What is meant by the achievement ability discrepancy?
the difference among what a person is know to be capable of in terms of academic abilities, and how they actually perform academically. Show
ABILITY-ACHIEVEMENT DISCREPANCY: "Leslie's ability-achievement discrepancy was larger than she expected it to be following receipt of her test score." Related Psychology Terms
Cite this page: N., Sam M.S., "ABILITY-ACHIEVEMENT DISCREPANCY," in PsychologyDictionary.org, April 7, 2013, https://psychologydictionary.org/ability-achievement-discrepancy/ (accessed December 22, 2022). In deciding whether a student has a severe discrepancy between her intellectual ability and her achievement in oral expression, listening comprehension, written expression, basic reading skills, reading comprehension, mathematical calculation, or mathematical reasoning, a school district must review all relevant material available on the student. No single score or product of scores or test or procedure shall be used as the only factor in making this decision. Standardized tests of ability and achievement are often used. If a student’s achievement scores are sufficiently below his ability scores, it indicates that the student has the severe discrepancy required for special education eligibility under this model. As part of their assessment, the assessor will convert the raw scores from both the academic and cognitive testing to a scale of 100 and then compare them. If there is between a 20-22 point difference (1.5 standard deviation), this is a strong indication that the student has a learning disability. The discrepancy must be corroborated by other evaluation information, such as from other tests, scales, instruments, observations, and work samples. [5 C.C.R. Sec. 3030(b)(10)(B).] Sometimes standardized tests cannot be used for particular students (such as IQ tests for African-American students). In that case, the discrepancy between ability and achievement must be measured by some other method. The alternative method of assessment must be specified in the assessment plan, which a parent must sign before any testing may be conducted. [5 C.C.R. Sec. 3030(b)(10)(B)(2).] If standardized tests do not show a severe discrepancy between ability and achievement, an IEP team can still find that a severe discrepancy exists. The IEP team must prepare a report on the student describing the basic psychological process in which the discrepancy exists, the degree of discrepancy, and the basis and method used to determine the discrepancy. The report must include information from tests, from the parent, from the pupil’s teacher, from observations of the student, and from his classroom performance and work samples. However, limited school experience or poor school attendance cannot be the primary cause of the severe discrepancy. [5 C.C.R. Sec. 3030(b)(10)(B)(3) & (4).] The category of specific learning disability (SLD) remains the largest and most contentious area of special education. A primary problem is overidentification of students with SLD as evidenced by the SLD category representing approximately5%of the school population and 50% of the special education population. Partially responsible for this problem is the overreliance on the ability-achievement discrepancy criterion as the sole indicator of SLD, a practice that remains widespread. Recently, new ways to conceptualize and define SLD have been proposed in an attempt to remedy the overidentification problem (e.g., Fletcher, Coulter, Reschly, and Vaughn, 2004). Most popular is a model that conceptualizes SLD in terms of a failure to respond to intervention (RTI) (Berninger and Abbott, 1994). Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves. This is a preview of subscription content, access via your institution. PreviewUnable to display preview. Download preview PDF. Unable to display preview. Download preview PDF. Aaron, P. G. (1997). The impending demise of the discrepancy formula. Review of Educational Research, 67, 461–502. CrossRef Google Scholar Al-Otaiba, S., & Fuchs, D. (2002). Characteristics of children who are unresponsive to early literacy intervention: a review of the literature. Remedial and Special Education, 23, 300–315. Google Scholar Ames, L. B. (1968). A low intelligence quotient often not recognized as the chief cause of many learning difficulties. Journal of Learning Disabilities, 1, 735–739. Google Scholar Bateman, B. D. (1965). An educator's view of a diagnostic approach to learning disabilities. In J. Hellmuth (Ed.), Learning Disorders (Vol. 1, pp. 217–239). Seattle: Special Child Publications. Google Scholar Berninger, V. W. & Abbott, R. D. (1994). Redefining learning disabilities: moving beyond aptitude–achievement discrepancies to failure to respond to validated treatment protocols. In G. R. Lyon (Ed.), Frames of Reference for the Assessment of Learning Disabilities (pp. 163–183). Baltimore: Paul H. Brookes. Google Scholar Buck, G. H., Polloway, E. A., Smith-Thomas, A., & Cook, K. W. (2003). Prereferral intervention processes: a survey of state practices. Exceptional Children, 69, 349–360. Google Scholar Buckhalt, J. A. (2002). A short history of j: psychometrics' most enduring and controversial construct. Learning and Individual Differences, 13, 101–114. CrossRef Google Scholar Carroll, J. B. (1993). Human Cognitive Abilities: A Survey of Factor-Analytic Studies. Cambridge, UK: Cambridge University Press. Google Scholar Carroll, J. B. (1997). The three-stratum theory of cognitive abilities. In D. P. Flanagan, J. L. Genshaft, & P. L. Harrison (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (pp. 122–130). New York: Guilford. Google Scholar Carroll, J. B. & Horn, J. L. (1981). On the scientific basis of ability testing. American Psychologist, 36, 1012–1020. CrossRef Google Scholar Chalfant, J. D. & King, F. S. (1976). An approach to operationalizing the definition of learning disabilities. Journal of Learning Disabilities, 9, 228–243. Google Scholar Coles, G. S. (1978). The learning-disability test battery: empirical and social issues. Harvard Educational Review, 48, 313–340. Google Scholar Cruickshank, W. M. (1977). Myths and realities in learning disabilities. Journal of Learning Disabilities, 10, 51–58. Google Scholar Danielson, L., Doolittle, J., & Bradley, R. (2005). Past accomplishments and future challenges. Learning Disability Quarterly, 28, 137–139. Google Scholar Das, J. P. & Naglieri, J. A. (1997). Das-Naglieri Cognitive Assessment System. Itasca, IL: Riverside Publishing. Google Scholar Dean, Y. J. & Burns, M. K. (2002). Inclusion of intrinsic processing difficulties in LD diagnostic models: a critical review. Learning Disability Quarterly, 25, 170–176. CrossRef Google Scholar Dean, R. & Woodcock, R. W. (1999). The WJ-R and Bateria-R in Neuropsychological Assessment. (Woodcock Psychological and Educational Assessment Research Report no. 3.) Itasca, IL: Riverside. Google Scholar Evans, J. H., Carlsen, R. N., & McGrew, K. S. (1993). Classification of exceptional students with the Woodcock-Johnson Psycho-Educational Battery-Revised. Journal of Psychoeducational Assessment [Monograph Series: WJ-R Monograph], 6–19. Google Scholar Flanagan, D. P. (2000). Wechlser-based CHC cross-battery assessment and reading achievement: Strengthening the validity of interpretations drawn from Wechsler test scores. School Psychology Quarterly, 15, 295–229. Google Scholar Flanagan, D. P. (2003). Use of the WJ III within the context of a modern operational definition of LD. In F. Schrank & D. P. Flanagan (Eds.), Clinical Use and Interpretation of the WJ III. Burlington, MA: Elsevier, Academic Press. Google Scholar Flanagan, D. P., Genshaft, J. L., & Harrison, P. L. (Eds.) (1997). Contemporary Intellectual Assessment: Theories, Tests, and Issues. New York: Guilford. Google Scholar Flanagan, D. P. & Harrison, P. L. (Eds.). (2005). Contemporary Intellectual assessment (2nd ed.) Theories, Tests, and Issues. New York: Guilford. Google Scholar Flanagan, D. P. & Kaufman, A. S. (2004). Essentials