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LD in 2003: Revitalizing, Reauthorizing, and Reconceptualizing our Definitions, Assessment, and Interventions of Learnin

LD in 2003: Revitalizing, Reauthorizing, and Reconceptualizing our Definitions, Assessment, and Interventions of Learning Delayed Students. James McDougal Michael LeBlanc SUNY Oswego. NY Learning Disability Definition.

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LD in 2003: Revitalizing, Reauthorizing, and Reconceptualizing our Definitions, Assessment, and Interventions of Learnin

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  1. LD in 2003: Revitalizing, Reauthorizing, and Reconceptualizing our Definitions, Assessment, and Interventions of Learning Delayed Students James McDougal Michael LeBlanc SUNY Oswego

  2. NY Learning Disability Definition A student with a disorder in one or more of the basic psychological processes involved in understanding or in using language, spoken or written, which manifests itself in an imperfect ability to listen, think, speak, read, write, spell, or to do mathematical calculations. The term includes such conditions as perceptual handicaps, brain injury, neurological impairment, minimal brain dysfunction, dyslexia and developmental aphasia. The term does not include students who have learning problems which are primarily the result of visual, hearing or motor handicaps, of mental retardation, of emotional disturbance, or of environmental, cultural or economic disadvantage. A student who exhibits a discrepancy of 50 percent or more between expected achievement and actual achievement determined on an individual basis shall be deemed to have a learning disability

  3. IDEA's Definition of Learning Disability ". . . a disorder in one or more of the basic psychological processes involved in understanding or in using language, spoken or written, that may manifest itself in an imperfect ability to listen, think, speak, read, write, spell, or do mathematical calculations, including conditions such as perceptual disabilities, brain injury, minimal brain dysfunction, dyslexia, and developmental aphasia." However, learning disabilities do not include, "…learning problems that are primarily the result of visual, hearing, or motor disabilities, of mental retardation, of emotional disturbance, or of environmental, cultural, or economic disadvantage."

  4. Example of State Requirements for LD Diagnosis

  5. Achievement Intelligence Discrepancy

  6. Severe Discrepancy Determination by Formula Kate obtains an IQ score of 90 and an achievement score of 74. Is this 16-point difference large enough to be considered a ‘significant difference’ between ability and achievement? Data: Ability Score ………………………………………………... 90 Reliability of Ability Score ……………………………. … 0.91 Achievement Score ……………………………………….. 74 Achievement Reliability ………………………………….. 0.91 Correlation Between Ability and Achievement Scores .. 0.47

  7. Methods for Determining Severe Discrepancy • Deviation from Grade Level • Standard Deviation from the Mean • Standard Score Comparison • Regression Formula

  8. Deviation from Grade Level • difference between grade level functioning and placement • “Is a student’s measure of grade level functioning significantly different than his or her grade placement?” • For example: • Kate is in grade 6 and is achieving at a 3rd grade level • the 50% discrepancy would be considered a severe discrepancy

  9. Deviation from Grade Level (continued) • Problems: • grade equivalent scores are not based on equal units • learning is not linear • example: a third grader two years behind is not comparable to an 11th grader two years behind • least psychometrically sound method

  10. Standard Deviation from the Mean • Difference between obtained achievement and normed averages • Compares an individual to a group • “Is a student’s score on an achievement test discrepant from the test mean by a standard value” • To calculate: • change achievement score to z-score • compare the z-score to some predefined discrepancy (e.g., 1.5sd or 1.75 sd)

  11. Standard Deviation from the Mean (continued) • Example of Kate • if a severe discrepancy is defined as 1.5 sd • Kate’s achievement score of 74 would transform to a z-score of (74-100)/15=-1.73 • Kate’s discrepancy does qualify as a severe discrepancy • Problems: • conceptually different from measures of intrapersonal discrepancies & would qualify all low performing individuals • would not identify many students who would be expected to perform better than the average • does not consider measurement error

  12. Standard Score Comparison • Difference between standard scores from ability and achievement tests • Compares an individual to himself or herself • To calculate: • obtain measures of achievement and ability • change scores to z-scores • subtract achievement z-score from ability z-score and divide by standard error of the difference • compare to predefined severe discrepancy score

