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35 - Assessment in Educational Settings

from Part IV - Clinical Assessment in Specific Settings

Published online by Cambridge University Press:  06 December 2019

By
Benjamin J. Lovett  and
Jason M. Nelson
Edited by
Martin Sellbom  and
Julie A. Suhr
Martin Sellbom
Affiliation:
University of Otago, New Zealand
Julie A. Suhr
Affiliation:
Ohio University
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Summary

Many clinical psychologists either work with children who may be eligible for educational accommodations and special education or else work with adults who have received such services. This chapter provides an overview of assessment issues in educational settings, with a focus on K-12 schooling. We review the legal framework for special education assessment, before considering two controversial issues that interact with that framework: multitiered systems of support that delay comprehensive assessments and the question of whether students with ethnic minority backgrounds are overidentified as having disabilities. We then turn to the assessment of learning disabilities, the largest special education category; we review and evaluate major approaches to learning disability identification. Our next topic is the use of assessment data to determine which students need accommodations on classroom and high-stakes tests. Finally, we discuss an emerging issue: the measurement of effort and motivation that students exhibit during testing in educational settings.

Keywords

testing accommodationslearning disabilitieseducational assessmentspecial educationdisproportionality
Type
Chapter
Information
The Cambridge Handbook of Clinical Assessment and Diagnosis , pp. 485 - 497
Publisher: Cambridge University Press
Print publication year: 2019