of WISC-IV assEssment. Hoboken, NJ: Wiley. Google Scholar Flanagan, D. P., Keiser, S. Berneir, J., & Ortiz, S. O. (2003). Diagnosing Learning Disability in Adulthood. Boston: Allyn & Bacon. Google Scholar Flanagan, D. P. & Ortiz, S. O. (2001). Essentials of Cross-Battery Assessment. New York: Wiley. Google Scholar Flanagan, D. P., Ortiz, S. O., Alfonso, V. C., & Dynda, A. M. (2006a). Integration of response-to-intervention and norm-referenced tests in learning disability identification: Learning from the tower of Babel. Psychology in the Schools, 43(7), 807–825. CrossRef Google Scholar Flanagan, D. P., Ortiz, S. O., Alfonso, V. C., & Mascolo, J. T. (2002). The Achievement Test Desk Reference (ATDR): Comprehensive Assessment and Learning Disabilities. Boston: Allyn & Bacon. Google Scholar Flanagan, D. P., Ortiz, S. O., Alfonso, V. C., & Mascolo, J. T. (2006b). The Achievement Test Desk Reference –Second Edition (ATDR-II): A Guide to Learning Disability Identification. New York: Wiley. Google Scholar Flanagan, D. P., Ortiz, S. O., & Alfonso, V. C. (2007). Essentials of Cross-Battery Assessment with C/D ROM (2nd ed.). New York: Wiley. Google Scholar Fletcher, J. M., Coulter, W. A., Reschly, D. J., & Vaughn, S. (2004). Alternative approaches to the definition and identification of learning disabilities: some questions and answers. Annals of Dyslexia, 54, 304–331. CrossRef PubMed Google Scholar Fletcher, J. M., Denton, C., & Francis, D. J. (2005). Validity of alternative approaches for the identification of learning disabilities: operationalizing unexpected underachievement. Journal of Learning Disabilities, 38, 545–552. PubMed Google Scholar Fletcher, J. M., Foorman, B. R., Boudousquie, A., Schatschneider, C., & Francis, D. J. (2002). Assessment of reading and learning disabilities: a research-based intervention-oriented approach. Journal of School Psychology, 40, 27–63. CrossRef Google Scholar Fletcher, J. M., Francis, D. J., Shaywitz, S. E., Lyon, G. R., Foorman, B. R., Stuebing. K. K., et al. (1998). Intelligent testing and the discrepancy model for children with learning disabilities. Learning Disabilities Research and Practice, 13, 186–203. Google Scholar Francis, D. J., Fletcher, J. M., Stuebing, K. K., Lyon, G. R., Shaywitz, B. A., & Shaywitz, S. A. (2005). Psychometric approaches to the identification of LD: IQ and achievement scores are not sufficient. Journal of Learning Disabilities, 38, 98–108. PubMed Google Scholar Fuchs, D., Deshler, D. D., & Reschly, D. J. (2004). National Research Center on Learning Disabilities: multimethod studies of identification and classification issues. Learning Disability Quarterly, 27, 189–195. CrossRef Google Scholar Fuchs, L. S., & Fuchs, D. (1998). Treatment validity: a unifying concept for reconceptualizing identification of learning disabilities. Learning Disabilities Research and Practice, 13, 204–219. Google Scholar Fuchs, D., Fuchs, L. S., & Compton, D. L., (2004). Identifying reading disabilities by responsiveness-to-instruction: specifying measures and criteria. Learning Disability Quarterly, 27, 216–227. CrossRef Google Scholar Fuchs, D., Mock, D., Morgan, P. L., & Young, C. L. (2003). Responsiveness-to-intervention: definitions, evidence, and implications for the learning disabilities construct. Learning Disabilities Research and Practice, 18, 157–171. CrossRef Google Scholar Galaburda, A. M. (2005). Neurology of learning disabilities: what will the future bring? The answer comes from the successes of the recent past. Learning Disability Quarterly, 28, 107–109. Google Scholar Glutting, J. J., Youngstrom, E. A., Ward, T., Ward. S., & Hale, R. L. (1997). Incremental efficiency of WISC-III factor scores in predicting achievement: What do they tell us? Psychological Assessment, 9, 295–301. CrossRef Google Scholar Gordon, M., Lewandowski, L., & Keiser, S. (1999). The LD label for relatively well-functioning students: a critical analysis. Journal of Learning Disabilities, 32, 