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 cognition1. 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

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

Χ2 beta Standard error

1. Methods 20.78*** -0.03 0.01

2. Age 1.11 -0.01 0.01

1. Sequencing 0.2 0.03 0.09

2. Explicit practice 7.39** 0.18 0.08

3. Novelty 1.07 -0.06 0.08

4. Attributions 0.04 -0.06 0.39

5. Reinforcement 0.25 -0.06 0.16

6. Peer modeling 0.26 -0.08 0.21

7. Task reduction 2.66 -0.09 0.08

8. Advanced organ 8.23*** 0.19 0.09

9. Questioning 2.94 -0.13 0.1

10. One-to-one instruction 0.45 -0.04 0.08

11. Control difficulty 0.18 0.02 0.08

12. Technology 0.95 0.05 0.07

13. Elaboration 0.52 0.09 0.17

14. Skill modeling 3.89* 0.13 0.09

15. Small group instruction 4.48* 0.14 0.09

16. Supplemental cues 0.91 0.12 0.17

17. Strategy cues 4.63* -0.16 0.1

18. Large group learning 4.17* 0.12 0.08

R2 = .20, Χ2 (df 20, N = 180) = 75.22 Intercept .86 (SE = .16)

Table 2 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

Math Calculation

-2.5

-2.25

-2

-1.75

-1.5

-1.25

-1

-0.75

-0.5

-0.25

0

0.25

0.5

0.75

1

1.25

1.5

1.75

2

2.25

2.5

Age 6 Age 7 Age 8 Age 9 Age 10

Growth

Mea

n Z

-sco

re

At Risk

Not At Risk

At Risk

Not At Risk

At Risk

Not At Risk

Reading Composite

Reading

-2.5

-2.25

-2

-1.75

-1.5

-1.25

-1

-0.75

-0.5

-0.25

0

0.25

0.5

0.75

1

1.25

1.5

1.75

2

2.25

2.5

Age 6 Age 7 Age 8 Age 9 Age 10

Growth

Mea

n Z

-sco

re

At Risk

Not At Risk

At Risk

Not At Risk

At Risk

Not At Risk

Phonological Processing

Phonological Processing

-2.5

-2.25

-2

-1.75

-1.5

-1.25

-1

-0.75

-0.5

-0.25

0

0.25

0.5

0.75

1

1.25

1.5

1.75

2

2.25

2.5

Age 6 Age 7 Age 8 Age 9 Age 10

Growth

Mea

n Z

-sco

re

At Risk

Not At Risk

At Risk

Not At Risk

At Risk

Not At Risk

Word Problems

Word Problem Solving

-2.5

-2.25

-2

-1.75

-1.5

-1.25

-1

-0.75

-0.5

-0.25

0

0.25

0.5

0.75

1

1.25

1.5

1.75

2

2.25

2.5

Age 6 Age 7 Age 8 Age 9 Age 10

Mea

n Z

-Sco

re

At Risk

Not At Risk

At Risk

Not At Risk

At Risk

Not At Risk

Growth

A Focus on the Instructional Side of LD

Issue 2: Determine Meaningful Outcomes1. 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?

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

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

Moderator Variables Mean Effect Sizes Cohen's Descriptors for d & r

Mean Effect Correlations

Mean d Mean r r²

Synthetic Phonics for Various Groups

K & 1st at Risk .64 MODERATE .30 .09 1st Normal .54 MODERATE .26 .07 2nd-6th Normal .27 SMALL .13 .02 2nd-6th Low Achievers .14ns TRIVIAL .07 .00 Reading Disabled .36 SMALL .18 .03 Unit of Instruction Tutor .57 MODERATE .27 .07 Small Group .43 SMALL .21 .04 Class .39 SMALL .19 .04

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

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 studies1. Mean ES between LD in control and TRT .562. Mean ES between LD (Exp. TRT) and NLD

in .973. Majority of Studies measure Reading4. 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