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References

Aaron, P. G. (1997). The impending demise of the discrepancy formula. Review of Educational Research, 67(4), 461–502.Google Scholar
Adelman, H. S., Lauber, B. A., Nelson, P., & Smith, D. C. (1989). Toward a procedure for minimizing and detecting false positive diagnoses of learning disability. Journal of Learning Disabilities, 22(4), 234–244.Google Scholar
AERA (American Educational Research Association), APA (American Psychological Association), & NCME (National Council on Measurement in Education). (2014). Standards for educational and psychological testing. Washington, DC: American Educational Research Association.Google Scholar
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.Google Scholar
Ardoin, S. P., & Christ, T. J. (2009). Curriculum-based measurement of oral reading: Standard errors associated with progress monitoring outcomes from DIBELS, AIMSweb, and an experimental passage set. School Psychology Review, 38(2), 266–284.Google Scholar
Barth, A. E., Stuebing, K. K., Anthony, J. L., Denton, C. A., Mathes, P. G., Fletcher, J. M., & Francis, D. J. (2008). Agreement among response to intervention criteria for identifying responder status. Learning and Individual Differences, 18(3), 296–307.Google Scholar
Bateman, B. D. (1965). An educator’s view of a diagnostic approach to learning disorders. In Hellmuth, J. (Ed.), Learning disorders (pp. 219–239). Seattle, WA: 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 Lyon, G. R. (Ed.), Frames of reference for the assessment of learning disabilities (pp. 163–183). Baltimore, MD: Brookes.Google Scholar
Blanchett, W. J. (2006). Disproportionate representation of African American students in special education: Acknowledging the role of white privilege and racism. Educational Researcher, 35(6), 24–28.Google Scholar
Brooks, B. L. (2011). A study of low scores in Canadian children and adolescents on the Wechsler Intelligence Scale for Children, (WISC-IV). Child Neuropsychology, 17(3), 281–289.Google Scholar
Burns, M. K. (2007). RTI will fail, unless … NASP Communiqué, 35(5), 38–40.Google Scholar
Burns, M. K., Jimerson, S. R., VanDerHeyden, A. M., & Deno, S. L. (2016). Toward a unified response-to-intervention model: Multi-tiered systems of support. In Jimerson, S. R., Burns, M. K., & VanDerHeyden, A. M. (Eds.), Handbook of response to intervention (2nd ed., pp. 719–732). New York: Springer.CrossRefGoogle Scholar
Carone, D. A. (2015). Clinical strategies to assess the credibility of presentations in children. In Kirkwood, M. W. (Ed.), Validity testing in child and adolescent assessment: Evaluating exaggeration, feigning, and noncredible effort (pp. 107–124). New York: Guilford.Google Scholar
Chafetz, M., & Prentkowski, E. (2011). A case of malingering by proxy in a Social Security Disability psychological consultative examination. Applied Neuropsychology, 18, 143–149. doi:10.1080/09084282.2011.570619Google Scholar
DeRight, J., & Carone, D. A. (2015). Assessment of effort in children: A systematic review. Child Neuropsychology, 21(1), 1–24. doi:10.1080/09297049.2013.864383Google Scholar
Dombrowski, S. C., Kamphaus, R. W., & Reynolds, C. R. (2004). After the demise of the discrepancy. Professional Psychology: Research and Practice, 35(4), 364–372.Google Scholar
Duckworth, A. L., Quinn, P. D., Lynam, D. R., Loeber, R., Stouthamer-Loeber, M., & Smith, E. E. (2011). Role of test motivation in intelligence testing. Proceedings of the National Academy of Sciences of the United States of America, 108(19), 7716–7720. doi:10.1073/pnas.10118601108/-/DCSupplementalGoogle Scholar
Eckert, T. L., & Lovett, B. J. (2013). Principles of behavioral assessment. In Saklofske, D. H., Reynolds, C. R., & Schwean, V. L. (Eds.), Oxford Handbook of Child Psychological Assessment (pp. 366–384). New York: Oxford University Press.Google Scholar
Flanagan, D. P., Alfonso, V. C., & Mascolo, J. T. (2011). A CHC-based operational definition of SLD: Integrating multiple data sources and multiple data-gathering methods. In Flanagan, D. P. & Alfonso, V. C. (Eds.), Essentials of specific learning disability identification (pp. 233–298). Hoboken, NJ: Wiley.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(6), 545–552.Google Scholar
Fletcher-Janzen, E., & Reynolds, C. R. (Eds.). (2008). Neuropsychological perspectives on learning disabilities in the era of RTI: Recommendations for diagnosis and intervention. Hoboken, NJ: Wiley.Google Scholar
Frazier, T. W., Frazier, A. R., Busch, R. M., Kerwood, M. A., & Demaree, H. A. (2008). Detection of simulated ADHD and reading disorder using symptom validity measures. Archives of Clinical Neuropsychology, 23, 501–509. doi:10.1016/j.acn.2008.04.001Google Scholar
Fuchs, D., Fuchs, L. S., & Stecker, P. M. (2010). The “blurring” of special education in a new continuum of general education placements and services. Exceptional Children, 76(3), 301–323.Google Scholar
Gersten, R., Jayanthi, M., & Dimino, J. (2017). Too much, too soon? Unanswered questions from national Response to Intervention evaluation. Exceptional Children, 83(3), 244–254.Google Scholar
