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IDEIA, SLD, RTI, and Cognitive Assessment

IDEIA, SLD, RTI, and Cognitive Assessment. Jack A. Naglieri, Ph.D. Professor of Psychology Center for Cognitive Development School Psychology Program Director George Mason University Fairfax, VA 22030 http://ccd.gmu.edu naglieri@gmu.edu. IDEA Reauthorization. Topical outline

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IDEIA, SLD, RTI, and Cognitive Assessment

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  1. IDEIA, SLD, RTI, and Cognitive Assessment Jack A. Naglieri, Ph.D. Professor of Psychology Center for Cognitive Development School Psychology Program Director George Mason University Fairfax, VA 22030 http://ccd.gmu.edu naglieri@gmu.edu

  2. IDEA Reauthorization • Topical outline • IDEIA and forthcoming regulations • A look at the Law • Response to intervention • Local comparison groups • Measurement of improvement • Research and reviews • A cognitive approach to assessment • Connecting LD definition with assessment of “basic psychological processes” Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  3. IDEA Reauthorization • Topical outline • IDEIA and forthcoming regulations • A look at the Law • Response to intervention • Local comparison groups • Measurement of improvement • Research and reviews • A cognitive approach to assessment • Connecting LD definition with assessment of “basic psychological processes” Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  4. IDEIA 2004 Law Individuals with Disabilities Education Improvement Act of 2004 Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  5. IDEA Reauthorization The IDEIA and the No Child Left Behind Act have encouraged a reexamination of how school psychologists function There have been many meetings of researchers, practitioners, and professional organizations and articles written which discuss how to improve the system, especially for LD diagnosis Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  6. IDEA Reauthorization • Reexamination of • the role of the school psychologists is good for the evolution of the field • how to improve diagnosis of Specific Learning Disabilities (SLD) is particularly important • how to reduce over-representation of minority children in special education is also needed Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  7. IDEIA What are some of the details of the new Law?

  8. IQ achievement discrepancy no longer required IDEIA 2004 Law RTI may be used AS A PART of the evaluation… but not as sole method Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  9. IDEIA 2004 Law “use a variety of assessment tools” “not use any single procedure” “assess cognitive factors” Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  10. IDEIA 2004 Law non discriminatory assessments valid and reliable assessment Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  11. IDEIA Law Summary • Ability achievement discrepancy is no longer required (not disallowed) • A variety of assessment tools required • The use of any single measure or assessment as the sole criterion for determining SLD is not permitted • Assessments must not be discriminatory on racial or cultural basis • Definition of SLD remains Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  12. Definition of SLD remains the same IDEIA 2004 Law Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  13. SLD Definition in Both Bills • The definition of SLD has not changed • “The term ‘specific learning disability’ means a disorder in one or more of thebasic psychological processes involved in understanding or in using language, spoken or written, which disorder may manifest itself in the imperfect ability to listen, think, speak, read, write, spell, or do mathematical calculations.” Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  14. Reactions to IDEIA Anticipation of the Regulations that follow…

  15. Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  16. Align the definition of SLD with the classification criteria Replace discrepancy with pattern of strengths and weaknesses and cognitive abilities impacting achievement Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  17. Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  18. SLD & Cognitive Processing Connecting the dots

  19. Hale, Naglieri, Kaufman, & Kavale (2004) Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  20. Hale, Naglieri, Kaufman, & Kavale (2004) • The definition of SLD is • “… a disorder in 1 or more of the basic psychological processes involved in understanding or in using language, spoken or written, which disorder may manifest itself in the imperfect ability to listen, think, speak, read, write, spell, or do mathematical calculations.” • Neither the discrepancy model or RTI evaluates basic psychology processes Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  21. Hale, Naglieri, Kaufman, & Kavale (2004) • The method of RTI is disconnected from the definition of SLD • “Establishing a disorder in the basic psychology processes is essential for determining SLD” • Practitioners have ignored this approach because of limited availability of good measures of processing • Times have changed Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  22. Hale, Naglieri, Kaufman, & Kavale (2004) • Processing measures of today are very different than those of the 1970s • Tests that we specifically developed to measure basic psychological processes should be used • Kaufman Assessment Battery for Children 2nd Edition • Cognitive Assessment System Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  23. Hale, Naglieri, Kaufman, & Kavale (2004) • Defining intelligence as processing • leads to smaller race and ethnic differences than traditional IQ tests • Yields excellent prediction to achievement • Provides sensitivity to the cognitive disorders seen in many exceptional children • Has demonstrated relationships to intervention Naglieri, J. A. (2003). Current advances in assessment and intervention for children with learning disabilities. In T. E. Scruggs and M. A. Mastropieri (Eds.) Advances in learning and behavioral disabilities Volume 16: Identification and assessment (pp. 163-190). New York: JAI. Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  24. What is Next? • Current status as of March 2005 • Regulations which are interpretations of the law are being written • Input on the regulations was due by Feb 28, 2005 • We need to learn about the strengths and weakness of the options • RTI – which may be included • Assessment of basic psychological processes – which needs to be assessed Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  25. IDEA Reauthorization • Topical outline • IDEIA and forthcoming regulations • A look at the Law • Response to intervention • Local comparison groups • Measurement of improvement • Research and reviews • A cognitive approach to assessment • Connecting LD definition with assessment of “basic psychological processes” Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  26. Alternatives to ability achievement discrepancy Response to Intervention

