education project and a PBS television documentary series. Retrieved from www.childrenofthecode.org/cotcintro.htm

Woodward, J. (1993). The technology of technology- based instruction: Comments on the research, development, and dissemination approach to innovation. Education & Treatment of Children, 16, 345–360.

Yan, W., & Lin, Q. (2004, February 24). The effect of kindergarten program types and class size on early academic performance. Education Policy Analysis Archives, 12(7). Retrieved from http://epaa.asu.edu/epaa/v12n7/

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