Working Memory Deficits as They Relate to Academic Growth of Students with RD

Olga Jerman, Ph.D.Director of ResearchFrostig Center, Pasadena, CA

Minyi Shih, Ph.D.California State University, Los Angeles

FrostigCenter

PCRC 2010San Diego, CA

AbstractThe study investigated whether (a) growth patterns related to cognitive processing (working memory, updating, inhibition) differed in subgroups of children with reading disabilities (RD), and (b) if growth in WM (executive processing) predicted growth in other cognitive areas, such as reading and math. 81 children (ages 7 to 17) categorized as poor decoders, poor comprehenders, or average readers were administered a battery of achievement and cognitive measures for three consecutive years. HLM showed that growth in executive processing (inhibition) in children with RD constrained growth in reading and math. The results support the notion that development in the executive system underlies performance on reading and math measures.

FrostigCenter

Working Memory & Reading Working Memory is:

A system that simultaneously processes and stores information for a brief period of time

Responsible for a range of cognitive functions, such as maintaining attention, inhibiting irrelevant information, switching between different stimuli, and updating.

There are different models of working memory and different tasks to assess working memory

Dyslexia

Average intelligence; Below average score on standardized reading

measures; Scores on math tasks within average range.

FrostigCenter

Baddeley’s model of WM

Central Executive

VisuospatialSketchpad Episodic

Buffer

PhonologicalLoop

Visual Semantics LTM Language

FrostigCenter

Research Questions:

1. Does growth in the executive components of WM or WM span differ as a function of reading ability?

2. Do deficits in the executive components of WM (or WM span) constrain RD students’ growth on measures related to crystallized intelligence (reading and math)?

FrostigCenter

Methods

Participants: 73 students

Gender: 24 girls and 49 boys

Mean age 12.20; range 7.8 – 17.0

SES: middle-upper to upper class

Ethnicity: 57 Caucasian; 6 African-

American; 5 Hispanic; 5 other

FrostigCenter

Subgroups

1. Poor decoders (PD); N = 25

Reading fluency (WRAT-3) < 25th percentile

(90 SS)

Math (WRAT-3) > 80 SS

2. Poor comprehenders (PC); N = 23

Reading fluency (WRAT-3) > 25th percentile

Comprehension (WRMT) < 25th percentile

Math (WRAT-3) > 80 SS

3. Control group (C); N = 25

Reading fluency (WRAT-3) > 40th percentile

Comprehension (WRMT) > 40th percentile

Math (WRAT-3) > 80 SS

FrostigCenter

Does Growth in WM Differ As a Function of Reading Ability?

WM growth rates among Poor decoders,

Poor comprehenders, and Average

readers are comparable for the younger

students

FrostigCenter

Results of Multilevel Modelsfor Change in Sentence Span

FrostigCenter

Parameter Unconditional means

Unconditional growth

Conditional means

Conditional growth

Fixed Effects

Initial status, π0i

Intercept γ00 1.3439*** 1.3027*** 1.4469*** 1.4498***

Group 1 (PD)

γ01

-0.1091 -0.1208

Group 2 (PC)

γ02

-0.3832* -0.3817*

Rate of change, π2i

Slope γ10

0.0104*** 0.0108*** 0.0137**

Group 1 (PD)

γ11

-0.0054

Group 2 (PC)

γ12

-0.0029

Variance components Goodness-of-fit

statistics

-2ln(L) 397.9 377.1 371.5 370.6

AIC 403.9 389.1 387.5 390.6

BIC 410.9 402.8 405.8 413.5

DC

0

1

2

3

4

AGE

90 114 138 162 186 210

Students’ Performance on Sentence Span

FrostigCenter

Note: Age is given in months, WM performance presented in span scores

Younger and Older Students Across3 Waves on Sentence Span

Sentence span

0

0.5

1

1.5

2

2.5

1 2 3 4 5 6

z-s

co

res

PD

PC

Control

FrostigCenter

Do Deficits in WM Span or Executive System Constrain Growth on Measures Related to Reading and Math?

Growth in WM span did not explain any additional variance in students’ reading and math performance and did not account for the growth in these areas.

On the other hand, measures of Executive processing were found to have an important influence in children’s growth in math and reading.

