SLD Identification: An Analysis of State Policies
Assistant Professor of Special Education, Midwestern State University
Tammy L. Stephens
Assistant Professor of Special Education, Texas
The reauthorization of the Individuals with Disabilities Education
Improvement Act (IDEA; 2004) has resulted in many changes in the
field of special education; specifically in the eligibility criteria
used to determine the presence of a specific learning disability.
Results indicate variability among the states regarding eligibility
with all states using response to intervention and the majority
of states allowing the use of various discrepancy models.
The 2004 Individuals with Disabilities Education Improvement
Act (IDEA; 2004) and subsequent regulations published August
have significantly changed the way students suspected of having
specific learning disabilities (SLD) are identified and found
eligible for special education. Specifically, under IDEA (2004),
school districts are no longer required to use a discrepancy
model when determining eligibility, but instead, may use alternative
means (e.g., response-to-intervention or processing deficit approaches)
to identify students.
students as having a learning disability, local education agencies
(LEAs) must use criteria set forth by their
respective state education agencies (SEAs). While consistencies
in the identification of specific learning disabilities may occur
within states, considerable differences occur in the identification
process between states (Ahearn, 2003; Ahearn, 2008; Zirkel & Krohn,
2008). To further complicate matters, the lack of consensus concerning
the operational definition of SLD , selecting the most effective
methods of identification (Flanagan, Ortiz, Alfonso & Dynda,
2006; Fletcher, Denton, & Francis, 2005; Fletcher, Francis,
Morris, & Lyon, 2005; Kavale, Holdnack, & Mostert, 2005;
Kavale, Kauffman, Bachmeier, & LeFever, 2008; Van den Broek,
2002) continues to be the topic of significant debate. This article
will describe the contemporary approaches to specific learning
disability identification and the eligibility criteria selected
by each state.
Contemporary Approaches to Identification
Current identification approaches can be classified into three
broad models: (a) discrepancy approaches, (b) response-to-intervention
(RTI) and problem solving approaches, and (c) the processing
Prior to the IDEA regulatory changes in 2006, mathematical approaches,
specifically the discrepancy model, have been the primary approach
to identification of specific learning disabilities. (Baer, 2000;
Dombrowski, Kamphaus, & Reynolds, 2004; Frankenberger & Fronzaglio,
1991; Kavale, 2002; Meyer, 2000). According to IDEA (2004), states
are not allowed to “require the use of severe discrepancy
between intellectual ability and achievement,” however,
it remains permissible to use along with RTI and “other
alternative research-based procedures (IDEA, 20 U.S.C.§1414
(b)(6)(A).” The underlying concept of discrepancy approaches
is that specific learning disabilities are operationalized as “unexpected
underachievement” (Dombrowski et al., 2004; Kavale, 2002;
Proctor & Prevatt, 2003).
Response- to- Intervention (RTI) is a multi-tiered prevention model
of support that delivers interventions and services at increasing
levels of intensity based on the response of the student (Bradley,
Danielson, & Doolittle, 2007).This approach is dependent
upon a systematic process that includes: (a) the application
of scientific, evidence-based interventions delivered in general
education, (b) monitoring the progress of students response to
these interventions, and (c) the use of RTI data to make informed
instructional decisions. While many of the concepts of RTI have
been familiar to educators for years, RTI gained legal status
when it was included in Public Law 108-446, the reauthorized
Individuals with Disabilities Education Improvement Act 2004
(Bradley, et al., 2007)
Processing Deficit Approaches
Identification based on processing deficits approaches have primarily
focused on operationalizing the federal definition of SLD and
the processes linked to reading such as “phonological processing.” According
to Ahearn (2003), there is some agreement among professionals
that certain psychological processing problems interfere with
a student’s learning such as limitations in working memory
capacity, phonological processing deficits, and auditory perception.
Currently there is not widespread acceptance that processing
deficit approaches are a viable method of identifying SLD (Bradley,
et al., 2002, p. 797). However, examining processing deficits
has given meaning to the most salient component of the federal
definition of SLD?a disorder in one or more of the basic psychological
processes and has resulted in some states using this approach
as an allowable methodology (Fiorello, Hale, & Snyder, 2006;
Flanagan et al., 2006; Kavale et al., 2005).