  13. Standard Score Comparison (continued) • Example of Kate • if a severe discrepancy is defined as 1.5 sd • Kate’s achievement score of 74 would transform to a z-score of (74-100)/15=-1.73 • Kate’s ability score of 90 would transform to a z-score of (90-100)/15=-0.66 • use formula (Zach-Zability)/((1-rxx) + (1-ryy))1/2 • (-1.73+.66)/.42 • -2.5 • compare -2.5 to 1.5 (note the severe discrepancy cutoff point is expressed as a positive value but think of it as a discrepancy between achievement and ability that would be a negative value when used to define ld) • because Kate’s discrepancy is larger than the predefined severe discrepancy • Kate’s discrepancy does qualify as a severe discrepancy

  14. Standard Score Comparison (continued) • Problems: • assumes that measures of ability perfectly correlate with measures of achievement • e.g., assumes that Kate’s measured IQ of 90 would mean that we expect her achievement score to be 90 • does not consider measurement error

  15. Regression Formula • Difference between standard scores from ability and achievement tests using regression formulas • use regression to predict an individual’s achievement score from his or her ability score • includes corrections for measurement error and regression to the mean

  16. Regression Formula (continued) • Example regression formula: y’ = rxy(Sy/Sx)(IQ - `x) + `y where: y’ = predicted achievement score rxy = correlation between IQ and achievement test Sy = standard deviation of achievement test Sx = standard deviation of IQ test `x = mean of IQ test `y = mean of achievement test

  17. Effects of Test Reliability or Error of Measurement Tests with high reliability Tests with low reliability

  18. Effects of CorrelationRegression to the Mean

  19. Regression Formula (continued) • After predicting achievement based on IQ • discrepancy is formed by calculating difference between actual and predicted achievement • the calculated discrepancy is tested for significance • is the discrepancy so large that we would consider it not likely due to chance? • Determination is made

  20. Regression Formula (continued) • Calculation discrepancy using a severe discrepancy calculator: • Kate’s Ability Score 90 • Achievement Score 74 • Reliability of Ability Score .91 • Achievement Reliability .91 • Correlation Between Ability and Achievement Scores .47

  21. Regression Formula (continued) • Predicted Achievement Score 95 • note: based on IQ score of 90, Kate’s predicted achievement score is “pulled towards the mean” • Difference between Predicted and Actual Achievement 21 • Magnitude of Difference required at .05 level 22 • Kate’s discrepancy doesnot qualify as a severe discrepancy

  22. 74 90 Kate’s Measured Achievement (74) and Ability (90)

  23. 74 90 95 Predicted Achievement Score (95) Based on IQ of 90

  24. Regression Formula (continued) • Problems: • complex calculations • excludes many students in lower ability range who would be included using simple discrepancy method • Benefit: • most psychometrically sound method

  25. Summary • Determination of LD Diagnosis is based in part on: • State determinations of severe discrepancy • method of calculating severe discrepancy • Different methods of calculating a discrepancy will result in different students being severely discrepant

  26. Summary • Regression models appear to produce proportional racial representation (Braden & Weiss, 1988) • Standard score comparison methods may over-identify high ability students and under-identify minority students (Braden & Weiss, 1988) • Deviation from grade level or test mean will under-identify high performing students.

  27. Questions • Is LD a Valid diagnosis? • can you make inferences based on LD? • Can you make predictions about LD individuals that differ from “low achievement”? • Is your method of determining LD consistent with your conception of LD? • e.g., intrapersonal construct vs. interpersonal construct

  28. Validity of LD as Discrepancy Based Construct • Cyril Burt (1937) “Capacity must obviously limit content. It is impossible for a pint jug to hold more than a pint of milk and it is equally impossible for a child’s educational attainment to rise higher than his educable capacity (p. 477).” • Implies that capacity to learn is fixed

  29. Validity • Learning disability is result of unexpected low achievement. • Also implies that children with unexpected low achievement (LD) are distinct from expected low achievement (i.e., low achievement and low intelligence).

