metafor (version 1.9-2)

dat.bangertdrowns2004: Studies on the Effectiveness of Writing-to-Learn Interventions

Description

Results from 48 studies on the effectiveness of school-based writing-to-learn interventions on academic achievement.

Usage

dat.bangertdrowns2004

format

The data frame contains the following columns: lll{ id numeric study number author character study author(s) year numeric publication year grade numeric grade level (1 = elementary; 2 = middle; 3 = high-school; 4 = college) length numeric treatment length (in weeks) minutes numeric minutes per assignment wic numeric writing in class (0 = no; 1 = yes) feedback numeric feedback (0 = no; 1 = yes) info numeric writing contained informational components (0 = no; 1 = yes) pers numeric writing contained personal components (0 = no; 1 = yes) imag numeric writing contained imaginative components (0 = no; 1 = yes) meta numeric prompts for metacognitive reflection (0 = no; 1 = yes) subject character subject matter ni numeric total sample size of the study yi numeric standardized mean difference vi numeric corresponding sampling variance }

source

Bangert-Drowns, R. L., Hurley, M. M., & Wilkinson, B. (2004). The effects of school-based writing-to-learn interventions on academic achievement: A meta-analysis. Review of Educational Research, 74, 29--58.

Details

In each of the studies included in this meta-analysis, an experimental group (i.e., a group of students that received instruction with increased emphasis on writing tasks) was compared against a control group (i.e., a group of students that received conventional instruction) with respect to some content-related measure of academic achievement (e.g., final grade, an exam/quiz/test score). The effect size measure for this meta-analysis was the standardized mean difference (with positive scores indicating a higher mean level of academic achievement in the intervention group). The standardized mean differences given here are bias-corrected and therefore differ slighty from the values reported in the article. Also, since only the total sample size is given in the article, the estimated sampling variances were computed under the assumption that $n_{i1} = n_{i2} = n_i / 2$.

Examples

### load data
data(dat.bangertdrowns2004)

### random-effects model
res <- rma(yi, vi, data=dat.bangertdrowns2004)
res