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Who are the Learning Disabled? Is There a Future for A Cognitive Basis? Evidence from Meta-Analyses and Longitudinal Research PowerPoint Presentation

Who are the Learning Disabled? Is There a Future for A Cognitive Basis? Evidence from Meta-Analyses and Longitudinal Research

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### Who are the Learning Disabled?Is There a Future for A Cognitive Basis?Evidence from Meta-Analyses and Longitudinal Research

H. Lee Swanson

University of California-Riverside

Institute for Education Sciences

June , 2009

Overview of Meta-Analyses

1. Meta-analyses of Cognitive and RTI Research (in process)—with Brenda Arellano, Loan Tran and Tori Sanchez

2. Meta-Analysis of Adults with RD

- Funded by NIFL (with Ching-Ju (Rosie) Hsieh—under review
3. Meta-Analysis of Memory and RD

(JLD,2009 with Xinhua Zheng and Olga Jerman)

Overview of Reading and Math Projects

4. Meta-Analysis of Correlational Data on Phonological Awareness, Rapid naming and Reading

(Review of Educational Research, 2003)

Key Collaborators Guy Trainin, Denise Necoechea

5. Meta-analysis of Discrepancy and Non-Discrepancy Poor Readers (School Psychology Review-2000)

Key Collaborator—Maureen Hoskyn

Overview of Reading and Math Projects

- 6. Current—Math Disabilities vs. RD, RD and MD—2007 Review of Educational Research
- Key collaborators—Olga Jerman, Georgia Dukas, Rebecca Gregg
- 7. Meta-Analysis of Experimental Intervention Research in LD (RER, 1998, JLD, 2000, 2003)
- Several collaborators—
- Key collaborators- Maureen Hoskyn and Carole Lee

Issue 1. Progress Toward Operational Definitions

- Agree on Subtypes relevant to academic outcomes----Three currently
- New—directions explore high order definitions—problem solving, comprehension
- Explore Cognitive Basis for definitions

Assumption related to the definition

- 1. Not due to inadequate opportunity to learn, general intelligence, or to significant physical or emotional disorders, but to basic disorders in specific psychological processes (e.g., remembering the association between sounds and letters).
- 2. Not due to poor instruction, but to specific psychological processing problems that have a neurological, constitutional, and/or biological base.
- 3. Not manifested in all aspects of learning. Such individual’s psychological processing deficits depress only a limited aspect of academic behavior. For example, such individuals may suffer problems in word recognition, but not calculation.

How researchers generally operationalize SLD

- 1. There are two subtypes that have some consensus:
- reading disabilities and mathematical disabilities. –also consider comorbid group
- 2. These subtypes are defined by standardized (normed referenced) and reliable measures of intelligence and achievement. The most commonly used intelligence tests are from the Wechsler measures and common achievement tests that include measures of word recognition or arithmetic calculation (e.g., WIAT, WRAT, WRMT).
- 3. In general, individuals with IQ scores (e.g., verbal) equal to or above a standard score of 85 and reading subtest scores equal to or below the 25th percentile and/or arithmetic subtest scores equal to or below the 25th percentile reflect two high incidence disorders within LD: reading (word recognition), and arithmetic (computation, written work).
- 4. By far, the subtype that has received the most research attention is reading disabilities.

- Some issues in the area of cognition
- 1. Clouded by conflicting evidence on IQ and reading discrepancy research—
- (logic that similarities in overt behavior reflect the same inefficiencies and/or of cognitive processes—consider MD and RD)
- 2. Clouded by previous cognitive intervention research (poor generalization to changes in academics)
- 3. Psychometric aspects of measures in question

- 4. Inadequate research framework which clouds interpretation of outcomes
- 5. Knowing cognitive deficits does not indicate teaching directions
- 6. There are few analogs (low inference observation measures) linking cognitive performance to classroom performance

Perspective of outcomes

- 1. Purpose of assessing cognition is to explain the “why” and “predict” how individual differences account for treatment outcomes
- 2. Purpose of an instructional approach (e.g., RTI) is to monitor the intensity of intervention (instruction) and make systematic changes as a function of overt performance—
- Pt----the approaches are complementary -
- Pt-The study of cognition has the potential to outline constraints in learning when individual differences cannot be explained as a function of best instructional practice
- Pt—instruction accounts for less than 20% of the variance in effect sizes (Swanson, 1999; Simmerman & Swanson, 2001)

Table 2. Regression model predicting effect size as a function of methods composite score, age, and instructional components