Confusion and debate regarding the operational definition of SLD
has resulted in a lack of consensus regarding the use of one specific
eligibility model across the United States. Specifically, an assortment
of eligibility models defined within this article are currently
being utilized within school districts throughout the United States.
Therefore, the purpose of this study is to identify which eligibility
models are most prominently used within LD eligibility determination
since the reauthorization of IDEA (2004).
Data were collected by accessing each state’s education website
and locating their respective special education rules and regulations.
The following procedures were applied: (a) the Special Education
Department from each of the fifty states’ Department of Education
was accessed via internet searches, (b) the special education rules
and regulations for each state were downloaded from the educational
site, (c) using a checklist to organize eligibility models, the
two researchers reviewed each states’ rules and regulations
and (d) the results were analyzed and compiled within a table.
Continue to Allow the Use of the Discrepancy Model
The majority of the states allow for the continued use of the discrepancy
model when determining SLD eligibility. Specifically, thirty-nine
(n = 39) states indicated that local education agencies may continue
to utilize the discrepancy model as an option of identification.
Of the thirty-nine states which continue to allow the use of
a severe discrepancy model, twenty-nine (n = 29) allow for the
use of a severe discrepancy and/or RTI. Furthermore, ten (n =
10) allow for the use of a severe discrepancy model, RTI, and/or
an alternative research-based method of identification.
Elimination of the Discrepancy Model
Of the fifty states analyzed, eleven states (n = 11) were identified
as prohibiting the use of the discrepancy model for eligibility.
Instead of allowing the use of the discrepancy model, the states
vary in the type of criteria they allow. For example, Indiana
(Indiana State Board of Education, 2008) prohibits the use of
the discrepancy model and instead allows the use of RTI and/or
the use of a research-based method which assesses patterns of
strengths and weaknesses between cognitive abilities and achievement.
Explicit Mention of Professional Judgment
Many states have placed increased emphasis on the use of the “professional
judgment” of educational personnel when determining eligibility.
Specifically, Arizona, Georgia, and New Mexico explicitly mention
the implementation of “professional judgment” within
their state rules and regulations. According to the Georgia state
regulations, the ultimate determination of SLD eligibility is determined
through professional judgment using multiple supporting evidences
to include data collected from norm-referenced assessments and/or
benchmarks, information from the student’s teacher regarding
classroom routines and instruction, information provided regarding
supplementary instruction, and information obtained from parents
and school records.
Additional Criteria for Specific Learning Disability Eligibility
Several states allow assessment personnel to use a “research-based
alternative eligibility method” when determining eligibility.
Of the fifty states, twenty-one (N = 21) allow for the use of an
alternative method of eligibility, generally by determining if
a student exhibits a pattern of strengths and weaknesses and/or
examining specific areas of cognitive processes that interfere
with learning. The following states will be briefly described to
illustrate these approaches: Indiana and Texas.
Indiana’s Special Education rules (2008) described SLD as “neurological
in origin” and allow “intellectual development that
is determined by the group to be relevant to the identification
of a specific learning disability” to be used as evidence
to support their findings. Specific cognitive processes that are
linked to specific academic skills are assessed. For example, nonverbal
problem solving, working and long-term memory, processing speed,
and attention are assessed when a student has difficulty in math.
In a similar fashion, the commissioner’s rules concerning
special education in Texas (2008) permits examining a pattern of
strengths and weaknesses and examining specific areas of cognitive
processing and linking them to areas of achievement as a method
of identification. In addition to not achieving adequately on age
or grade level achievement standards, a student may be considered
learning disabled if he or she: (II) exhibits a pattern of strengths
and weaknesses in performance, achievement, or both relative to
age, grade-level standards, or intellectual ability, as indicated
by significant variance among specific areas of cognitive function,
such as working memory and verbal comprehension, or between specific
areas of cognitive function and academic achievement (p.4).
The reauthorization of the Individuals with Disabilities Education
Improvement Act (IDEA, 2004) has resulted in new guidelines for
eligibility in the area of specific learning disability. State
education agencies have been charged with the responsibility
of interpreting federal regulations and setting guidelines for
local education agencies to follow when determining eligibility.
