Meta-Analysis Data on AI Tools for Student Problem-Solving

25 experimental and quasi-experimental studies provide the quantitative data for a meta-analysis on AI-based educational tools. The dataset includes sample sizes, effect size values, standard errors, and study moderators like educational stage and intervention duration. It was created by Ruxue Bai and last updated in May 2026 to support the reproducibility of the published analysis.

Use Cases

• Replicate the overall effect size analysis based on the provided effect size values and standard errors.
• Conduct moderator analysis to assess the influence of educational stage, intervention duration, and AI tool type on outcomes.
• Validate meta-analytic calculations for educational intervention studies using the systematically extracted data.

Strengths

• Data is systematically extracted from 25 published peer-reviewed articles.
• Includes essential meta-analytic variables: effect sizes, standard errors, and three study moderators.
• Explicitly supports reproducibility for the corresponding journal article's findings.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Contains only study-level summary statistics; no raw participant-level individual data are included.

Provenance

Source

Ruxue Bai via figshare

Collection Method

Systematically extracted from published peer-reviewed articles.

Freshness

Last updated 2026-05-22 10:45:17; freshness should be verified.