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Enhancing SLD Diagnoses Through the Identification of Psychological Processing Deficits

Published online by Cambridge University Press:  07 January 2014

Milton J. Dehn
Milton J. Dehn*
Affiliation:
Schoolhouse Educational Services, Onalaska, Wisconsin, USA University of Wisconsin-La Crosse, La Crosse, Wisconsin, USA
*
Address for correspondence: Milton J. Dehn, Ed.D., Program Director for Schoolhouse Educational Services, Onalaska, Wisconsin, USA. Email: milt@psychprocesses.com
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Abstract

After defining psychological processing and providing descriptions of 10 interrelated neuropsychological processes, the author proposes an integrated model for identifying an individual's pattern of psychological processing strengths, weaknesses, and deficits when conducting a specific learning disability (SLD) assessment. The model incorporates approaches from other pattern of strengths and weaknesses (PSW) models, while adding three requirements designed to reduce psychometric concerns about the identification procedures. Details for analysing cross-battery data and recommendations for applying processing deficits to SLD determination are included. In support of the model, the article reviews research that links psychological processing deficits with specific learning disabilities. The article concludes with a brief overview of evidence-based interventions for psychological processing deficits.

Keywords

Psychological processeslearning difficultyprocessing deficitscross-battery assessmentsSLD diagnosis
Type
Articles
Information
The Educational and Developmental Psychologist , Volume 30 , Issue 2 , December 2013 , pp. 119 - 139
Copyright
Copyright © Australian Psychological Society Ltd 2013 

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References

Alloway, T.P., & Copello, E. (2013). Working memory: The what, the why, and the how. The Australian Educational and Developmental Psychologist, 30 (2), 105–118.CrossRefGoogle Scholar
Atkinson, R.C., & Shiffrin, R.M. (1968). Human memory: A proposed system and its control processes. In Spence, K. & Spence, J. (Eds.), The psychology of learning and motivation (Vol. 2). New York: Academic Press.Google Scholar
Baddeley, A.D. (2006). Working memory: An overview. In Pickering, S.J. (Ed.), Working memory and education (pp. 1–31). Burlington, MA: Academic Press.Google Scholar
Baldo, J.V., & Dronkers, N.F. (2006). The role of inferior parietal and inferior frontal cortex in working memory. Neuropsychology, 20, 529–538.Google Scholar
Barkl, S., Porter, A., & Ginns, P. (2012). Cognitive training for children: Effects on inductive reasoning, deductive reasoning, and mathematics achievement in an Australian school setting. Psychology in the Schools, 49, 828–842.CrossRefGoogle Scholar
Barkley, R.A. (1997). ADHD and the nature of self-control. New York: Guilford Press.Google Scholar
Benson, N. (2008). Cattell-Horn-Carroll cognitive abilities and reading achievement. Journal of Psychoeducational Assessment, 26, 27–41.CrossRefGoogle Scholar
Berninger, V.W., & Richards, T.L. (2002). Brain literacy for educators and psychologists. San Diego: Academic Press.Google Scholar
Best, J.R., Miller, P.H., & Naglieri, J.A. (2011). Relations between executive function and academic achievement from ages 5 to 17 in a large, representative national sample. Learning and Individual Differences, 21, 327–336.Google Scholar
Bragard, A., Schelstraete, M., Snyers, P., & James, D. G. (2012). Word-finding intervention for children with specific language impairment: A multiple single-case study. Language, Speech, and Hearing Services in the Schools, 43, 222–234.CrossRefGoogle ScholarPubMed
