Understanding Specific Learning Disabilities: Definition, Characteristics, and Identification

Specific Learning Disabilities (SLD) represent a complex and multifaceted area within special education. Recognized as a potentially disabling condition that interferes with adaptation at school and in society, SLD has been the subject of extensive research and evolving definitions over the past half-century. This article aims to provide a comprehensive overview of SLD, encompassing its definition, characteristics, methods of identification, and the ongoing evolution of understanding in the field.

Defining Specific Learning Disabilities

A learning disability is a processing disorder which affects the ability to understand or use language, and may result in difficulties in listening, thinking, speaking, reading, writing, spelling, and mathematics. The Individuals with Disabilities Education Act (IDEA) mandates that children and youth ages 3-21 with disabilities be provided a free and appropriate public school education in the least restricted environment. Children are identified as SLD through IDEA when a child does not meet state-approved age- or grade-level standards in one or more of the following areas: oral expression, listening comprehension, written expression, basic reading skills, reading fluency, reading comprehension, mathematics calculation, and mathematics problem solving.

The original 1968 definition of SLD remains statutory through different reauthorizations of the 1975 special education legislation that provided free and appropriate public education for all children with disabilities, now referred to as the Individuals with Disabilities Education Act (IDEA).

Key Characteristics of SLD

Students with learning disabilities usually have average or above average intelligence. There seems to be a gap between the student’s ability and actual achievement. Students with learning disabilities display one or more of the following primary characteristics: Reading problems (decoding and / or comprehension), difficulties in written language, and underachievement in math. Secondary characteristics might include poor social skills, inattention, hyperactivity, and behavioral problems. May struggle to accurately interpret non-verbal cues.

SLD can manifest as primary conditions-as difficulties in acquiring specific academic skills-or as secondary conditions, comorbid to other developmental disorders such as Attention Deficit Hyperactivity Disorder. SLD, exemplified here by Specific Word Reading, Reading Comprehension, Mathematics, and Written Expression Disabilities, represent spectrum disorders each occurring in approximately 5-15% of the school-aged population. In addition to risk for academic deficiencies and related functional social, emotional, and behavioral difficulties, those with SLD often have poorer long-term social and vocational outcomes.

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Methods of SLD Identification

When IDEA was last reauthorized in 2004, additional methods of specific learning disability (SLD) identification were added. For decades, SLD identification was determined by a discrepancy between intellectual ability as measured by an IQ score, and academic achievement. IDEIA, the legislation that reauthorized IDEA in 2004, stated that states had to adopt criteria for SLD identification but noted states “…must not require the use of a severe discrepancy between intellectual ability and achievement…”.

Over the years, various methods for identifying SLD have emerged, each with its strengths and limitations. These include:

Ability Achievement Discrepancy (AAD)

Because learning disabilities often present as difficulty acquiring academic skills despite evidence of typical intelligence, Ability Achievement Discrepancy (AAD) was a preferred method of SLD identification for many decades. AAD defines an SLD as a discrepancy between an overall intellectual ability score (IQ) and academic achievement. This method typically identifies students with average or better overall cognitive ability and below average academic skills. When AAD is used, students with low or below average over cognitive ability often are not identified because their skills are viewed as commensurate with their overall abilities. This method does not consider that overall cognitive scores (IQ scores) are impacted by specific processing deficits. This is problematic because students with SLD frequently have weaknesses in abilities such as working memory or processing speed and these weaknesses can depress the overall IQ score as this score is essentially a composite of all the discrete cognitive abilities that are measured on these tests. Also problematic is that there is no consistent criteria for what represents a ‘significant’ or ‘severe’ discrepancy.