485–490. PubMed Google Scholar Gottfredson, L. S. (1997a). Mainstream science on intelligence: an editorial with 52 signatories, history, and bibliography. Intelligence, 24, 13–24. CrossRef Google Scholar Gottfredson, L. S. (1997b). Why g matters: The complexity of everyday life. Intelligence, 24, 79–134. CrossRef Google Scholar Gregg, N. Coleman, C. & Knight, D. (2003). Use of the Woodcock-Johnson III in the diagnosis of learning disabilities. In Schrank, F. A. and Flanagan, D. P. (Eds.), WJ III Clinical Use and Interpretation: Scientist-Practitioner Perspectives (pp. 176–199). New York: Academic Press. Google Scholar Gresham, F. M. (2002). Responsiveness to intervention: an alternative approach to the identification of learning disabilities. In R. Bradley, L. Danielson, & D. Hallahan (Eds.), Identification of Learning Disabilities: Research to Practice (pp. 467–519). Mahwah, NJ: Lawrence Erlbaum. Google Scholar Horn, J. L. (1988). Thinking about human abilities. In J. Nesselroade & R. Cattell (Eds.), Handbook of Multivariate Psychology(rev. ed., pp. 645–683). New York: Academic Press. Google Scholar Johns, B. H. (2003). NCLB and IDEA: never the twain should meet. Learning Disabilities: A Multidisciplinary Journal, 12, 89–91. Google Scholar Kaufman, A. S. & Kaufman, N. L. (2001). Assessment of specific learning disabilities in the new millennium: Issues, conflicts, and controversies. In A. Kaufman & N. Kaufman (Eds.), Specific Learning Disabilities and Difficulties in Children and Adolescents: Psychological Assessment and Evaluation (pp. 433–461). Cambridge, UK: Cambridge University Press. Google Scholar Kaufman, A. S. & Kaufman, N. L. (2004). Kaufman Assessment Battery for Children—Second Edition. Circle Pines, MN: American Guidance Service. Google Scholar Kaufman, J. C., Kaufman, A. S., Kaufman-Singer, J., & Kaufman, N. L. (2005). The Kaufman Assessment Battery for Children-Second Edition and the Kaufman Adolescent and Adult Intelligence Test. In D. P. Flanagan and P. L. Harrison (Eds.), Contemporary intellectual assessment: Theories, Tests, and Issues (2nd ed.) (pp. 344–370). New York: Guilford. Google Scholar Kaufman, A. S., Lichtenberger, E. O., Fletcher-Janzen, E., & Kaufman, N. L. (2004). Essentials of KABC-II Assessment. New York: Wiley. Google Scholar Kavale, K. A. (2002). Discrepancy models in the identification of learning disability. In R. Bradley, L. Danielson, & D. Hallahan (Eds.), Identification of Learning Disabilities: Research to Practice (pp. 287–333). Mahwah, NJ: Lawrence Erlbaum. Google Scholar Kavale, K. A. (2005). Identifying specific learning disability: is responsiveness to intervention the answer? Journal of Learning Disabilities, 38, 553–562. PubMed Google Scholar Kavale, K. A. & Forness, S. R. (1995). The Nature of Learning Disabilities: Critical Elements of Diagnosis and Classification. Mahwah, NJ: Lawrence Erlbaum. Google Scholar Kavale, K. A. & Forness, S. R. (2000a). Auditory and visual perception processes and reading ability: a quantitative reanalysis and historical reinterpretation. Learning Disability Quarterly, 23, 253–270. CrossRef Google Scholar Kavale, K. A. & Forness, S. R. (2000b). What definitions of learning disability say and don't say: a critical analysis. Journal of Learning Disabilities, 33, 239–256. Google Scholar Kavale, 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. Google Scholar Kavale, K. A. & Nye, C. (1991). The structure of learning disabilities. Exceptionality, 2, 141–156. Google Scholar Kavale, K. A. & Reese, J. H. (1992). The character of learning disabilities: an Iowa profile. Learning Disability Quarterly, 15, 74–94. CrossRef Google Scholar Kavale, K. A., Kaufman, A. S., Naglieri, J. A., & Hale, J. B. (2005). Changing procedures for identifying learning disabilities: the danger of poorly supported ideas. The School Psychologist, 59, 16–25. Google Scholar Keogh, B. K. (1987). Learning disabilities: in defense of a construct. Learning Disabilities Research, 3, 4–9. Google Scholar