Green, P. (2003). Word Memory Test. Edmonton: Green’s Publishing.Google Scholar
Green, P. (2009). The Advanced Interpretation Program. Edmonton: Green’s Publishing.Google Scholar
Green, P., & Flaro, L. (2003). Word Memory Test performance in children. Child Neuropsychology, 9(3), 189–207. doi:10.1076/chin.9.3.189.16460CrossRefGoogle ScholarPubMed
Gresham, F. M. (2002). Responsiveness to intervention: An alternative approach to the identification of learning disabilities. In Bradley, R., Danielson, L., & Hallahan, D. P. (Eds.), Identification of learning disabilities: Research to practice (pp. 467–519). Mahwah, NJ: Erlbaum.Google Scholar
Guilmette, T. J. (2013). The role of clinical judgment in symptom validity assessment. In Carone, D. & Bush, S. (Eds.), Mild traumatic brain injury: Symptom validity assessment and malingering (pp. 31–45). New York: Springer.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 identification (pp. 173–202). Hoboken, NJ: Wiley.Google Scholar
Harrison, A. G., & Armstrong, I. (2014). WISC-IV unusual digit span performance in a sample of adolescents with learning disabilities. Applied Neuropsychology: Child, 3(2), 152–160. doi:10.1080/21622965.2012.753570Google Scholar
Harrison, A. G., & Edwards, M. J. (2010). Symptom exaggeration in post-secondary students: Preliminary base rates in a Canadian sample. Applied Neuropsychology, 17, 135–143. doi:10.1080/09084281003715642Google Scholar
Harrison, A. G., Edwards, M. J., Armstrong, I., & Parker, K. C. H. (2010) An investigation of methods to detect feigned reading disabilities. Archives of Clinical Neuropsychology, 25, 89–98. doi:10.1093/arclin/acp104Google Scholar
Harrison, A. G., Edwards, M. J., & Parker, K. C. H. (2008). Identifying students feigning dyslexia: Preliminary findings and strategies for detection. Dyslexia, 14, 228–246. doi:10.1002/dys.366Google Scholar
Harrison, A. G., Green, P., & Flaro, L. (2012). The importance of symptom validity testing in adolescents and young adults undergoing assessments for learning or attention difficulties. Canadian Journal of School Psychology, 27(1), 98–112. doi:10.1177/0829573512437024Google Scholar
Heward, W. L. (2013). Exceptional children (10th ed.). Boston: Pearson.Google Scholar
Hunt, E. (2011). Human intelligence. New York: Cambridge University Press.Google Scholar
Infante-Green, A. (2016). Changes in allowable testing accommodations on the Grades 3–8 New York State English Language Arts Assessments. www.p12.nysed.gov/specialed/publications/testing-accommodations-ela-grades-3–8.htmGoogle Scholar
Kirk, S. A. (1962). Educating exceptional children. Boston: Houghton Mifflin.Google Scholar
Kirkwood, M. W. (2015). Review of pediatric performance and symptoms validity tests. In Kirkwood, M. W. (Ed.), Validity testing in child and adolescent assessment: Evaluating exaggeration, feigning, and noncredible effort (pp. 79–106) New York: Guilford.Google Scholar
Kirkwood, M. W., Kirk, J. W., Blaha, R. Z., & Wilson, P. (2010). Noncredible effort during pediatric neuropsychological evaluations: A case series and literature review. Child Neuropsychology, 16, 604–618. doi:10.1080/09297049.2010.495059Google Scholar
Kovaleski, J. F., VanDerHeyden, A. M., & Shapiro, E. S. (2013). The RTI approach to evaluating learning disabilities. New York: Guilford.Google Scholar
Larochette, A., & Harrison, A. G. (2012). Word Memory Test performance in Canadian adolescents with learning disabilities: A preliminary study. Applied Neuropsychology: Child, 1, 38–47. doi:10.1080/21622965.2012.665777Google Scholar
Lewandowski, L., Gathje, R. A., Lovett, B. J., & Gordon, M. (2013). Test-taking skills in college students with and without ADHD. Journal of Psychoeducational Assessment, 31(1), 41–52.Google Scholar
Lindstrom, W. A., Lindstrom, J. H., Coleman, C., Nelson, J., & Gregg, N. (2009). The diagnostic accuracy of symptom validity tests when used with postsecondary students with learning disabilities: A preliminary investigation. Archives of Clinical Neuropsychology, 24, 659–669. doi:10.1093/arclin/acp071Google Scholar
Lovett, B. J., & Kilpatrick, D. A. (2018). Differential diagnosis of SLD versus other difficulties. In Flanagan, D. P. & Alfonso, V. C. (Eds.), Essentials of specific learning disability assessment (2nd ed., pp. 549–571). Hoboken, NJ: Wiley.Google Scholar
Lovett, B. J., & Lewandowski, L. J. (2006). Gifted students with learning disabilities: Who are they? Journal of Learning Disabilities, 39(6), 515–527.Google Scholar
Lovett, B. J., & Lewandowski, L. J. (2015). Testing accommodations for students with disabilities: Research-based practice. Washington, DC: American Psychological Association.Google Scholar
Maki, K. E., Floyd, R. G., & Roberson, T. (2015). State learning disability eligibility criteria: A comprehensive review. School Psychology Quarterly, 30(4), 457–469. doi:10.1037/spq0000109Google Scholar
Martin, P. K., Schroeder, R. W., & Odland, A. P. (2015). Neuropsychologists’ validity testing beliefs and practices: A survey of North American professionals. The Clinical Neuropsychologist, 29(6), 741–776. doi:10.1080/13854046.2015.1087597Google Scholar