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

LD Treatment vs. LD Control

N K Effect Size Q Effect Size Q 95 % Confidence Interval Standard Error

Unweighted* 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. Other 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 7a. Standardized 3 7 .37 .36 .14 .58 . II 7b. Experimental 16 60 .80 .68 .59 . 78 .04

8. Vocabulary 11 20 .79 .78 .66 .89 .05

Table 4 continued

LD Treatment vs. LD Control

N K Effect Size Q Effect Size g 95 % Confidence Interval Standard Error

Unweighted* Weighted for Weighted Effects

Lower Upper

9. Attitude/Self-Concept 25 86 .68 (.69) .39 .33 .45 .03

10. Intelligence 9 32 .58 (.59) .41 .30 .52 .06

II. General Reading 15 31 .60 (.50) .52 .41 .65 .06

12. Phonics/orthographic 29 175 .70 (.36) .64 .60 .69 .02 12a. Standardized phonics 8 60 .72 .67 .62 .73 .03 12b. Experimental phonics 21 78 .76 .60 .52 .67 .04

13. Global Achievement 10 21 .91 (.76) .45 .31 .58 .07

(Grades, total achievement)

14. Creativity 3 11 .84 (.49) .70 .52 .87 .09

15. Social Skills 13 36 .46 (.22) .41 .30 .51 .05

16. Perceptual Processes 10 37 .74 (.65) .26 .17 .35 .04

9 52 .36 .28 .44 .04 17. Language

.54 (.48)

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

Components N Mean SD

1. Sequencing 13 0.96 0.55

2. Drill-repetition-practice-feedback 9 0.78* 0.44

3. Orienting to process or task 8 1.13 0.52

4. Question/answer verbal interaction 3 1.2 0.46

5. Individual plus small group 16 0.95 0.53

6. Novelty 14 0.94 0.54

7. Strategy attributions (self-monitoring) 10 0.80 0.53

8. Systematic probing 6 0.73* 0.38

9. Peer mediation (tutoring) 1 0.52* -

10. Segmentation 10 1.04 0.62

11. Advanced organizers 8 1.31 0.52

12. Directed questioning 2 1.06 0.55

13. One-to-one tutoring 12 0.85 0.54

14. Control for task difficulty 5 1.21 0.43

15. Technology 6 0.97 0.74

16. Elaboration 1 1.5 -

17. Teacher modeling 9 0.93 0.57

18. Small group interaction 12 1.01 0.56

19. Parents as mediators 1 1.68 -

20. Strategy cuing 5 0.74* 0.72

Note. NLD served as a control group and did not participate in treatment. N, number of studies ,*effect sizes at .80 and below

Issue 3: Determine the moderating role of IQ

What about Bob (IQ) ?

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

Bottom Line ON IQ

1. LD in Exp. Condition vs. average ES=.69 for IQ+RD information

ES=1.41 for no IQ + RD information2. LD in Exp. vs. LD in ControlES=.63 for IQ+RD informationES=.82 for no IQ +RD informationES=.60 for IQ+RD+Math information

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

Predictor VariableModel 1 Model 2 Model 3 Model 4 Model 5 Model 6

Age -6.95*** -4.79*** - -4.98*** - -5.42***

Word recognition -1.14 .04 - -.07 - .74

Verbal IQ 3.29** 6.32** - 2.96** - 2.96**

Discrepancy contrast - - - .96 2.81** 1.12

RD-IQ contrast - - - -2.14* - -1.66

LA-IQ contrast - - - -.01 - .52

Spelling -.43 .15 - .27 .32

phonol. Processing -.61 .49 - .70 .47

Pseudo-word reading -3.08** - -.72 - -.43 -1.00

Real-word phonetic analysis

-.65 - .56 - .90 .21

Automaticity -4.22*** - -.43 - -.40 -1.05

Memory - .28 -.13 - .16 .08

Lexical knowledge - 3.09** 1.57 - 1.85 1.35

Syntactical knowledge - 3.61** 2.53** - 2.86** 1.80

Spatial ability - 3.21*** .93 - 1.21 1.39

Motor ability - .76 .00 - .01 .01

REML Log Likelihood 511.95 520.56 538.14 527.20 533.60 511.46

A speculation

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?

