Презентация на тему «Reviewing systematic reviews: meta-analysis of What Works Clearinghouse computer-assisted reading interventions»

Reviewing systematic reviews: meta-analysis of What Works

Clearinghouse computer-assisted reading interventions.

October 2012 Improving Education through Accountability and Evaluation: Lessons from Around the World Rome, Italy Andrei Streke ? Tsze Chan

Session 4.2: Building and Interpreting Scientific Evidence Thursday,

October 4th

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Presentation Overview

What Works Clearinghouse (WWC) systematic reviews Meta-analysis of computer-assisted programs across WWC topic areas, reading outcomes Meta-analysis of computer-assisted programs within Beginning Reading topic area (grades K-3)

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Key terms

What Works Clearinghouse (WWC) is a “central and trusted source of scientific evidence for what works in education.” WWC produces systematic reviews on the effectiveness of educational interventions (programs, curricula, products, and practices) grouped by topic areas. Meta-analysis is a statistical technique that summarizes quantitative findings across similar studies. Each study’s findings are converted to a standard effect size. Computer-assisted interventions encompass reading software products, and programs that combine a mix of computer activities and traditional curriculum elements.

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WWC Systematic Review

A clearly stated set of objectives with pre-defined eligibility criteria for studies An explicit reproducible methodology A systematic search that attempts to identify all studies that would meet the eligibility criteria An assessment of the validity of the findings of the included studies A systematic presentation, and synthesis, of the characteristics and findings of the studies

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Meta-Analysis of Reading interventions

Extraction of statistical and descriptive information from intervention reports and study review guides Aggregation of effect sizes across studies Moderator Analysis -- ANOVA type -- Regression type

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WWC Systematic Review

WWC products: Intervention reports http://ies.ed.gov/ncee/wwc/publications_reviews.aspx Practice guides Quick reviews Normative documents (http://ies.ed.gov/ncee/wwc ): WWC Procedures and Standards Handbook WWC topic area review protocol

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Meta-analysis of computer-assisted programs across WWC topic areas,

reading outcomes Does the evidence in WWC reports indicate that computer-assisted programs increase student reading achievement?

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Computer-assisted interventions

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Example of computer-assisted programs

Earobics® is interactive software that provides students in pre-K through third grade with individual, systematic instruction in early literacy skills as students interact with animated characters. The program builds children’s skills in phonemic awareness, auditory processing, and phonics, as well as the cognitive and language skills required for comprehension.

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Meta-Analysis procedures

Effect Sizes Aggregation Method Testing for Homogeneity Fixed and Random Effects Models Moderator Analysis -- ANOVA type -- Regression type

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Effect Size

(1) Effect size (Hedges & Olkin, 1985):

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Flowchart for calculation of effect size (Tobler et al

, 2000)

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Number of students and effect sizes by topic area

Type of Program

Number of students

Number of students

Number of students

Number of effect sizes

Number of effect sizes

total

intervention

control

Adolescent Literacy

26970

12717

14253

59

Beginning Reading

2636

1339

1297

151

Early Childhood Education

910

447

463

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English Language Learners

308

173

135

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Total

30824

14676

16148

255

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Aggregation of Effect Sizes

(1) Effect size (Hedges):

(2) Effect size variance:

Weight (w)= (Variance)-1

(3) Weighted average effect size:

(4) Weighted average effect size variance:

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Fixed and Random Effects Model weights

Fixed effects model weights each study by the inverse of the sampling variance. Random effects model weights each study by the inverse of the sampling variance plus a constant that represents the variability across the population effects (Lipsey & Wilson, 2001).

This is the random effects variance component.

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Computer-assisted programs, random effects

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0.13

0.03

0.07

0.18

4.56

0.00

33

0.28

0.06

0.16

0.40

4.71

0.00

6

0.12

0.07

-0.01

0.25

1.74

0.14

3

0.30

0.27

-0.23

0.83

1.11

0.38

WWC Topic Area

Number of Studies

Weighted Effect Size

Standard Error

Lower Confidence Interval

Upper Confidence Interval

Z-value

P-value

Adolescent literacy

Beginning reading

Early childhood education

English language learners

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Computer-assisted reading interventions, topic area effects and 95%

CIs

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Meta-analysis of computer-assisted programs within Beginning Reading

topic area Are computer-assisted reading programs more effective than non-computer reading programs in improving student reading achievement?

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Selection Criteria for Beginning Reading Topic Area

Manuscript is written in English and published 1983 or later Both published and unpublished reports are included Eligible designs: RCT; QED with statistical controls for pretest and/or a comparison group matched on pretest; regression discontinuity; SCD At least one relevant quantitative outcome measure Manuscript focuses on beginning reading Focus is on students ages 5-8 and/or in grades K-3 Primary language of instruction is English

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Beginning Reading Topic Area

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Example of “other” reading programs

Reading Recovery® is a short-term tutoring intervention intended to serve the lowest-achieving first-grade students. The goals of Reading Recovery® are to promote literacy skills, reduce the number of first-grade students who are struggling to read, and prevent long-term reading difficulties. Reading Recovery® supplements classroom teaching with one-to-one tutoring sessions, generally conducted as pull-out sessions during the school day.