Keogh, B. K. (1994). A matrix of decision points in the measurement of learning disabilities. In G. R. Lyon (Ed.), Frames of Reference for the Assessment of Learning Disabilities: New Views on Assessment Issues(pp. 15–26). Baltimore: Paul H. Brookes. Google Scholar Keogh, B. K. (2005). Revisiting classification and identification. Learning Disability Quarterly, 28, 100–102. Google Scholar Kibby, M. Y. & Hynd, G. W. (2001). Neurobiological basis of learning disabilities. In D. Hallahan & B. Keogh (Eds.), Research and Global Perspectives in Learning Disabilities: Essays in Honor of William M. Cruickshank (pp. 25–42). Mahwah, NJ: Lawrence Erlbaum. Google Scholar Lyon, G. R., Fletcher, J. M., Shaywitz, S. E., Shaywitz, B. A., Torgensen, J. K., Wood, F. B., et al. (2001). Rethinking learning disabilities. In C. Finn, R. Rotherham, & C. Hokanson (Eds.), Rethinking Special Education for a New Century (pp. 259–287). Washington, DC: Thomas B. Fordham Foundation. Google Scholar MacMillan, D. L. & Siperstein, G. N. (2002). Learning disabilities as operationally defined by schools. In R. Bradley, L. Danielson, & D. Hallahan (Eds.), Identification of Learning Disabilities: Research to Practice (pp. 287–333). Mahwah, NJ: Lawrence Erlbaum. Google Scholar MacMillan, D. L., Gresham, F. M., & Bocian, K. M. (1998). Discrepancy between definitions of learning disabilities and school practices: an empirical investigation. Journal of Learning Disabilities, 31, 314–326. PubMed Google Scholar Mann, L. (1971). Psychometric phrenology and the new faculty psychology: the case against ability assessment and training. Journal of Special Education, 5, 3–14. Google Scholar Mather, N. & Schrank, F. A. (2003). Using the Woodcock-Johnson III discrepancy procedures for diagnosing learning disabilities. In F. A. Schrank and D. P. Flanagan (Eds.), WJ III Clinical Use and Interpretation: Scientist-Practitioner Perspectives (pp. 176–199). New York: Academic Press. Google Scholar McGrew, K. S. & Flanagan, D. P. (1998). The Intelligence Test Desk Reference (ITDR): Gf–Gc Cross-Battery Assessment. Boston: Allyn & Bacon. Google Scholar McGrew, K. S., Flanagan, D. P., Keith, T. Z., & Vanderwood, M. (1997). Beyond g: The impact of Gf-Gc specific cognitive abilities research on the future use and interpretation of intelligence tests in the schools. School Psychology Review, 26, 177–189. Google Scholar McGrew, K. S., & Knopik, S. N. (1996). The relationship between intra-cognitive scatter on the Woodcock-Johnson Psycho-Educational Battery—Revised and school achievement. Journal of School Psychology, 34, 351–364. CrossRef Google Scholar McMaster, K. L., Fuchs, D., Fuchs, L. S., & Compton, D. L (2005). Responding to nonresponsiveness: an experimental field trip of identification and intervention methods. Exceptional Children, 71, 445–463. Google Scholar Mellard, D. F., Deshler, D. D., & Barth, A. (2004). LD identification: it's not simply a matter of building a better mousetrap. Learning Disability Quarterly, 27, 229–243. CrossRef Google Scholar Mellard, D. F., Byrd, S. E., Johnson, E., Tollefson, J. M., & Boesche, L. (2004). Foundations and research on identifying model responsiveness-to-intervention sites. Learning Disability Quarterly, 27, 243–256. CrossRef Google Scholar Naglieri, J. A. (2005). The Cognitive Assessment System. In D. P. Flanagan and P. L. Harrison (Eds.), Contemporary Intellectual Assessment: Theories, Tests, and Issues (2nd ed.) (pp. 441–460). New York: Guilford. Google Scholar Nelson, J. R., Benner, G. J., & Gonzalez, J. (2003). Learner characteristics that influence the treatment effectiveness of early literacy interventions: a meta-analytic review. Learning Disabilities Research and Practice, 18, 255–267. CrossRef Google Scholar Oakley, D. (2006). The Relationship between Intra-Cognitive Scatter on the WJ III and School Achievement. Unpublished doctoral dissertation. St. John's University, New York. Google Scholar Peterson, K. M. H. & Shinn, M. R. (2002). Severe discrepancy models: which