Criteria for Selection1. Published Refereed Journal2. 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

Synthesis of Experimental on Dynamic Assessment (RER, 2001)

Questions

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 )?

Effect Size

Item N K Weighted Lower Upper Age Range

1. Younger « 10)

4,480

55 0.65 0.62 0.72. Middle (10-13)

4,90678 0.36 0.31 0.4

3. Older (> 13)

2,55831 0.38 0.32 0.44

Domain

1. Verbal 368 11 0.31 0.16 0.472. Visual-Spatial

11,548153 0.48 0.45 0.51

Classification1. Average Ach.7,523 98 0.41 0.38 0.452. MR 2,645 23 0.49 0.43 0.553. LD 633 20 0.1 -0.01 0.224. Uach 419 8 0.98 0.81 1.145. Hearing 350 9 0.75 0.58 0.91

# Sessions1. Single 9,154 127 0.48 0.45 0.522. Multiple 2,762 37 0.43 0.37 0.49

Type of Inst.1. T. Limits 8,221 128 0.48 0.45 0.522.Train 1,695 14 0.21 0.15 0.283. Strat/Monit.2,000 22 0.65 0.58 0.71

95% CI for

Weighted Effects

Results and Implications for LD---DA vs. traditional1. Lower effect sizes emerge for LD relative to

other categories of children2. Largest ESs occur for underachievers3. 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

Criteria for Selection1. Published Study (1985-2008)-2. Divided sample intoresponders and nonresponders3. Focus on reading-Elementary4. Reported Pretest Scores by Responders and

Nonresponders5. Reported Standardized scores6. Allow for calculation of ESOnly 9 studies met criteria (119 ES)

Issues facing RTI and how a Meta-analysis can help1. 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)

Variable K

Mean

SD

Effect Sizes*

ES pretest 62 1.05 0.97

ES posttest 93 1.09 1.27

Gains-Total Sample

ES gain Score 51 0.41 0.98

ES corrected Gain Score

51 0.27 0.65

Weighted Effect Sizes as a Function of Categories Comparing Responders and Nonresponders at Risk for RD

K Weighted Effect Size

SE Lower Confidence

Upper Confidence Homogeneity (Q)

Post-Test

Word Identification

18 1.27 0.074 1.12 1.42 74.97***

Phon./Basic Skills

9 1.18 0.11 0.96 1.39 44.43**

Word Attack 16 1.53 0.095 1.34 1.71 155.27***

Naming Speed 8 -0.68 0.08 -0.86 -0.51 12.20

Vocabulary 5 0.81 0.16 0.49 1.14 14.13**

IQ 7 1.04 0.107 0.83 1.25 11.94

Spelling 10 0.87 0.17 0.53 1.22 45.68**

Behavior Rating 5 0.3 0.23 -0.16 0.76 39.41***

Process (DTLA) 6 0.8 0.24 0.33 1.27 4.06

Orthography 4 0.89 0.1 0.68 1.11 2.86

Table 3

Weighted Effect Sizes as a Function of Categories Comparing Responders and Nonresponders at Risk for RD

K Weighted Effect Size

Standard Error

Lower Confidence

Upper Confidence

Homogeneity (Q)

Pretest

Word identification

16 0.94 0.07 0.79 1.09 48.29***

Phon./Skills 8 1.19 0.11 0.96 1.41 36.40***

Word Attack 14 1.24 0.1 1.03 1.44 79.75**

Naming Speed 1 -1.07

IQ 1 1.16

Spelling 3 0.86 0.26 0.34 1.38 0.35

Behavior

Ratings

5 0.024

0.22 -0.41 0.46 25.73**

Table 4

Effect Sizes for Post-test when Compared to Normed Referenced Measures at Pre-test.