  27. IDEA Reauthorization • Topical outline • IDEA reauthorization • The problem of LD identification • Response to intervention • Local comparison groups • Measurement of improvement • A cognitive approach to assessment Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  28. Response to Intervention and SLD A summary of the method and researchers’ response to RTI

  29. Kovaleski & Prasse (2004) • The dual discrepancy format for SLD identification • Part 1: Low academic performance • Part 2: Poor response to appropriate instruction Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  30. Kovaleski & Prasse (2004) Part 1 • Low academic performance • The student must be significantly below same-grade peers • Shinn (2002) notes that a 2.0 grade level discrepancy is a typical index that identifies a significant academic deficiency • This is based on a discrepancy from grade-level performance without reference to an assessment of the student’s ability level (i.e., IQ) Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  31. Assessing Academic Performance • Low academic performance (continued) • BUT… Shinn’s 2.0 grade level discrepancy is also a “wait to fail ”model because you can’t be behind by two years until you are in at least second grade • BUT…The grade equivalent method has many well known psychometric problems • AND…differences in curriculum can influence who is behind Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  32. Kovaleski & Prasse (2004) Part 1 • Low academic performance (continued) • Advocates argue for RTI as a curriculum-based measurement (CBM) approach • Reading fluency is overemphasized • The student’s discrepancy is determined in relation to classmates by comparing the performance on CBM measures with norms from the student’s school or school district Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  33. Assessing Academic Performance • Local Norms • Advantage • Local norms are good at telling where the child is in relation to the smallest comparison group – the child’s classroom • Disadvantage • Local norms only tell where the child is in relation to the smallest comparison group – the child’s classroom • Change the classroom and the score changes • Change the school and the score changes Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  34. The Problem with Local Norms Fairfax County Schools

  35. Fairfax County Elementary • Reading scores were obtained for all 69 elementary schools in Fairfax County Public Schools • The schools were ranked on reading scores • The 10th, 35th, and 59th ranked schools were selected • School based standard scores were computed • Reading score – standard score (mean 100, SD of 15) were computed and compared across schools Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  36. The same Reading score of 55 yields a standard score of 112 (above average) for a child in Herndon Elementary School but a score of 92 (average) in Columbia Elementary School and a score of 84 (well below average) in Flint Hill Elementary School. Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  37. Local Norms for Inner City Schools Scores based on a national norm group indicate these children are low Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  38. Local Norms for Inner City Schools Standard scores based on local mean falsely describe half the children with national scores below 85 as OK Standard scores based on a national norm group indicate these children are low Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  39. Local Norms • How effective is a local norm? • It calibrates a child based on a comparison to the classroom, school, or school district • Is it consistent across classrooms? • By definition – NO • Is it consistent across schools? • By definition – NO • Is it consistent across districts? • By definition – NO • Local norms provide an inconsistent unit of measurement Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  40. Fairfax County Elementary • Conclusions on Local Norms • Local norms are useful to determine how the child compares to the rest of the class and for instructional planning • A wide variety can exist between schools in the same school district • A child may be “failing” in one class but doing “well” in another • Determining SLD on local norms will yield considerable inequities especially for minority groups Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  41. Kovaleski & Prasse (2004) Part 2 • Poor response to appropriate instruction • The student performs poorly to carefully planned and precisely delivered instruction • The data are developed through ongoing progress monitoring on a critical academic measure during the course of an individually designed intervention • The use of CBM as an ongoing performance measure (usually through data collected twice per week) is recommended Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  42. Does an increase in counts mean improvement is real? Good news can be relative

  43. Rates of Improvement An Achievement Example

  44. Rates of Improvement • Vocabulary Growth • Meaning vocabulary growth average increase is 2,500 words per year (McCormick, 1998) • A child needs to learn about 2,500 words per year to keep up with peers • But a child can learn more words every year and still fall behind Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  45. Rates of Improvement-Vocabulary Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  46. 50% increase in number of words per year expressed as standard scores in relation to normal growth rate Improvement or Deterioration? 50% increase in number of words learned per year Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  47. Rates of Improvement • Visual examination of changes in rate are only sufficient to demonstrate change from baseline • Changes over time are helpful for instructional decisions • Aim lines based on local norms are misleading Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  48. Conclusions Regarding Kovaleski & Prasse (2004) The dual discrepancy format: Low academic performance and Poor response to instruction

  49. Conclusions on Dual Discrepancy • Changes over time do not necessarily mean the child has reached a level that is consistent with normative expectations • Competency levels can be set so low, and “improvement” defined by such small steps, that apparent improvement may be better described as showing Illusory Validity Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

  50. Conclusions on Dual Discrepancy • RTI may be a reasonable way to find children who are doing poorly in class • RTI problems • Local norms do not provide consistency • Increases in performance can be misleading Jack A. Naglieri, Ph.D. George Mason Univ, Fairfax, VA 22030. naglieri@gmu.edu

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