Response to Intervention (RTI)

Identification of an SLD using “a process based on the child’s response to scientific, research-based intervention” is referred to as RTI. More recently, the term multi-tiered system of supports (MTSS) has become common. As the name implies, this method provides students with increasingly intensive academic intervention and monitors the students’ response. RTI typically identifies students who are at the lowest end of the academic skill distribution. Cognitive abilities and processing skills are not assessed other than a rule out of intellectual disability. While RTI has now been in use as an identification method, there is little research that defines exactly what criteria should be used to determine that a student’s progress is not adequate.

Patterns of Strengths and Weaknesses (PSW)

In the twenty years since the 2004 reauthorization of IDEA, patterns of strengths and weakness (PSW) models have come to be known as the “third method” of SLD identification allowed for because they are “alternative, research-based procedures” or models of SLD identification. Like AAD, PSW models investigate underachievement that is unexpected given the individual’s otherwise average or typical cognitive abilities. Unlike AAD, PSW models recognize that there are numerous cognitive abilities and processing skills that are able to be assessed discreetly. PSW models recognize that cognitive processing weaknesses will impact achievement and may also result in composite IQ scores that underestimate an individual’s potential. Neurocognitive research continues to increase our understanding of how cognitive processing abilities are best conceptualized, measured and how they impact academics.

Exclusionary Factors

Identification methods have searched for other markers of unexpected underachievement beyond low achievement, but always include exclusionary factors. Diagnosis solely by exclusion has been criticized due to the heterogeneity of the resultant groups.

Historical Context and Evolution of SLD Understanding

Three strands of phenomenological inquiry culminated in the 1968 definition and have continued to shape current terminology and conventions in the field of SLD. The first, a medical strand, originated in 1676, when Johannes Schmidt described an adult who had lost his ability to read (but with preserved ability to write and spell) because of a stroke. Interest in this strand reemerged in the 1870s with the publication of a string of adult cases who had lived through a stroke or traumatic brain injury. Subsequent cases involved children who were unable to learn to read despite success in mathematics and an absence of brain injury, which was termed “word blindness” (W. P. Morgan, 1896).

The second strand is directly related to the formalization of the American Psychiatric Association’s Diagnostic and Statistical Manual (DSM). Rooted in the work of biologically oriented physicians, the 1952 first edition (DSM-I) referenced a category of chronic brain syndromes of unknown cause that focused largely on behavioral presentations we now recognize as hyperkinesis and Attention Deficit Hyperactivity Disorder (ADHD). After almost 30 years of research into this general category of “minimal brain dysfunction,” representing “… children of near average, average, or above average general intelligence with certain learning or behavioral disabilities … associated with deviations of function of the central nervous system.” (Clements, 1966, pp. 9-10), the field acknowledged the heterogeneity of these children and the failure of general “one size fits all” interventions. As a result, the 1980 DSM-III formally separated academic skill disorders from ADHD. The 1994 DSM-IV differentiated reading, mathematics, and written expression SLD.

The third strand originated from the development of effective interventions based on cognitive and linguistic models of observed academic difficulties. This strand, endorsed in the 1960s by Samuel Kirk and associates, viewed SLD as an overarching category of spoken and written language difficulties that manifested as disabilities in reading (dyslexia), mathematics (dyscalculia), and writing (dysgraphia).

Advances have been made in understanding the psychological and cognitive texture of SLD, developing interventions aimed at overcoming or managing them, and differentiating these disorders from each other, from other developmental disorders, and from other forms of disadvantage. Although its exclusionary criteria were well specified, the definition of SLD did not provide clear inclusionary criteria. Thus, the US Department of Education’s 1977 regulatory definition of SLD included a cognitive discrepancy between higher IQ and lower achievement as an inclusionary criterion. This discrepancy was viewed as a marker for unexpected underachievement and penetrated the policy and practice of SLD in the US and abroad. In many settings, the measurement of such a discrepancy is still considered key to identification. Yet, IDEA 2004 and the DSM-5 moved away from this requirement due to a lack of evidence that SLD varies with IQ and numerous philosophical and technical challenges to the notion of discrepancy (Fletcher, Lyon, Fuchs, & Barnes, 2019).