Initial analyses of state guidelines indicate much variability
continues to exist in the eligibility models being used across
the fifty states. In adherence to federal guidelines, all state
education agencies allow for the use of a response-to-intervention
model in some form. Additionally, the majority of the states
continue to allow for the use of a discrepancy model as an allowable
US Dept. of Education Guidance to States on RtI:
On January 21 2011, the Office of Special Education Programs at the U.S. Dept. of Education issued a memorandum to State Directors of Special Education regarding the use of RtI to delay-deny an evaluation for eligibility under the IDEA.
E.M. (2003). Specific learning disability: Current approaches
to identification and
proposals for change. Retrieved October 3, 2008 from http://www.projectforum.org/documentsearch.cfm
Ahearn, E.M. (2008). State eligibility requirements for specific learning disabilities.
October 3, 2008 from http://www.projectforum.org/documentsearch.cfm
Anthony, J.L., & Francis, D.J. (2005). Development of phonological awareness.
Directions in Psychological Science, 14, 255-259.
R.D. (2000). Issues in severe discrepancy measurement: A technical
assistance paper for
special educators. Logan, UT: Utah State University, Center for Persons with
Bradley, R., Danielson, L., & Hallahan, D. (2002). Identification of learning
Research to practice. Mahwah, NJ: Lawrence Erlbaum.
Bradley, R., Danielson, L., & Doolittle, J. (2007). Responsiveness to intervention:
Teaching Exceptional Children, 39, 8-12.
S. C., Kamphaus, R.W., & Reynolds, C.R. (2004). After the
demise of the
discrepancy: Proposed learning disabilities diagnostic criteria. Professional
Psychology: Research and Practice, 35, 364-372.
Fiorello, C.A., Hale, J.B., & Snyder, L.E. (2006). Cognitive hypothesis
testing and response to
intervention for children with reading problems. Psychology in the Schools,
Flanagan, D.P., ORTIz. S.O., Alfonso, V.C., & Dynda, A.M. (2006). Integration
of response to
intervention and norm-referenced tests in learning disability identification:
Learning from the tower of Babel. Psychology in the Schools, 43, 807-825.
Fletcher, J.M., Denton, C., & Francis, D.J. (2005). Validity of alternative
approaches for the
identification of learning disabilities: Operationalizing unexpected achievement.
Journal of Learning Disabilities, 38, 545-552.
Fletcher, J.M., Francis, D.J., Morris, R.D., & Lyon, G.R. (2005). Evidence-based
learning disabilities in children and adolescents. Journal of Clinical Child
and Adolescent Psychology, 34, 506-522.
W., & Fronzaglio, K. (1991). A review of states’ criteria
and procedures for
identifying children with learning disabilities. Journal of Learning Disabilities,
with Disabilities Education Improvement Act of 2004 (IDEA), Pub.L.No.108-446,
118 Stat. 2647 (2004), [Amending 20 U.S.C. § § 1400 et seq.].
K.A. (2002). Discrepancy models in the identification of learning
disability. In R. Bradley, L. Danielson, & D.P. Hallahan
(Eds.), Identification of learning disabilities: Research to
practice (pp. 369-426). Mahwah, NJ: Erlbaum.
K.A., Holdnack, J.A., & Mostert, M.P. (2005). Responsiveness
to intervention and the
identification of specific learning disability: A critique and alternative
proposal. Learning Disability Quarterly, 28-2-16.
K.A., Kauffman, J.M., Bachmeier, R. J., & LeFever, G.B. (2008).
intervention: Separating the rhetoric of self congratulation from the reality
of specific learning disability identification. Learning Disability Quarterly,
M.S., (2000). The ability-achievement discrepancy: Does it contribute
understanding of learning disabilities. Educational Psychology Review, 12,
B., & Prevatt, F. (2003). Agreement among four models used
for diagnosing learning
disabilities. Journal of Learning Disabilities, 36, 459-467.
den Broek, W. (2002). The misconception of the regression-based
operationalization in the definition and research of learning disabilities.
Learning Disabilities, 35, 194-204.
O.A., & Krohn, N. (2008). RTI after IDEA: A survey of state
laws. Teaching Exceptional
Children, 40, 71-73.