Bus, A., & Van Ijzendoorn, M. (1999). Phonological awareness and early reading: A meta-analysis of experimental training studies. Journal of Educational Psychology, 91, 403–414.Google Scholar
Carroll, J.B. (1993). Human cognitive abilities: A survey of factor-analytic studies. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Catts, H.W. (1996). Defining dyslexia as a developmental language disorder: An expanded view. Topics in Language Disorders, 16, 14–29.Google Scholar
Comblain, A. (1994). Working memory in Down's syndrome: Training the rehearsal strategy. Down's Syndrome: Research and Practice, 2, 123–126.Google Scholar
Compton, D.L., Fuchs, L.S., Fuchs, D., Lambert, W., & Hamlett, C.L. (2012). The cognitive and academic profiles of reading and mathematics learning disabilities. Journal of Learning Disabilities, 45, 79–95.Google Scholar
Conway, R.N., & Ashman, A. (1989). Teaching planning skills in the classroom: The development of an integrated model. International Journal of Disability, Development and Education, 36, 225–240.CrossRefGoogle Scholar
Cormier, P., Carlson, J.S., & Das, J.P. (1990). Planning ability and cognitive performance: The compensatory effects of a dynamic assessment approach. Learning and Individual Differences, 2, 437–449.CrossRefGoogle Scholar
Dehn, M.J. (2007). Cognitive processing deficits. In Morris, R.J. & Mather, N. (Eds.), Evidence-based interventions for students with learning and behavioral challenges (pp. 258–287). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
Dehn, M.J. (2008). Working memory and academic learning: Assessment and intervention. Hoboken, NJ: Wiley.Google Scholar
Dehn, M.J. (2010). Long-term memory problems in children and adolescents: Assessment, intervention, and effective instruction. Hoboken, NJ: Wiley.Google Scholar
Dehn, M.J. (2012a). Children's Psychological Processes Scale. Onalaska, WI: Schoolhouse Educational Services.Google Scholar
Dehn, M.J. (2012b). Psychological Processing Analyzer. Stoddard, WI: Schoolhouse Educational Services.Google Scholar
Dehn, M.J. (2014). Essentials of processing assessment (2nd ed.). Hoboken, NJ: Wiley.Google Scholar
Deppeler, J.M., Taranto, A.M., & Bench, J. (2004). Language and auditory processing changes following Fast ForWord. Australian and New Zealand Journal of Audiology, 26, 94–109.Google Scholar
Dye, M.W., Green, C.S., & Bavelier, D. (2009). Increasing speed of processing with action video games. Current Directions in Psychological Science, 18, 321–326.CrossRefGoogle ScholarPubMed
Elliott, J.G., Gathercole, S.E., Alloway, T.P., Holmes, J., & Kirkwood, H. (2010). An evaluation of a classroom-based intervention to help overcome working memory difficulties and improve long-term academic achievement. Journal of Cognitive Education and Psychology, 9, 227–250.Google Scholar
Fey, M.E., Richard, G.J., Geffner, D., Kamhi, A.G., Medwetsky, L., Paul, D., . . . Schooling, T. (2011). Auditory processing disorder and auditory/language interventions: An evidence-based systematic review. Language, Speech, and Hearing Services in Schools, 42, 246–264.CrossRefGoogle ScholarPubMed
Flanagan, D.P., Alfonso, V.C., & Mascolo, J.T. (2011). A CHC-based operational definition of SLD. In Flanagan, D.P. & Alfonso, V.C. (Eds.), Essentials of specific learning disability assessment (pp. 233–298). Hoboken, NJ: Wiley.Google Scholar
Flanagan, D.P., Ortiz, S.O., & Alfonso, V.C. (2013). Essentials of cross-battery assessment (3rd ed.). Hoboken, NJ: Wiley.Google Scholar
Flanagan, D.P., Ortiz, S.O., Alfonso, V.C., & Mascolo, J.T. (2006). The achievement test desk reference: A guide to learning disability identification (2nd ed.). Hoboken, NJ: Wiley.Google Scholar