Word Identification

Phon. Process/Basic Skills

Word Attack

Pre-Test (SS)

Mean SD Mean SD Mean SD

Responders

92.52 14.7

92.55 13.7 96.06 8.54

Low responders

82.28 9.91

81.65 7.29 86.74 9.97

Effect Sizes

Pretest 1.02 0.64

1.47 0.9 1.13 0.51

Post-test 1.39 0.77

1.41 0.84 1.88 1.35

Spearman Rho

0.71 0.88

0.82

.83

Tentative Conclusions (RTI Studies)

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 ?1. Children who yield low outcomes under optimal

instructional conditions (components that significantly and positively influence effect sizes

2. Those optimal instructional components that predicted treatment outcomes---Drill-repetition-skills, strategy training and small interactive groups

3. 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

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--

Math disabilities: Meta-analysis of published literature

Research and Policy Question

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

1. Pool in excess of 800 articles2. 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 Psychological and Demographic Information on Participants

Chronological Age Matched (N=784) Math Disabled (N=527) Effect Size

M SD Range M SD Range M SD

Age 124.51 52.22 72-158 123.64 58.93 73-157 .12 .34

IQ 105.59 8.70 80-120 99.69 8.51 80-119 -.59 .40

Math 105.64 6.51 96-119 84.76 5.93 75-96 -2.19 1.13

Reading 106.80 5.93 96-113 98.37 7.68 87-109 -.59 .49

Table 2 Continued

Comorbid (MD & RD)(N=135) Math Disabled (N=294) Effect Size

M SD Range M SD Range M SD

Age 122.49 47.49 57-322 135.76 83.65 56-304 -.54 .99

IQ 92.43 5.10 89-98 99.92 5.64 94-112 .59 .16

Math 84.65 2.84 81-87 86.02 7.92 75-88 .26 .24

Reading 82.83 1.25 81-87 100.75 8.28 84-108 1.68 .47

Note. Negative effect size is in favor of contrast group and positive effect size is in favor of MD group.

Table 2 Continued

Reading Disabled (N=224) Math Disabled (N=250) Effect Size

M SD Range M SD Range M SD

Age 131.25 82.30 59-141 135.34 76.84 59-142 .08 .33

IQ 96.78 7.55 80-107 97.83 8.93 80-105 -.31 .56

Math 95.75 8.87 85-103 86.61 6.56 75-87 -1.11 1.50

Reading 80.69 6.75 66-87 99.058 8.16 97-1054 2.27 1.16

Table 3 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).

Comparison K Effect Size Standard

Error Lower Upper Homogeneity Q

Total Across Categories

MD/NMD 194 -.52 .01 -.56 -.48 767.05***

MD/RD 58 -.10a .03 -.16 -.04 263.35***

MD/CMOR 102 .26a .02 .22 .31 650.86***

1. Literacy (vocabulary, reading comprehension)

MD/NMD 19 -.30 .05 -.40 -.40 73.52***

MD/RD 6 .11 .07 -.02 .25 2.00

MD/CMOR 10 .75 .06 .62 .88 49.30**

2. Problem Solving-verbal

MD/NMD 29 -.58 .04 -.67 -.49 242.41***

MD/RD 1 .10 . . . .

MD/CMOR 15 .13 .05 .02 .23 107.72

Table 3 Continued

Comparison K Effect Size Standard

Error Lower Upper Homogeneity Q

3. Speed-naming

MD/NMD 17 -.70 .06 -.83 -.56 55.70 ***

MD/RD 6 -.23 .13 -.49 .02 .38

MD/CMOR 10 -.39 .09 -.58 -.19 6.01

4. Visual-spatial Problem Solving

MD/NMD 23 -.48 .05 -.47 -.31 41.61***

MD/RD 4 .04 .09 -.17 .18 8.90*

MD/CMOR 10 .51 .06 .38 .64 44.03***

5. LTM-retrieval (e.g., general information)

MD/NMD 15 -.72 .09 -.90 -.54 35.49***

MD/RD 0 . . . . .