- Table 2 function of methods composite score, age, and instructional components
- Predictions of Year 3 Problem Solving Accuracy Based on Wave 3 Math Calculation,
- Problem Solving Knowledge and Wave 1 Fluid Intelligence, Reading and Cognitive Variables
- Model 5 B SE ß t
- Wave 3 Predictors
- Problem Solving Knowledge 0.25 0.11 0.12 2.13*
- Calculation 0.30 0.08 0.27 3.42**
- Wave 1 Predictors
- Fluid Intelligence (Raven) 0.13 0.04 0.16 2.85**
- Reading 0.12 0.12 0.12 1.00
- Phon. Know. -0.01 0.10 0.10 -0.09
- Fluency 0.02 0.07 0.007 0.33
- Speed -0.004 0.06 -0.004 -0.06
- Inhibition 0.09 0.06 0.07 1.60
- Age -0.15 0.06 -0.16 -2.39*
- Sketchpad 0.15 0.04 0.14 3.23***
- Phon. Loop 0.12 0.06 0.09 1.85
- Executive 0.19 0.08 0.15 2.34*
- Model 5 F (12, 279) = 22.52; p< .001, R2 = .49

Math Calculation function of methods composite score, age, and instructional components

Reading Composite function of methods composite score, age, and instructional components

Phonological Processing function of methods composite score, age, and instructional components

Word Problems function of methods composite score, age, and instructional components

A Focus on the Instructional Side of LD function of methods composite score, age, and instructional components

Issue 2: Determine Meaningful Outcomes function of methods composite score, age, and instructional components

- 1. Control group needs to include significant instructional moderators (e.g.,DRP, overlap with treatment)
- 2. Determine the role definitional moderators

Why Do A Meta-Analysis to address these questions? function of methods composite score, age, and instructional components

- 1. Evidence Based—Pattern across several studies vs. single study---vs. overstated or understated information
- 2. Influence of sample (age, IQ, Discrepancy) and intervention parameters (time,responsiveness vs. resistance to instruction, components of instruction) on outcomes.
- 3. Theory Testing---identify the core problem---area most resistant to intervention
- 4. Allows for Replication

Interpretation function of methods composite score, age, and instructional components

For the purpose of discussion, Cohen’s (1988) distinctions on the magnitude of the effect size will be used.

* .20 is a small size

* .60 is a moderate size

* .80 is a large effect size

Table 1 NRP function of methods composite score, age, and instructional components

Can we ignore cognition by focusing primarily on evidence-based instruction ?What do we know related to evidence based intervention and where should we go?1. Meta-Analysis of Experimental Interventions and LD (e.g., RER, 1989, JLD 2001).2. Meta-analysis of Dynamic Assessment (e.g., RER, 2001)3. Meta-analysis of RTI research (in progress)

Criteria evidence-based instruction ?

- Computer search, dissertations, state department reports- 3000 manuscripts
. Control group, average intelligence, minimum of 3 sessions, ES can be calculated.

Final 180 group design (K=1,537) and 85 single subject design studies (K=793)

Bottom line for evidence based studies evidence-based instruction ?

- 1. Mean ES between LD in control and TRT .56
- 2. Mean ES between LD (Exp. TRT) and NLD in .97
- 3. Majority of Studies measure Reading
- 4. Several variables significantly moderate treatment outcomes (IQ & Reading, teacher effects, # components overlap, standardized vs. experimental measures, ratings on internal and external validity)
- 5. Combined Strategy and Direct instruction most robust procedure

Table 4 evidence-based instruction ?

Weighted Mean, Effect Sizes for Group Design Studies as a Function of Dependent Measure

Category

LD Treatment vs. LD Control

K

N

Effect Size Q

Effect Size Q

95 % Confidence Interval

Standard

Error

Unwe

ighted*

Weighted"

for Weighted Effects

Lower

Upper

1.

Cognitive Processing

41

115

.87

.54

.48

.61

.03

1 a. Metacognitive

9

27

.98

.80

.66

.94

.07

1b. Attribution

7

17

.79

.62

.44

.79

.08

I c. Oth

er Processes

25

71

.65

.46

.38

.53

.03

2.

Word Recognition

54

159

.71

.57

.52

.62

.02

2a. Standardized

23

79

.79

.62

.54

.69

.04

2b. Experimental

35

80

.72

.53

.48

.60

.03

3.

Reading Comprehension

58

176

.82

.72

.68

.77

.02

3a. Standardized

16

38

.45

.45

.36

.54

.05

3b. Experimental

44

138

.84

.81

.75

.86

.02

4.