Fletcher, J.M., Taylor, H.G., Levin, H.S., & Satz, P. (1995). Neuropsychological and intellectual assessment of children. In Kaplan, H. & Saddock, B. (Eds.), Comprehensive textbook of psychiatry (6th ed., pp. 581–601). Baltimore, MD: Basic Books, Williams, & Wilkens.Google Scholar
Floyd, R.G., Evans, J.J., & McGrew, K.S. (2003). Relations between measures of Cattell-Horn-Carroll (CHC) cognitive abilities and mathematics achievement across the school-age years. Psychology in the Schools, 40, 155–171.Google Scholar
Floyd, R.G., McGrew, K.S., & Evans, J.J. (2008). The relative contributions of the Cattell-Horn-Carroll cognitive abilities in explaining writing achievement during childhood and adolescence. Psychology in the Schools, 45, 132–144. doi:10.1002/pits.20284CrossRefGoogle Scholar
Fry, A.F., & Hale, S. (1996). Processing speed, working memory, and fluid intelligence: Evidence for a developmental cascade. Psychological Science, 7, 237–241.Google Scholar
Fuchs, D., & Young, C.L. (2006). On the irrelevance of intelligence in predicting responsiveness to reading instruction. Exceptional Children, 73, 8–30.Google Scholar
Garrett, Z., Law, J., & Nye, C. (2004). The efficacy of treatment for children with developmental speech and language delay/disorder: A meta-analysis. Journal of Speech, Language, and Hearing Research, 47, 924–943.Google Scholar
Gathercole, S.E., Brown, L., & Pickering, S.J. (2003). Working memory assessments at school entry as longitudinal predictors of National Curriculum attainment levels. Educational and Child Psychology, 20, 109–122.Google Scholar
Geary, D.C. (1993). Mathematical disabilities: Cognitive, neuropsychological, and genetic components. Psychological Bulletin, 114, 345–362.Google Scholar
Geary, D.C., Hoard, M.K., & Bailey, D.H. (2011). How SLD manifests in mathematics. In Flanagan, D.P. & Alfonso, V.C. (Eds.), Essentials of specific learning disability identification (pp. 43–64). Hoboken, NJ: Wiley.Google Scholar
Gill, C.B., Klecan-Aker, J., Roberts, T., & Fredenburg, K.A. (2003). Following directions: Rehearsal and visualization strategies for children with specific language impairment. Child Language Teaching & Therapy, 19, 85–104.Google Scholar
Gillon, G.T. (2004). Phonological awareness. New York: Guilford.Google Scholar
Gioia, G.A., Isquith, P.K., Guy, S.C., & Kenworthy, L. (2000). Behavior Rating Inventory of Executive Function. Lutz, FL: Psychological Assessment Resources.Google Scholar
Glutting, J.J., McDermott, P.A., & Konold, T.R. (1997). Ontology, structure, and diagnostic benefits of a normative subtest taxonomy from the WISC-III standardization sample. In Flanagan, D.P., Genshaft, J.L., & Harrison, P.L. (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (pp. 340–372). New York: Guilford Press.Google Scholar
Gomez, R., & Condon, M. (1999). Central auditory processing ability in children with ADHD with and without learning disabilities. Journal of Learning Disabilities, 32, 150–158.Google Scholar
Graham, S., & Harris, K.R. (1989). Component analysis of cognitive strategy instruction: Effects on learning disabled students’ compositions and self-efficacy. Journal of Educational Psychology, 81, 353–361.Google Scholar
Green, C.S., & Bavelier, D. (2008). Exercising your brain: A review of human brain plasticity and training-induced learning. Psychology and Aging, 23, 692–701.Google Scholar
Hale, J., Alfonso, V., Berninger, V., Bracken, B., Christo, C., Clark, E., . . . Schultz, E.K. (2010). Critical issues in response-to-intervention, comprehensive evaluation, and specific learning disabilities identification and intervention: A white paper consensus. Learning Disability Quarterly, 33, 223–236.Google Scholar