MD/CMOR 9 .44 .12 .20 .69 10.35

Table 3 Continued

Comparison K Effect Size Standard

Error Lower Upper Homogeneity Q

6. STM-Words

MD/NMD 16 -.45 .06 -.58 -.32 44.78***

MD/RD 3 .16 .13 -.10 .42 7.33*

MD/CMOR 4 .71 .12 .46 .96 12.61**

7.STM-Digits/numbers

MD/NMD 11 -.26 .07 -.41 .10 48.94***

MD/RD 4 .03 .14 -.24 .32 6.35

MD/CMOR 9 -.08 .11 -.30 .13 110.57***

8. WM-Verbal

MD/NMD 43 -.70 .04 -.79 -.61 83.84***

MD/RD 19 -.07 .06 -.19 .04 139.95***

MD/CMOR 20 .30 .06 .17 .42 86.49**

Table 3 Continued

Comparison K Effect Size Standard

Error Lower Upper Homogeneity Q

9.WM-Visual Spatial

MD/NMD 13 -.63 .07 -.77 -.48 28.14**

MD/RD 13 -.30 .07 -.44 -.16 35.43**

MD/CMOR 13 .23 .07 .08 .38 14.10

10. Attention

MD/NMD 8 -.15 .09 -.33 .03 34.83***

MD/RD 0 - - - - -

MD/CMOR 2 -.57 .11 -.79 -.35 6.97*

Note. MD = Math Disabled only, NMD = non math disabled-average achiever, RD = reading disabled, CMOR

= comorbid group with both low reading and math; K = number of measures, Lower and Upper = 95% level

of confidence range. a Positive effect sizes favor MD and negative effect sizes favor comparison group;

*p < 05, **p < .01, ***p < .001.

What About Applied Cognition (Memory)—JLD-20091. Published studies—1970-20082. Defined RD and CA matched NONRD sample

by Standardized scores3. Outcomes on at least one STM or WM measure

(operationally defined)4. 88 studies, weighted ES=-.89, STM=-.65,

WM=-.675. Low IQ+Low Reading ES (RD vs.

NRD)=-.49,High IQ+low reading=-.856. 52 % of between study variance explained by

Memory

W 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

LowerUpper

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

LowerUpper

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- Matrix26 -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

Big Question

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

Research Questions

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

Dates 1966-2001-Include PA, RAN, and reading (138 studies)

35 Studies Meeting Selection Parameters (report SD, complete intercorrelations)

Correlations (K=2,257)

Measures 1 2 3 4 5 6 7 8 9 10

1. Word 1.0 .43 .42 .69 .42 .38 .41 .78 .37 .74

2. Phonol. 1.0 .36 .52 .28 .42 .33 .52 .30 .49

3. RAN 1.0 .53 .36 .26 .41 .53 .27 .60

4. Pseudo word 1.0 .63 .34 .52 .77 .54 .67

5. Intelligence 1.0 .42 .54 .70 .45 .68

6. Vocabulary 1.0 .34 .58 .39 .44

7. Ortho/homo. 1.0 .64 .38 .61

8. Spelling 1.0 .53 .80

9. Memory 1.0 .48

10 Reading comp. 1.0

Note. Phon.=Phonological awareness,Ortho/homo=Orthography/homophones, Reading comp.=Reading

comprehension

Table 4

Estimated Intercorrelations Among Cognitive Measures

Conclusions

1. Predictions of real word reading—No clear advantages for PA and RAN

when compared with other variables2. 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

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 scores4. Reported measures independent of

classification measures5. 52 studies met full inclusion criteria—

Table 1

Psychological and Achievement Profiles on Standardized Normed Referenced Measures for Adult Participants with and Without Reading Disabilities

 

Chronological Age Matched (N=1162) Reading Disabled (N=1719) Effect Size

Studies M SD     M SD   M SD

Norm-Referenced  

Read. Comp. 33 109.87 11.29 93.05 12.29 1.25 0.73

General Intell. 46 110.55 6.89 104.64 11.62 0.26 0.67

Verbal Intelligence 19 110.6 9 101.36 12.63 0.69 0.61

Word Recognition 30 107.19 8.24 88.65 10.16 1.64 0.79

Table 2

Weighted Effect Sizes, Standard Error, Confidence Intervals and Homogeneity of Categories for Comparisons between Adults with and without RD (corrected for outliers).