These three stands of inquiry into SLD use a variety of concepts (e.g., word blindness, strephosymbolia, dyslexia and alexia, dyscalculia and acalculia, dysgraphia and agraphia), which are sometimes differentiated and sometimes used synonymously, generating confusion in the literature. Given the heterogeneity of their manifestation and these diverse historical influences, it has been difficult to agree on the best way to identify SLD, although there is consensus that their core is unexpected underachievement.

Cognitive Models of SLD

A rich literature on cognitive models of SLD (Elliott & Grigorenko, 2014; Fletcher et al., 2019) provides the basis for five central ideas. First, SLD are componential (Melby-Lervåg, Lyster, & Hulme, 2012; Peng & Fuchs, 2016): Their academic manifestations arise on a landscape of peaks, valleys, and canyons in various cognitive processes, such that individuals with SLD have weaknesses in specific processes, rather than global intellectual disability (Morris et al., 1998). Second, the cognitive components associated with SLD, just like academic skills and instructional response, are dimensional and normally distributed in the general population (Ellis, 1984), such that understanding typical acquisition should provide insight into SLD and vice versa (Rayner, Foorman, Perfetti, Pesetsky, & Seidenberg, 2001). Third, each academic and cognitive component may have a distinct signature in the brain (Figure 3) and genome (Figure 4). These signatures and etiologies likely overlap because they are correlated, but are not interchangeable, as their unique features substantiate the distinctness of various SLD (Vandermosten, Hoeft, & Norton, 2016). Fourth, the overlap at least partially explains their rates of comorbidity (Berninger & Abbott, 2010; Szucs, 2016; Willcutt et al., 2013).

Specific Types of SLD

The DSM-5 and IDEA 2004 reflect agreement that SLD can occur in word reading and spelling (Specific Word Reading Disability; SWRD) and in specific reading comprehension disability (SRCD). SWRD represents difficulties with beginning reading skills due at least in part to phonological processing deficits, while other language indicators (e.g., vocabulary) may be preserved (Pennington, 2009). In contrast, SRCD (Cutting et al., 2013), which is more apparent later in development, is associated with non-phonological language weaknesses (Scarborough, 2005).

Math SLDs are differentiated as calculations (SMD) versus problem solving (word problems) SLD, which are associated with distinct cognitive deficits (L. S. Fuchs et al., 2010) and require different forms of intervention (L. S. Fuchs et al., 2014). Calculation is more linked to attention and phonological processing, while problem solving is more linked to language comprehension and reasoning; working memory has been associated with both.

Specific written expression disability, SWED (Berninger, 2004; Graham, Collins, & Rigby-Wills, 2017) occurs in the mechanical act of writing (i.e., handwriting, keyboarding, spelling), associated with fine motor-perceptual skills, or in composing text (i.e., planning and revising, understanding genre), associated with oral language skills, executive functions, and the automaticity of transcription skills. Although each domain varies in its cognitive correlates, treatment, and neurobiology, there is overlap.

The Decline in SLD Identification Rates

The percentage of children served by federally mandated special education programs, out of total public school enrollment, increased from 8.3 percent to 13.8 percent between 1976-77 and 2004-05. Much of this overall increase can be attributed to a rise in the percentage of students identified as having SLD from 1976-77 (1.8 percent) to 2004-05 (5.7 percent). The overall percentage of students being served in programs for those with disabilities decreased between 2004-05 (13.8 percent) and 2013-14 (12.9 percent). However, there were different patterns of change in the percentages served with some specific conditions between 2004-05 and 2013-14. The percentage of children identified with SLD declined from 5.7 percent to 4.5 percent of the total public school enrollment during this period. This number is highly variable by state: for example, in 2011 it ranged from 2.3% in Kentucky to 13.8% in Puerto Rico, as there is much variability in the procedures used to identify SLD, and disproportional demographic representation.

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