Hale, J.B., & Fiorello, C.A. (2004). School neuropsychology: A practitioner's handbook. New York: Guilford Press.Google Scholar
Hale, J.B., Wycoff, K.L., & Fiorello, C.A. (2011). RTI and cognitive hypothesis testing for identification and intervention of specific learning disabilities: The best of both worlds. In Flanagan, D.P. & Alfonso, V.C. (Eds.), Essentials of specific learning disability assessment (pp. 173–202). Hoboken, NJ: Wiley.Google Scholar
Harris, K.R., Friedlander, B.D., Saddler, B., Frizzelle, R., & Graham, S. (2005). Self-monitoring of attention versus self-monitoring of academic performance: Effects among students with ADHD in the general education classroom. The Journal of Special Education, 39, 145–156.Google Scholar
Hooper, S.R., Costa, L-J., & McBee, M. (2011). Concurrent and neuropsychological contributors to written language expression in first and second grade students. Reading and Writing: An Interdisciplinary Journal, 24, 221–152.Google Scholar
Jaeggi, S.M., Buschkuehl, M., Jonides, J., & Perrig, W.J. (2008). Improved fluid intelligence with training on working memory. Proceedings of the National Academy of Sciences of the United States of America, 105, 6829–6833.Google Scholar
Kane, M.J., & Engle, R.W. (2002). The role of prefrontal cortex in working-memory capacity, executive attention, and general fluid intelligence: An individual-differences perspective. Psychonomic Bulletin and Review, 9, 637–671.Google Scholar
Kaplan, E., Fein, D., Morris, R., & Delis, D.C. (1991). WAIS-R as a neuropsychological instrument. San Antonio, TX: The Psychological Corporation.Google Scholar
Kar, B. C., Dash, U. N., Das, J. P., & Carlson, J. (1993). Two experiments on the dynamic assessment of planning. Learning and Individual Differences, 5, 13–29.Google Scholar
Kaufman, A.S. (1994). Intelligent testing with the WISC-III. New York: Wiley.Google Scholar
Kaufman, A.S., & Kaufman, N.L. (2004). Kaufman Assessment Battery for Children, second edition. Circle Pines, MN: AGS Publishing.Google Scholar
Kavale, K.A., & Forness, S.R. (2000). What definitions of learning disability say and don't say: A critical analysis. Journal of Learning Disabilities, 33, 239–256.Google Scholar
Klauer, K.J., & Phye, G.D. (2008). Inductive reasoning: A training approach. Review of Educational Research, 78, 85–123.Google Scholar
Korkman, M., Kirk, U., & Kemp, S. (2007). NEPSY-II: A Developmental Neuropsychological Assessment. San Antonio, TX: The Psychological Corporation.Google Scholar
Kovaleski, J.F., VanDerHeyden, A.M., & Shapiro, E.S. (2013). The RTI approach to evaluating learning disabilities. New York: Guilford.Google Scholar
Kramer, J.H., Knee, K., & Delis, D.C. (2000). Verbal memory impairments in dyslexia. Archives of Clinical Neuropsychology, 15, 83–93.Google Scholar
Kroesbergen, E.H., Van Luit, J.E., & Naglieri, J.A. (2003). Mathematical learning disabilities and PASS cognitive processes. Journal of Learning Disabilities, 36, 574–582.Google Scholar
Lawson, M.J., & Rice, D.N. (1989). Effects of training in use of executive strategies on a verbal memory problem resulting from a closed head injury. Journal of Clinical and Experimental Neuropsychology, 11, 842–854.Google Scholar
Levin, J.R. (1993). Mnemonic strategies and classroom learning: A twenty-year report card. The Elementary School Journal, 94, 235–244.Google Scholar
Lezak, M.D., Howieson, D.B., & Loring, D.W. (2004). Neuropsychological assessment (4th ed.). New York: Oxford University Press.Google Scholar