Comparison K Effect Size Standard Error Lower Upper

Total Across Categories

RD/NRD 776 0.54 0.01 0.52 0.56

1. Reading comprehension

RD/NRD 53 1.20 0.04 1.12 1.28

2. General Intelligence

RD/NRD 48 0.20 0.03 0.13 0.28

2.1 Verbal Intelligence

RD/NRD 20 0.63 0.05 0.5 0.74

3.0 Reading Recognition

RD/NRD 43 1.37 0.04 1.28 1.44

Table 2

Weighted Effect Sizes, Standard Error, Confidence Intervals and Homogeneity of Categories for Comparisons between Adults with and without RD (corrected for outliers).

Comparison K Effect Size Standard Error Lower Upper Homogeneity Q

4.0 Speed of Processing (e.g., letter naming, etc)

RD/NRD 56 0.96 0.03 0.88 1.04 184.19***

5. Phonological Processing

RD/NRD 42 0.87 0.05 0.77 0.98 199.08***

6.0 Word Attack

RD/NRD 55 1.33 0.03 1.25 1.41 284.18***

7.0 Math

RD/NRD 32 0.75 0.03 0.68 0.83 189.19***

8.0 Vocabulary

RD/NRD 29 0.71 0.04 0.62 0.8 163.52***

9.0 Spelling

RD/NRD 33 1.57 0.05 1.47 1.67 258.25***

10.0 Writing

RD/NRD 11 0.72 0.07 0.58 0.86 162.18***

Table 2

Weighted Effect Sizes, Standard Error, Confidence Intervals and Homogeneity of Categories for Comparisons between Adults with and without RD (corrected for outliers).

Comparison K Effect Size Standard Error Lower Upper

11.0 Social and Personal Skills

RD/NRD 34 0.10 0.03 0.02 0.17

12.0 Problem Solving and Reasoning

RD/NRD 38 0.11 0.04 0.03 0.2

13.0 Verbal Memory

RD/NRD 44 0.62 0.04 0.53 0.71

13.1 Visual-Spatial memory

RD/NRD 6 -0.39 0.12 -0.63 -0.14

13.2 Cognitive monitoring

RD/NRD 19 0.27 0.06 0.15 0.39

Table 2        Weighted Effect Sizes, Standard Error, Confidence Intervals and Homogeneity of Categories for Comparisons between Adults with and without RD (corrected for outliers).

Comparison KEffect Size SE Lower Upper

14.0 Perceptual Motor Skills

RD/NRD 66 -0.13 0.03 -0.19 -0.07

14.1 Auditory Perceptual

RD/NRD 27 -0.18 0.06 -0.31 -0.06

14.2 Visual Perceptual

RD/NRD 14 0.13 0.11 -0.09 0.35

15. General Information (LTM)

RD/NRD 9 0.47 0.08 0.31 0.64

16. External Criterion

RD/NRD 11 -0.23 0.05 -0.33 -0.12

17.0 Personality

RD/NRD 16 0.28 0.04 0.19 0.37

Note. NRD = non reading disabled-average achiever, RD = reading disabled; ; K = number of measures, Lower and Upper = 95% level of confidence range. a Positive effect sizes favor NRD and negative effect sizes favor RD group

Table 1

Psychological and Achievement Profiles on Standardized Normed Referenced Measures for Adult Participants with and Without Reading Disabilities

 