  30. Validity • Validity of construct relies on its uniqueness and utility • Validity of a discrepancy based model assumes that ability-achievement discrepant children are qualitatively distinct regular “low achievers. • Also assumes that identifying LD will lead to useful interventions specific to that group.

  31. Assessing Validity of LD • Fletcher et al. (2001) describe means of validating LD diagnosis • Prognosis • Response to intervention • Distinct cognitive profiles

  32. Cognitive Domains • Meta-Analysis • Hoskyn & Swanson (2000) • Stuebing et al. (2002)

  33. Hoskyn & Swanson • “… few recognize that the use of discrepancy scores implies that it accomplishes something beyond their component parts. One obvious test of this notion is whether some children defined by discrepancy scores are more likely to respond favorably to one treatment when compared to those poor achieving children without discrepancies.”

  34. Hoskyn & Swanson • “Responsiveness to instruction seems to be a missing test in the majority of studies comparing discrepancy and nondiscrepancy groups. To date, there are no systematic analyses which support the notion that the discrepancy model is a useable construct when it comes to intervention and prognosis of intervention.”

  35. Stuebing et al. • Substantial overlap between IQ-discrepant & IQ-consistent poor readers • Differences between groups on several cognitive domains were negligible or small • Research indicates little need for using IQ tests in assessing LDs

  36. Prognosis • Do LD students and ordinary low-achievers differ in development of reading ability? • O’Mally et al. (2002) found little evidence of differences between groups. • Several longitudinal studies found little or no differences in reading development between groups.

  37. Response to Intervention • Research generally finds that discrepancy based LD vs. low-achievers do not respond differently to interventions. • Vellutino, Scanlon, Lyon (2000) reported that IQ-achievement discrepancy did not predict differences between groups on responses to mediation or which group would be more easily remediated.

  38. Assessing Validity of LD:Summary • Research indicates little or no differences between discrepancy based LD students and ordinary low achievers based on: • Cognitive Profiles • Prognosis • Response to intervention

  39. Validity • Current definitions and diagnosis of LD students lacks uniqueness (distinct group of learners) and utility (clear differences in treatment and prognosis).

  40. A New Era: Revitalizing Special Education for Children and their Families President’s Commission on Excellence in Special Education July 1, 2002

  41. Introduction to a New Era Students with disabilities drop out of high school at twice the rate of their peers Most public school educators do not feel well prepared to work with children with disabilities

  42. Introduction to a New Era Almost half of the children in special education are identified as having a specific learning disability- a 300% increase since 1976 80% of of those with SLD (40% of Sp Ed students) are there because they haven’t learned how to read

  43. Introduction to a New Era Children of minority status continue to be over represented in special education- African American students are twice as likely as whites to be labeled MR and 50% more likely to be designated as emotionally disturbed.

  44. Three Major Recommendations • Focus on results-not on the process • Embrace a model of prevention not failure • Consider children with disabilities as general education children first

  45. “The education of all children, regardless of background or disability must always be a national priority. One of the most important goals of my administration is to support states and local communities in creating and maintaining a system of public education where no child is left behind. Unfortunately, among those at greatest risk of being left behind are children with disabilities” President G. W. Bush, Executive Order 13227

  46. Federal Reg’s & Monitoring, paperwork reduction, increased flexibility *Assessment & Identification Sp Ed finance Accountability, flexibility, parental empowerment Post secondary results, effective transition services Teacher/administrator preparation, training, retention Sp Ed research and dissemination 7 Sections

  47. Assessment & Identification Identify and Intervene Early. Implement research-based, early identification and intervention programs to better serve children with learning and behavioral difficulties at an earlier age. Include early screening, prevention, and intervention practices to identify academic and behavioral problems in young children

  48. “Services first, assessment later,” • Commissioner Steve Bartlett

  49. Assessment & Identification Simplify the Identification Process. Simplify the ID and eligibility determination process, and clarify the criteria used to determine the existence of a disability, particularly high incidence disabilities.

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