Loarer, E. (2003). Cognitive training for individuals with deficits. In Sternberg, R.J., Lautrey, J., & Lubart, T.I. (Eds.), Models of intelligence: International perspectives (pp. 243–260). Washington, DC: American Psychological Association.Google Scholar
Luria, A.R. (1970). The functional organization of the brain. Scientific American, 222, 66–78.Google Scholar
McCloskey, G., & Perkins, L.A. (2013). Essentials of executive functions assessment. Hoboken, NJ: Wiley.Google Scholar
McCloskey, G., Perkins, L.A., & Van Divner, B. (2009). Assessment and intervention for executive function difficulties. New York: Taylor and Francis.Google Scholar
McGrew, K.S., & Wendling, B.J. (2010). Cattell-Horn-Carroll cognitive-achievement relations: What we have learned from the past 20 years of research. Psychology in the Schools, 47, 651–675.Google Scholar
McGrew, K.S., & Woodcock, R.W. (2001). Technical manual. Woodcock-Johnson III. Itasca, IL: Riverside Publishing.Google Scholar
Mackey, A.P., Hill, S.S., Stone, S.I., & Bunge, S.A. (2011). Differential effects of reasoning and speed training in children. Developmental Science, 14, 582–590.Google Scholar
McNamara, D.S., & Scott, J.L. (2001). Working memory capacity and strategy use. Memory & Cognition, 29, 10–17.Google Scholar
Mastropieri, M.A., & Scruggs, T.E. (1991). Teaching students ways to remember: Strategies for learning mnemonically. Cambridge, MA: Brookline Books.Google Scholar
Milberg, W.P., Hebben, N.A., & Kaplan, E. (2009). The Boston process approach to neuropsychological assessment. In Grant, I. & Adams, K. (Eds.), Neuropsychological assessment of neuropsychiatric disorders (3rd ed., pp. 65–86). New York: Oxford University Press.Google Scholar
Miller, D.C. (Ed.). (2010). Best practices in school neuropsychology: Guidelines for effective practice, assessment, and evidence-based intervention. Hoboken, NJ: Wiley.Google Scholar
Miller, D.C. (2013). Essentials of school neuropsychological assessment (2nd ed.). Hoboken, NJ: Wiley.Google Scholar
Morrison, A.B., & Chein, J.M. (2011). Does working memory training work? The promise and challenges of enhancing cognition by training working memory. Psychonomic Bulletin Review, 18, 46–60.Google Scholar
Naglieri, J.A. (1999). Essentials of CAS assessment. Hoboken, NJ: Wiley.Google Scholar
Naglieri, J.A. (2005). The Cognitive Assessment System. In Flanagan, D.P. & Harrison, P.L. (Eds.), Contemporary intellectual assessment (2nd ed., pp. 441–460). New York: Guilford.Google Scholar
Naglieri, J.A. (2011). The discrepancy/consistency approach to SLD identification using the PASS theory. In Flanagan, D.P. & Alfonso, V.C. (Eds.), Essentials of specific learning disability assessment (pp. 145–172). Hoboken, NJ: Wiley.Google Scholar
Naglieri, J.A., & Gottling, S.H. (1997). Mathematics instruction and PASS cognitive processes: An intervention study. Journal of Learning Disabilities, 30, 513–520.Google Scholar
Naglieri, J.A., & Johnson, D. (2000). Effectiveness of a cognitive strategy intervention to improve math calculation based on the PASS theory. Journal of Learning Disabilities, 33, 591–597.Google Scholar
National Reading Panel. (2000). Teaching children to read: An evidence-based assessment of the scientific research literature on reading and its applications for reading instruction. Washington, DC: National Institute of Child Health and Human Development (NICHD).Google Scholar
Rabiner, D.L., Murray, D.W., & Schmid, L. (2004). An exploration of the relationship between ethnicity, attention problems, and academic achievement. School Psychology Review, 33, 498–509.Google Scholar
Reid, R., Schartz, M., & Trout, A.L. (2005). Self-regulation interventions for children with attention deficit/hyperactivity disorder. Exceptional Children, 71, 361–377.Google Scholar