best explains school identification practices for learning disabilities? School Psychology Review, 31, 459–746. Google Scholar Pugach, M. & Johnson, L. J. (1989). Prereferral interventions: progress, problems, and challenges. Exceptional Children, 56, 217–226. Google Scholar Reschly, D. J. & Hosp, J. L. (2004). State SLD identification policies and practices. Learning Disability Quarterly, 27, 197–213. CrossRef Google Scholar Roid, G. H. & Pomplun, M. (2005). Interpreting the Stanford-Binet Intelligence Scales, Fifth Edition. In D. P. Flanagan and P. L. Harrison (Eds.), Contemporary Intellectual A ssessment: Theories, Tests, and Issues (2nd ed.) (pp. 325–343). New York: Guilford. Google Scholar Rutter, M. & Yule, W. (1975). The concept of specific reading retardation. Journal of Child Psychology and Psychiatry, 16, 181–197. CrossRef PubMed Google Scholar Schrank, F. A. (2006). Assessment Service Bulletin 7: Specification of the Cognitive Processes Involved in Performance on the Woodcock-Johnson III NU. Itasca, IL: Riverside. Google Scholar Scruggs, T. E. & Mastropieri, M. A. (2002). On babies and bathwater: addressing the problems of identification of learning disabilities. Learning Disability Quarterly, 25, 155–168. CrossRef Google Scholar Shepard, L. A. & Smith, M. L. (1983). An evaluation of the identification of learning disabled students in Colorado. Learning Disability Quarterly, 6, 115–127. CrossRef Google Scholar Siegal, L. S. (1989). IQ is irrelevant to the definition of learning disabilities. Journal of Learning Disabilities, 489, 469–478. Google Scholar Siegel, L. S. (1999). Issues in the definition and diagnosis of learning disabilities: a perspective on Guckenberger v. Boston University. Journal of Learning Disabilities, 32, 304–319. PubMed Google Scholar Siegel, L. S. (2003). IQ-discrepancy definitions and the diagnosis of LD: introduction to the special issue. Journal of Learning Disabilities, 36, 2–3. PubMed Google Scholar Spear-Swerling, L. & Sternberg, R. J. (1996). Off Track: When Poor Readers Become “Learning Disabled.” Boulder, CO: Westview Press. Google Scholar Stanovich, K. E. (1985). Explaining the variance in reading ability in terms of psychological processes: what have we learned? Annals of Dyslexia, 35, 67–96. Google Scholar Stanovich, K. E. (1988). Explaining the differences between the dyslexic and the garden-variety poor reader: the phonological–core-variable–difference model. Journal of Learning Disabilities, 21, 141–156. Google Scholar Stanovich, K. E. (1991). Discrepancy definitions of reading disability: has intelligence led us astray? Reading Research Quarterly, 26, 7–29. CrossRef Google Scholar Stanvich, K. E. (1999). The sociopsychometrics of learning disabilities. Journal of Learning Disabilities, 32, 350–361. Google Scholar Stanovich, K. E. (2005). The future of a mistake: will discrepancy measurement continue to make the learning disabilities field a pseudoscience? Learning Disability Quarterly, 28, 103–106. Google Scholar Sternberg, R. J. & Grigorenko, E. L. (2002). Difference scores in the identification of children with learning disabilities: it's time to use a different method. Journal of School Psychology, 40, 65–83. CrossRef Google Scholar Stuebing, K. K., Fletcher, J. M., LeDoux, J. M., Lyon, G. R., Shaywitz, S. E., & Shaywitz, B. A. (2002). Validity of IQ-discrepancy classifications of reading disabilities: a meta-analysis. American Educational Research Journal, 39, 469–518. CrossRef Google Scholar Swanson, H. L., Trainin, G., Necoechea, D. M., & Hammill, D. D. (2003). Rapid naming, phonological awareness, and reading: a meta-analysis of the correlation evidence. Review of Educational Research, 73, 407–440. CrossRef Google Scholar Thorndike, R. L. (1963). The Concepts of Over- and Under-Achievement. New York: Teachers College Press. Google Scholar Torgensen, J. K. (1979). What shall we do with psychological processes? Journal of Learning Disabilities, 12, 514–521. CrossRef Google Scholar