Spelling

24

54

.54

.44

.37

.52

.04

4a. Standardized

.8

20

.61

.45

.34

.57

.06

4b. Experimental

18

34

.48

.44

.33

.54

.05

5.

Memory/Recall

12

33

.81

.56

.43

.70

.06

6.

Mathematics

28

71

.58

.40

.33

.46

.04

6a. Standardized

9

22

.41

.33

.23

.46

.05

6b. Experimental

21

49

.59

.42

.34

.51

.04

7.

Writing

19

67

.84

.63

.54

.72

.05

II

.

7a. Standardized

3

7

.37

.36

.14

.58

7b. Experimental

16

60

.80

.68

.59

. 78

.04

8.

Vocabulary

11

20

.79

.78

.66

.89

.05

TABLE 25. Mean Effect Sizes on Instructional Components Comparing LD in Treatment Conditions to NLD Participants

Issue 3: Determine the moderating role of IQ Comparing LD in Treatment Conditions to NLD Participants

What about Bob (IQ) ? Comparing LD in Treatment Conditions to NLD Participants

- 1. Does IQ relate to treatment outcomes ?
- Rephrase the question—if IQ is left out of the definition will it influence treatment outcomes?

Instructional Outcomes as A Function of IQ and Reading Level Comparing LD in Treatment Conditions to NLD Participants

Bottom Line ON IQ Comparing LD in Treatment Conditions to NLD Participants

- 1. LD in Exp. Condition vs. average ES=.69 for IQ+RD information
- ES=1.41 for no IQ + RD information
- 2. LD in Exp. vs. LD in Control
- ES=.63 for IQ+RD information
- ES=.82 for no IQ +RD information
- ES=.60 for IQ+RD+Math information

Mixed Regression Modeling for Predicting Estimates of Effect Size in Cognitive Processing

A speculation Size in Cognitive Processing

- Based on studies that include optimal instructional conditions—the mean effect size one could expect comparing LD with nonLD is (tier 2 or 3)----
- D-R-P (.78)
- Systematic Probing (.73)
- Peer Mediation (.52)
- Strategy Cuing (.74)
- Mean ES=.69 under evidence based instruction---which may varying depending on the entry of new data--

Issue 4:Develop Standardized Measures related to Dynamic Assessment

- Can we detect LD early with DA procedures?---longitudinal research
- DA of Cognitive and/or Academic?

Synthesis of Experimental on Dynamic Assessment (RER, 2001) Assessment

- Criteria for Selection
- 1. Published Refereed Journal
- 2. Control group comparison (between and within comparisons) for DA vs. static or traditional measurement (no feedback)
- 3. 30 articles from 303 potential (majority eliminated because ES could not be calculated, duplicate data) articles analyzed

Questions Assessment

- Is new information gained by DA procedures relative to traditional assessment?
- Are some groups of children more responsive then others?
- Which DA procedures yield the highest outcomes (relative to traditional assessment )?

Results and Implications for LD---DA vs. traditional Assessment

- 1. Lower effect sizes emerge for LD relative to other categories of children
- 2. Largest ESs occur for underachievers
- 3. Testing limits (e.g., scaffolding---various cuing procedures) and general strategies (general feedback, modeling strategies) yielded higher outcomes than test-train-test models
- Implication---LD sample performance as a function of DA is hard to change relative to other groups--

Issue 5: determine if RTI studies can change risk factor of children already with serious risk factors (beyond what psychometric studies can provide)----is there better explanatory power knowing general areas of cognition?

- IS RTI itself a wait and fail situation???

Meta-analytic look at RTI findings children already with serious risk factors (beyond what psychometric studies can provide)----is there better explanatory power knowing general areas of cognition?

Criteria for Selection

1. Published Study (1985-2008)-

2. Divided sample into

responders and nonresponders

3. Focus on reading-Elementary

4. Reported Pretest Scores by Responders and Nonresponders

5. Reported Standardized scores

6. Allow for calculation of ES

Only 9 studies met criteria (119 ES)

Issues facing RTI and how a Meta-analysis can help children already with serious risk factors (beyond what psychometric studies can provide)----is there better explanatory power knowing general areas of cognition?

- 1. No (or few) systematic control studies (none meeting the gold standard) comparing RTI with a competing model of classification
- 2. RTI is a function of instruction (as well as teachers), and because there is no standardized protocol for instruction—how well can people generalize from findings to classify child at risk across school districts?
- 3. No consensus on definition of what resistance to instruction should be (slope of 0 or .25 or benchmarks?)---Is the issue really intercept level and not change (slope)?