Reynolds, C.R. (2007). RTI, neuroscience, and sense: Chaos in the diagnosis and treatment of learning disabilities. In Fletcher-Janzen, E. & Reynolds, C.R. (Eds.), Neuropsychological perspectives on learning disabilities in the era of RTI (pp. 14–27). Hoboken, NJ: Wiley.Google Scholar
Reynolds, C.R., & Fletcher-Janzen, E. (Eds.). (1997). Handbook of clinical child neuropsychology (2nd ed.). New York: Plenum Press.Google Scholar
Sattler, J.M. (2001). Assessment of children: Cognitive applications (4th ed.). La Mesa, CA: Author.Google Scholar
Schneider, J.W., & McGrew, K.S. (2012). The Cattell-Horn-Carroll (CHC) model of intelligence. In Flanagan, D.P. & Harrison, P.L. (Eds.), Contemporary intellectual assessment (3rd ed.). New York: Guilford.Google Scholar
Shalev, L., Tsal, Y., & Mevorach, C. (2007). Computerized progressive attentional training (CPAT) program: Effective direct intervention for children with ADHD. Child Neuropsychology, 13, 382–388.Google Scholar
Singer, B.D., & Bashir, A.S. (1999). What are executive functions and self-regulation and what do they have to do with language-learning disorders? Language, Speech, and Hearing Services in Schools, 30, 265–273.Google Scholar
Sotelo-Dynega, M., Flanagan, D.P, & Alfonso, V.C. (2011). Overview of specific learning disabilities. In Flanagan, D.P. & Alfonso, V.C. (Eds.), Essentials of specific learning disability assessment (pp. 1–19). Hoboken, NJ: Wiley.Google Scholar
Swanson, H.L. (2000). Are working memory deficits in readers with learning disabilities hard to change? Journal of Learning Disabilities, 33, 551–566.Google Scholar
Swanson, H.L., & Berninger, V.W. (1995). The role of working memory in skilled and less skilled readers’ comprehension. Intelligence, 21, 83–108.Google Scholar
Swanson, H.L., Hoskyn, M., & Lee, C. (1999). Interventions for students with learning disabilities: A meta-analysis of treatment outcomes. New York: Guilford Press.Google Scholar
Swanson, H.L., Howard, C.B., & Saez, L. (2006). Do different components of working memory underlie different subgroups of reading disabilities? Journal of Learning Disabilities, 39, 252–269.Google Scholar
Swanson, H.L., & Jerman, O. (2006). Math disabilities: A selective meta-analysis of the literature. Review of Educational Research, 76, 249–274.Google Scholar
Tageuchi, H., Sekiguchi, A., Taki, Y., Yokoyama, S., Yomogida, Y., Komuro, N., . . . Kawashima, R. (2010). Training of working memory impacts structural connectivity. The Journal of Neuroscience, 30, 3297–3303.Google Scholar
Tallal, P., Miller, S.L., Bedi, G., Byma, G., Wang, X., Nagarajam, S., . . . Merzenich, M.M. (1996). Language comprehension in language-learning impaired children improved in acoustically modified speech. Science, 271, 81–84.Google Scholar
Tamm, L., Hughes, C., Ames, L., Pickering, J., Silver, C.H., Stavinoha, P., . . . Emslie, G. (2010). Attention training for school-aged children with ADHD: Results of an open trial. Journal of Attention Disorders, 14, 86–94.Google Scholar
VanDerHeyden, A.M., & Burns, M.K. (2010). Essentials of response to intervention. Hoboken, NJ: Wiley.Google Scholar
Wiig, E.H. (2011). How SLD manifests in oral expression and listening comprehension. In Flanagan, D.P. & Alfonso, V.C. (Eds.), Essentials of specific learning disability assessment (pp. 89–113). Hoboken, NJ: Wiley.Google Scholar
Woodcock, R.W., McGrew, K.S., & Mather, N. (2001). Woodcock-Johnson III Tests of Cognitive Abilities. Itasca, IL: Riverside Publishing.Google Scholar
Ysseldyke, J.E. (2005). Assessment and decision making for students with learning disabilities: What if this is as good as it gets? Learning Disability Quarterly, 28, 125–128.Google Scholar