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Number of students and effect sizes by type of program: Beginning

Reading topic area

Type of Program

Number of students

Number of students

Number of students

Number

total

intervention

control

of effect sizes

BR Computer-Assisted Programs

2636

1339

1297

151

Other BR Programs

7591

4042

3549

174

Total Beginning Reading

10227

5381

4846

325

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Beginning Reading programs, random effects

Type of Program

n

M

Standard Error

95% Lower

95% Upper

Z-value

P-value

Computer-assisted programs

33

0.28

0.06

0.16

0.40

4.71

0.000

Other BR programs

47

0.39

0.04

0.32

0.47

9.84

0.000

Beginning Reading Total

80

0.35

0.03

0.29

0.42

10.65

0.000

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Beginning Reading Interventions, Random Effects, 95% Confidence

Intervals

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Moderator Analysis, random effects

Modeling between study variability: Categorical models (analogous to a one-way ANOVA) Regression models (continuous variables and/or multiple variables with weighted multiple regression)

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Categorical analysis: moderators of program effectiveness

Population Design Sample size Control group Reading domain

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Weighted mean Effect Sizes for moderators: 80 studies, Beginning

Reading, random effects

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Weighted mean Effect Sizes for moderators: 80 studies, Beginning

Reading, random effects

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Dummy Variables for Regressions

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Regression Statistics for BR Programs, Random effects

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Regression Statistics for BR Programs, Random effects

Type of Program

n

M

Standard Error

95% Lower

95% Upper

Z-value

P-value

Computer-assisted programs

33

0.28

0.06

0.16

0.40

4.71

0.000

Other BR programs

47

0.39

0.04

0.32

0.47

9.84

0.000

Beginning Reading Total

80

0.35

0.03

0.29

0.42

10.65

0.000

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Regression Statistics for BR Programs, Random Effects

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Meta-Analytic Multiple Regression Results from the Wilson/Lipsey SPSS

Macro

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Conclusions

Investments in education have become an important national policy tool across the globe. With schools facing substantial costs of hardware and software, concerns naturally arise about the contribution of technology to students’ learning. The present work lends some support to the proposition that computer-assisted interventions in reading are effective. The average effect for beginning reading computer-assisted programs is positive and substantively important (that is >0.25). For the Beginning Reading topic area (grades K-3), the effect appears smaller than the effect achieved by non-computer reading programs.

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References

Borenstein, M., Hedges, L.V., Higgins, J.P., and Rothstein, H.R. (2009). Introduction to meta-analysis. John Wiley and Sons. Hedges, L. V. and Olkin I. (1985). Statistical Methods for Meta-Analysis. New York: Academic Press. Lipsey, M.W., & Wilson, D.B. (2001). Practical meta-analysis. Thousand Oaks, CA: Sage. Tobler, N.S., Roona, M.R., Ochshorn, P., Marshall, D.G., Streke, A.V., & Stackpole, K.M. (2000). School-based adolescent drug prevention programs: 1998 meta-analysis. Journal of Primary Prevention, 20(4), 275-336.

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For More Information

Please contact: Andrei Streke AStreke@mathematica-mpr.com Tsze Chan TChan@air.org

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Beginning Reading programs, random and fixed effects

Type of Program

n

M

Standard Error

95% Lower

95% Upper

Z-value

P-value

Computer-assisted programs

33

0.28

0.06

0.16

0.40

4.71

0.000

Other BR programs

47

0.39

0.04

0.32

0.47

9.84

0.000

Beginning Reading Total

80

0.35

0.03

0.29

0.42

10.65

0.000

Type of Program

n

M

Standard Error

95% Lower

95% Upper

Z-value

P-value

Computer-assisted programs

33

0.26

0.04

0.18

0.34

6.50

0.000

Other BR programs

47

0.34

0.02

0.29

0.39

14.35

0.000

Beginning Reading Total

80

0.32

0.02

0.28

0.36

15.65

0.000

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Computer-assisted programs, random and fixed effects

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Random versus Fixed Effects Models

Fixed effects model assume: (1) there is one true population effect that all studies are estimating (2) all of the variability between effect sizes is due to sampling error Random effects model assume: (1) there are multiple (i.e., a distribution) of population effects that the studies are estimating (2) variability between effect sizes is due to sampling error + variability in the population of effects (Lipsey and Wilson, 2001)

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Beginning Reading Interventions, Random Effects, 95% Confidence

Intervals

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Examples of problematic study designs that do not meet WWC criteria

Designs that confound study condition and study site Programs that were tested with only one treatment and one control classroom or school Non-comparable groups Study designs that compared struggling readers to average or good readers to test a program’s effectiveness

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