Group Design RTI Studies (Responder vs. nonresponder in the same evidence-based intervention)

Tentative Conclusions (RTI Studies) same evidence-based intervention)

- 1. Pretest differences for some children seriously at risk remain stable—and a source for determining LD
- 2. Instruction is not robust enough to ignore individual differences in achievement and “perhaps” cognition

Conclusion on Interventions—Who are the SLD ? same evidence-based intervention)

- Children who yield low outcomes under optimal instructional conditions (components that significantly and positively influence effect sizes
- Those optimal instructional components that predicted treatment outcomes---Drill-repetition-skills, strategy training and small interactive groups
- Definition does influence outcomes-IQ and Reading Scores in combination are not irrelevant to instructional outcomes (at least from this data set). Average IQ and low Reading group (< 25th percentile) appears to be one subgroup most at risk in terms of the magnitude of outcomes.

The Assessment Side of LD same evidence-based intervention)

- What Cognitive Variables are Important in Assessing RD and MD in children?
- Do risk factors related to Cognition go away in adulthood?

Issue 6: What are the important cognitive processes to consider in in children and adults with LD ?

- What are the common cognitive deficits among subgroups?
- What are the non-overlapping cognitive deficits among subgroups?
- What deficient cognitive processes operate independent of classification variables--

Research and Policy Question consider in

1. Are cognitive deficits comparable between RD and MD children?

2. Does the identification of cognitive processes help in the classification (does it matter) ?

Selection criteria consider in

- 1. Pool in excess of 800 articles
- 2. 85 articles with defined control groups (needed at least a nondisabled control group)
- 3. Standardized math,reading, and IQ scores
- 4. 28 studies met full inclusion criteria—

Table 2 consider in Psychological and Demographic Information on Participants

Table 2 Continued consider in

Table 2 Continued consider in

Table 3 consider in Weighted Effect Sizes, Standard Error, Confidence Intervals and Homogeneity of Categories for Comparisons between MD and non math disabled (MD/NMD), MD and reading disabled (MD/RD), and MD and RD+MD (CMOR) (corrected for outliers).

Table 3 Continued consider in

Table 3 Continued consider in

Table 3 Continued consider in

What About Applied Cognition (Memory)—JLD-2009 consider in

- 1. Published studies—1970-2008
- 2. Defined RD and CA matched NONRD sample by Standardized scores
- 3. Outcomes on at least one STM or WM measure (operationally defined)
- 4. 88 studies, weighted ES=-.89, STM=-.65, WM=-.67
- 5. Low IQ+Low Reading ES (RD vs. NRD)=-.49,High IQ+low reading=-.85
- 6. 52 % of between study variance explained by Memory

- W consider in
- Effect Size as a Function of Categorical Variables When Compared to Chronological Age and IQ Matched
- CCategory Number of Studies M SD K Weighted Effect Size 95% CI for effect size
- Lower Upper
- SShort-Term Memory
- 1. Phonological 7 -0.83 1.15 22 -0.39 -0.50 -0.29
- 2. Pictures 17 -0.90 1.13 53 -0.57 -0.65 -0.49
- 3. Words 25 -0.50 0.66 76 -0.55 -0.61 -0.48
- 4. Digits 11 -1.49 2.2 55 -0.63 -0.69 -0.56
- 5. Letters 4 -1.06 0.52 13 -1.10 -1.24 -0.95
- DDual Task-Trade-off-reorder
- 6. Backwards 16 -0.70 0.45 59 -0.69 -0.74 -0.63
- 7. Preload 3 -0.53 0.27 7 -0.49 -0.73 -0.26

- NNumber of Studies M SD K Weighted Effect Size 95% CI for effect size
- Lower Upper
- WWorking Memory-D & C format
- 9 Counting 10 -0.88 0.55 32 -0.78 -0.84 -0.73
- 1Listen/Sentence19 -1.51 1.21 57 -0.84 -0.89 -0.79
- 1 Visual- Matrix 26 -0.69 0.63 72 -0.80 -0.86 -0.74
- 1 Complex Visual.6 -0.52 0.17 20 -0.48 -0.57 -0.39
- 1 Semantic Assoc.10 -0.81 0.44 31 -0.37 -0.44 -0.30
- 1 Digit/Sentence10 -1.47 2.25 24 -0.58 -0.68 -0.48
- Story Retelling 4 -0.80 0.7 9 -0.37 -0.50 -0.24
- 1Phonol/Rhyming 7 0.32 13 -0.61 -0.74 -0.49 -0.72
- D & C=Daneman and Carpenter task format

Rapid Naming, Phonological Awareness and Reading Weighted Effect Size 95% CI for effect size

Big Question Weighted Effect Size 95% CI for effect size

- Is Phonological Awareness the most important variable in predicting reading accuracy? or is a more comprehensive cognitive battery called for?

