Inducing Self-Explanation: a Meta-Analysis

  • Kiran Bisra
  • Qing Liu
  • John C. Nesbit
  • Farimah Salimi
  • Philip H. Winne
Meta-Analysis

Abstract

Self-explanation is a process by which learners generate inferences about causal connections or conceptual relationships. A meta-analysis was conducted on research that investigated learning outcomes for participants who received self-explanation prompts while studying or solving problems. Our systematic search of relevant bibliographic databases identified 69 effect sizes (from 64 research reports) which met certain inclusion criteria. The overall weighted mean effect size using a random effects model was g = .55. We coded and analyzed 20 moderator variables including type of learning task (e.g., solving problems, studying worked problems, and studying text), subject area, level of education, type of inducement, and treatment duration. We found that self-explanation prompts are a potentially powerful intervention across a range of instructional conditions. Due to the limitations of relying on instructor-scripted prompts, we recommend that future research explore computer-generation of self-explanation prompts.

Keywords

Self-explanation Instructional explanation Meta-analysis Prompts 

Notes

Funding

This study was funded by Social Sciences and Humanities Research Council of Canada (grant number 435–2012-0723).

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

References

Articles included in the meta-analyses are marked with an asterisk

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Kiran Bisra
    • 1
  • Qing Liu
    • 1
  • John C. Nesbit
    • 1
  • Farimah Salimi
    • 1
  • Philip H. Winne
    • 1
  1. 1.Simon Fraser UniversityBurnabyCanada

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