FrostigCenter

Growth Models for Reading(TOWRE Real Word and Non-word Reading)

Fixed Effects Parameter Unconditional

means Unconditional

growth Conditional

means Conditional

growth

Initial status, π0i

Intercept γ00 0.3865*** 0.3181*** 0.9380*** 0.9367***

Group 1 (PD)

γ01 -1.4966*** -1.5016***

Group 2 (PC)

γ02 -0.4577* -0.4423*

DC γ03 0.3472 p=.64

Rate of change, π2i

Slope γ10 0.01557*** 0.01268*** 0.01254***

Group 1 (PD)

γ11

Group 2 (PC)

γ12

DC γ13 -9.0633 p=.66

Variance components

Goodness-of-fit statistics

-2ln(L) 332.0 286.1 242.0 241.7

AIC 338.0 298.1 258.0 261.7

BIC 344.9 311.9 276.3 284.6

FrostigCenter

Growth Models for Math(WISC-R Arithmetic Subtest)

Fixed Effects Parameter Unconditional means

Unconditional growth

Conditional means

Conditional growth

Initial status, π0i

Intercept γ00 0.4733*** 0.3344** 0.8151*** 0.8213***

Gr 1 (PD) γ01 -0.7582*** -0.778***

Gr 2 (PC) γ02 -0.7232*** -0.6878***

DC γ03 1.3970; p=.108

Rate of change, π2i

Slope γ10 0.0171*** 0.0174*** 0.0167***

Gr 1 (PD) γ11

Gr 2 (PC) γ12

DC γ13 -37.9112 p=.128

Variance components Goodness-of-fit statistics

-2ln(L) 449.2 409.0 394.4 391.8

AIC 455.2 421.0 410.4 411.8

BIC 462.2 434.8 428.7 434.7

FrostigCenter

Growth Models with Executive Activity (EA) as a Predictor of Math

Fixed Effects Parameter Based on Conditional means models for math

Initial status, π0i

Intercept γ00 0.7433*** 0.7481*** 0.6897*** 0.6767***

Gr 1 (PD) γ01 -0.5863** -0.5913** -0.5406** -0.5572**

Gr 2 (PC) γ02 -0.6804** -0.65** -0.5794** -0.5902**

EA γ03 0.1927** 1.1119** 1.1933** 1.9283***

EA*Gr1 γ04 -0.1786 -2.685*

EA*Gr2 γ05 -0.2662*

-1.5262 p=.085

Rate of change, π2i

Slope γ10 0.0166*** 0.0159*** 0.0157*** 0.0167***

Gr 1 (PD) γ11

Gr 2 (PC) γ12

EA γ13 -80.1154* -74.7292* -140.36**

EA*Gr1 γ14 212.01*

EA*Gr2 γ15 111.11 p=.15

Variance components Goodness-of-fit statistics

-2ln(L) 385.5 380.1 375.8 370.2

AIC 403.5 400.1 339.8 398.2

BIC 424.1 423.0 427.3 430.2

FrostigCenter

Growth Models with Executive Activity (EA) as a Predictor of Reading

Fixed Effects parameter Based on Conditional means models for Reading

Initial status, π0i

Intercept γ00 .8839*** .8627*** .8642*** .9311***

Gr 1 (PD) γ01 -1.3721*** -1.3715*** -1.2673*** -1.2818***

Gr 2 (PC) γ02 -.4094* -.3823* -.3923* -.5464**

EA γ03 .1424* .3482 .4672 1.0123**

EA*gr1 γ04 .1597 -2.0265*

EA*gr2 γ05 -.0896 -1.6763* Rate of change, π2i

Slope γ10 .01214*** .01209*** .01267*** .01414***

Gr 1 (PD) γ11

Gr 2 (PC) γ12

EA γ13 -17.8989 -27.573 -82.3519**

EA*gr1 γ14 197.55**

EA*gr2 γ15 147.28*

Variance components Goodness-of-fit statistics

-2ln(L) 235.4 236.0 233.6 222.9

AIC 253.4 254.0 255.6 250.9

BIC 274.0 274.6 280.8 283.0

FrostigCenter

Conclusion

Functions of the Executive system of WM,

specifically inhibition and/or updating of the

new information, contribute significantly to

students’ reading and math growth.

Students with RD show deficits in these

areas, which constrain their ability to learn

new material, comprehend written text, and

problem-solve.

FrostigCenter

Implications Theoretical implications:

Findings suggest that specific aspects of the Central Executive, rather than general WM impairments, are deficient in RD students.

Functions of the Central Executive are critical for successful learning in school. Deficits in executive functions result in developmental lag in reading and math acquisition.

Practical implications: Modification of classroom instruction and curricular

materials: Minimize the amount of irrelevant info; reduce switching

between tasks & activities; slower pace of introducing new info (updating).

FrostigCenter