McGill, R. J., Styck, K. M., Palomares, R. S., & Hass, M. R. (2016). Critical issues in specific learning disability identification: What we need to know about the PSW model. Learning Disability Quarterly, 39(3), 159–170.Google Scholar
Miciak, J., Williams, J. L., Taylor, W. P., Cirino, P. T., Fletcher, J. M., & Vaughn, S. (2016). Do processing patterns of strengths and weaknesses predict differential treatment response? Journal of Educational Psychology, 108(6), 898–909.CrossRefGoogle ScholarPubMed
Morgan, P. L., Farkas, G., Hillemeier, M. M., & Maczuga, S. (2012). Are minority children disproportionately represented in early intervention and early childhood special education? Educational Researcher, 41(9), 339–351.Google Scholar
Morgan, P. L., Farkas, G., Hillemeier, M. M., Mattison, R., Maczuga, S., Li, H., & Cook, M. (2015). Minorities are disproportionately underrepresented in special education: Longitudinal evidence across five disability conditions. Educational Researcher, 44(5), 278–292.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 identification (pp. 145–172). Hoboken, NJ: Wiley.Google Scholar
Osmon, D. C., Plambeck, E., Klein, L., & Mano, Q. (2006). The Word Reading Test of effort in adult learning disability: A simulation study. The Clinical Neuropsycholgist, 20, 315–324. doi:10.1080/13854040590947434Google Scholar
Phillips, S. E. (1994). High-stakes testing accommodations: Validity versus disabled rights. Applied Measurement in Education, 7(2), 93–120.Google Scholar
Reschly, D. J., & Hosp, J. L. (2004). State SLD identification policies and practices. Learning Disability Quarterly, 27(4), 197–213.Google Scholar
Rutkowski, D., & Wild, J. (2015). Stakes matter: Student motivation and the validity of student assessments for teacher evaluation. Educational Assessment, 20(3), 165–179. doi:10.1080/10627197.2015.1059273Google Scholar
Scanlon, D. (2013). Specific learning disability and its newest definition: Which is comprehensive? And which is insufficient? Journal of Learning Disabilities, 46, 26–33.Google Scholar
Schneider, W.J. , & McGrew, K. S. (2012). The Cattell-Horn-Carroll model of intelligence. In Flanagan, D. & Harrison, P. (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (3rd ed., pp. 99–144). New York: Guilford.Google Scholar
Sherman, E. M. S. (2015). Terminology and diagnostic concepts. In Kirkwood, M. W. (Ed.), Validity testing in child and adolescent assessment: Evaluating exaggeration, feigning, and noncredible effort (pp. 22–41). New York: Guilford.Google Scholar
Skiba, R. J., Simmons, A. B., Ritter, S., Gibb, A. C., Rausch, M. K., Cuadrado, J., & Chung, C. G. (2008). Achieving equity in special education: History, status, and current challenges. Exceptional Children, 74(3), 264–288.Google Scholar
Slick, D., Hopp, G., Strauss, E., & Thompson, G. B. (1997). Victoria Symptom Validity Test. Odessa, FL: Psychological Assessment Resources.Google Scholar
Slick, D. J., Sherman, E. M. S., & Iverson, G. L. (1999). Diagnostic criteria for malingered neurocognitive dysfunction: Proposed standards for clinical practice and research. The Clinical Neuropsychologist, 13(4), 545–561. doi:10.1076/1385-4046(199911)13:041-Y;FT545Google 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(2), 103–106.Google Scholar
Steedle, J. T., & Grochowalkski, J. (2017). The effects of stakes on accountability test scores and pass rates. Educational Assessment, 22(2), 11–123. doi:10.1080/10627197.2017.1309276Google 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(1), 65–83.Google Scholar
Sullivan, A. L., & Bal, A. (2013). Disproportionality in special education: Effects of individual and school variables on disability risk. Exceptional Children, 79(4), 475–494.Google Scholar
Sullivan, B. K., May, K., & Galbally, L. (2007). Symptom exaggeration by college adults in attention-deficit hyperactivity and learning disorder assessments. Applied Neuropsychology, 14(3), 189–207. doi:10.1080/09084280701509083Google Scholar
Thurlow, M. L., Elliott, J. L., & Ysseldyke, J. E. (2003). Testing students with disabilities: Practical strategies for complying with district and state requirements. Thousand Oaks, CA: Corwin.Google Scholar
Tombaugh, T. N. (1996). Test of Memory Malingering. Toronto: Multi-Health Systems.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 of reading disability. Journal of Learning Disabilities, 33(3), 223–238.Google Scholar
Volpe, R. J., & Fabiano, G. A. (2013). Daily behavior report cards. New York: Guilford.Google Scholar
Walker, J. S. (2011). Malingering in children: Fibs and faking. Child and Adolescent Psychiatric Clinics of North America, 20, 547–556. doi:10.1016/j.chc.2011.03.13Google Scholar
Yell, M. L., Katsiyannis, A., & Collins, J. C. (2010). Compton Unified School District v. Starvenia Addison: Child find activities and response to intervention. Journal of Disability Policy Studies, 21(2), 67–69.Google Scholar
Ysseldyke, J. (2001). Reflections on a research career: Generalizations from 25 years of research on assessment and instructional decision making. Exceptional Children, 67(3), 295–309.Google Scholar

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