Chronological Age Matched (N=1162) Reading Disabled (N=1719) Effect Size

K M SD     M SD   M SD

Fluency/RAN 15 105.93 6.36 88.72 16.4 1.01 0.65

Phonol. Processing 8 105.48 24.03 76.26 16.96 1.6 0.68

Word Attack 21 105.82 8.23 87.17 11.88 1.68 0.72

Math 14 106.23 8.71 93.64 10.31 0.88 0.82

Vocabulary 17 104.89 7.39 92.3 11.28 0.88 0.649

Spelling 20 107.89 7.02 87.62 9.88 1.77 0.66

Writing 8 101.94 7.95 88.15 11.07 0.81 1.1

Problem solving/reasoninga 29 11.94 1.88 11.32 1.7 0.04 0.3

Memory-Verbalb 21 9.99 3.38 8.13 2.21 0.81 0.8

                 

RD vs. Slow Learners: More Alike than Different?

Big Question

Is IQ completely irrelevant in separating various reading groups??

Research Questions

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

1. 20year period—must include comparison of Discrepancy and Non Discrepancy groups

2. Criterion measure was reading recognition3 Must report Standardized Intelligence and

Reading Measures4. Published in a refereed journal-English69 potential articles—19 met criteria-274 effect sizes Mean ES .21 (SD=.65)

Table 1Age and Psychometric Characteristics of Children with RD and Low Achievers

VariableRD Group Mean

RD GroupSD

LA Group Mean

LA GroupSD

Age 111.05 33.34 110.92 33.48

Word Recognition 79.82 5.75 84.09 5.72

Verbal Intelligence 99.46 4.79 83.64 4.91

Magnitude of Effect Size by Category of Dependent Measure.

Category of dependent measure

K Mean Hedge’s

g

SD Range Q

Phonological processing:

Phonological processing

34 .27 .50 -.67 to 1.36 117.19**

Pseudo-word reading

18 .29 .39 -.50 to 1.01 25.98*

Real-word phonetic analysis

26 -.02 .52 -1.44 to 1.05 61.09**

Automaticity 55 .05 .45 -1.21 to .85 93.11**

Spelling 8 .19 .43 -.34 to .93 14.32*

Memory 59 .12 .89 -3.56 to 1.24 159.07**

Syntactical knowledge

11 .87 .24 .55 to 1.29 5.47

Lexical knowledge 17 .55 .63 -.50 to 1.85 47.74**

Visual Spatial Reasoning:

Visual-motor skills 9 .15 .80 -1.36 to 1.29 54.57**

Spatial processing 37 .36 .67 -1.36 to 1.85 150.45**

Conclusions

Verbal IQ and Age moderate the overall level of cognitive performance.—

This conclusion is different than saying IQ is irrelevant

Overall Conclusions

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?

Validating a Science Based Model of Learning Disabilities

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 1-3Step 1a Select children who have average intelligence, score below the 25th percentile in reading or math and been provided intense instruction but show limited growth in achievement

Step 1b Select a parsimonious domain embedded within a model of learning (e.g., Reading, Mathematics).

Step2 Select tasks that both represent the domain (e.g., working memory) and are sensitive to individual differences in learning (construct validity).

Step 3 Determine the locus of ability group differences on those tasks.

Step 4Step 4: Delineate the cognitive processes that

underlies ability group performance.

a. Relate process measures with ability differences in academic functioning

b. Determine if process measures account for the major variance in academic performance

c. Determine which process measures best predict academic performance.

d. Eliminate process measures that poorly correlate with academic performance.

e. Demonstrate interaction between ability group and process manipulation

f. Partial out the effects of academic ability.

g. Determine neurological correlates between children with and without LD.

Step 5

Step 5: Categorize processing difficulties.

a. Parameter differences

b. Sequence differences

c. Route differences

d. Strategy differences

Step 6

Step 6 :Teach LD children to process as NLD children, thereby attempting to raise their performance to a level similar to their counterparts.

a. If instruction fails to induce change, move to Step 7.

b. If instruction induces change, determine if both ability groups used the same processes

c. Collect concurrent measures on classroom functioning

Step 7

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).