Research Questions Weighted Effect Size 95% CI for effect size

- 1.What is the correlational evidence on the relationships between phonological awareness, rapid naming speed, and sight word recognition?
- 2. Do other processes play an important role?
- 3. Are the correlations between RAN and PA independent—are they sensitive to age?

Selection Criteria Weighted Effect Size 95% CI for effect size

- Dates 1966-2001-Include PA, RAN, and reading (138 studies)
- 35 Studies Meeting Selection Parameters (report SD, complete intercorrelations)
- Correlations (K=2,257)

Table 4 Weighted Effect Size 95% CI for effect size Estimated Intercorrelations Among Cognitive Measures

Conclusions Weighted Effect Size 95% CI for effect size

- 1. Predictions of real word reading—
- No clear advantages for PA and RAN when compared with other variables
- 2. Role of Chronological age—age did not appear to play a moderating role in the correlations between RAN and PA

Do process deficits go away with time? Adult Outcomes Weighted Effect Size 95% CI for effect size

- 1. Pool in excess of 450 articles- samples > 18 yrs of age and reading scores
- 2. Articles with RD and defined control groups (needed at least a nondisabled control group)
- 3. Standardized reading and IQ scores
- 4. Reported measures independent of classification measures
- 5. 52 studies met full inclusion criteria—

RD vs. Slow Learners: More Alike than Different? Weighted Effect Size 95% CI for effect size

Big Question Weighted Effect Size 95% CI for effect size

- Is IQ completely irrelevant in separating various reading groups??

Research Questions Weighted Effect Size 95% CI for effect size

- 1. Is the phonological core deficit the only process that holds between the two groups?
- 2.Are the effect sizes moderated by Age and/or verbal IQ?
- Problem—what’s low achiever (< 96 on IQ and reading—40th percentile)
- What’s RD (25th percentile in reading and verbal IQ > 80---designated discrepancy)

Selection of Studies Weighted Effect Size 95% CI for effect size

- 1. 20year period—must include comparison of Discrepancy and Non Discrepancy groups
- 2. Criterion measure was reading recognition
- 3 Must report Standardized Intelligence and Reading Measures
- 4. Published in a refereed journal-English
- 69 potential articles—
19 met criteria-274 effect sizes

Mean ES .21 (SD=.65)

Table 1 Weighted Effect Size 95% CI for effect size

Age and Psychometric Characteristics of Children with RD and Low Achievers

Magnitude of Effect Size by Category of Dependent Measure. Weighted Effect Size 95% CI for effect size

Conclusions Weighted Effect Size 95% CI for effect size

- Verbal IQ and Age moderate the overall level of cognitive performance.—
This conclusion is different than saying IQ is irrelevant

Overall Conclusions Weighted Effect Size 95% CI for effect size

- Who are the SLD?
- Children with average IQ’s (>84) with reading and/or math scores below the 25th percentile whose academic performance outcomes remain below an ES of .70 (when compared to normal achieving peers) after intense exposure to optimal instructional conditions

- 1. There evidence to suggest that IQ (at least verbal IQ) should “not” be thrown out of the definition.
- 2. Two processes are critical (PA, WM) when determining the subtypes of disabilities.
- 3. Children at great risk for SLD are those exposed to optimal instructional conditions who are in the average range of intelligence and also experience processing inefficiencies in PA and WM.

Where to go from here? should “not” be thrown out of the definition.

Validating a Science Based Model of Learning Disabilities should “not” be thrown out of the definition.Swanson, H.L. (2008) Neuroscience and Response to Instruction (RTI): A complementary Role In C. Reynolds & E. Fletcher-Janzen (Eds.) Neuropsychological Perspectives on Learning Disabilities in the Era of RTI: Recommendation for Diagnosis and Intervention. NY: John Wiley & Sons.Steps 1-3

Step 4 should “not” be thrown out of the definition.

Step 5 should “not” be thrown out of the definition.

Step 6 should “not” be thrown out of the definition.

Step 7 should “not” be thrown out of the definition.

- Step 7: Formulate a metatheory of learning disabilities by designating the parameters susceptible and not susceptible to instruction
- a.If anomalous data occur, return to Step 1.b.
- b. If additional data confirm theory, broaden context (e.g., determine influence of non-cognitive classroom variables on learning).

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