Torgensen, J. K. (2000). Individual differences in response to early interventions in reading: the lingering problem of treatment resisters. Learning Disabilities Research and Practice, 15, 55–64. CrossRef Google Scholar Truscott, S. D., Cohen, C. E., Sams, D. P., Sanborn, K. J., & Frank, A. J. (2005). The current state(s) of prereferral intervention teams: a report from two national surveys. Remedial and Special Education, 26, 130–140. CrossRef Google Scholar US Office of Education (1977). Assistance to states for education of handicapped children: Procedures for evaluating specific learning disabilities. Federal Register, 42, (250), 65082–65085. Washington, DC: US Government Printing Office. Google Scholar Vanderwood, M. L., McGrew, K. S., Flanagan, D. P., & Kieth, T. Z. (2002). The contribution of general and specific cognitive abilities to reading achievement. Learning and Individual Differences, 13, 159–188. CrossRef Google Scholar Vaughn, S., Linan-Thompson, S., & Hickman, P. (2003). Response to instruction as a means of identifying students with reading/learning disabilities. Exceptional Children, 69, 391–410. Google Scholar Vellutino, F. R., Scanlon, D. M., & Lyon, G. R. (2000). Differentiating between difficult-to-remediate and readily remediated poor readers: more evidence against the IQ–achievement discrepancy definition for reading disability. Journal of Learning Disabilities, 33, 223–238. PubMed Google Scholar Vukovic, R. K. & Siegel, L. S. (2006). The double-deficit hypothesis: a comprehensive analysis of the evidence. Journal of Learning Disabilities, 39(1), 25–47. PubMed Google Scholar Wagner, R. K. & Torgensen, J. K. (1987). The nature of phonological processing and its causal role in the acquisition of reading skills. Psychological Bulletin, 101, 192–212. CrossRef Google Scholar Woodcock, R. W. (1993). An information processing view of Gf-Gc theory. Journal of Psychoeducational Assessment, 8, 231–258. CrossRef Google Scholar Ysseldyke, J. (2005). Assessment and decision making for student with learning disabilities: what if this is as good as it gets? Learning Disability Quarterly, 28, 125–128. Google Scholar Download references Author informationAuthors and Affiliations
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Rights and permissionsReprints and Permissions Copyright information© 2007 Springer About this chapterCite this chapterKavale, K.A., Flanagan, D.P. (2007). Ability—Achievement Discrepancy, Response to Intervention, and Assessment of Cognitive Abilities/Processes in Specific Learning Disability Identification: Toward a Contemporary Operational Definition. In: Jimerson, S.R., Burns, M.K., VanDerHeyden, A.M. (eds) Handbook of Response to Intervention. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-49053-3_10 What is the ability achievement discrepancy analysis?Ability-Achievement Discrepancy (AAD) Analysis is one of three methods recommended by the Individuals with Disabilities Education Improvement Act (IDEIA, 2004) to establish eligibility for direct specialized instruction under the classification Specific Learning Disability (SLD).
What is the IQ academic achievement discrepancy model?The IQ-achievement discrepancy model assesses whether there is a significant difference between a student's scores on a test of general intelligence (e.g., an IQ test such as the WISC-IV) and scores obtained on a test of academic achievement (e.g., the Woodcock-Johnson Achievement Test).
What is a discrepancy score?A discrepancy score of a time interval is a numerical value that captures the discrepancy between the presence of the topic in the time interval and that outside the interval.
What is the discrepancy formula?However, the classic formula to calculate ad discrepancy (regardless of the metric) is: Subtract the number you received from the other party (be it sell or buy) Divide it by the other party's number and multiply by 100. The number you receive is the % of the discrepancy.
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