A Meta-Analysis Exploring the Effect of Worked Examples on Mathematics Performance

• In Event: Using Examples and Mistakes to Facilitate Mathematics Learning

Abstract

The current meta-analysis quantifies the average effect of worked examples on mathematics performance to assess what moderates this effect. Exclusionary coding was conducted on 8033 abstracts from published and grey literature to yield a sample of high-quality experimental and quasi-experimental work, yielding 43 articles reporting on 55 studies and 181 effect sizes. Using robust variance estimation (RVE) to account for clustered effect sizes, the average effect size of worked examples on mathematics performance outcomes was g = 0.48, p = .01. Moderators assessed included example type (correct and incorrect examples alone or in combination), pairing with self-explanation prompts, and timing of administration (i.e., practice vs. skill acquisition). Findings will inform both theory and practice.

Authors

• Christina Areizaga Barbieri, University of Delaware
  Presenting Author

• Dana Miller-Cotto, Kent State University
  Non-Presenting Author

• Sarah Clerjuste, University of Delaware
  Non-Presenting Author

• Kamal Chawla, University of Delaware
  Non-Presenting Author

• Phuc Huynh Le
  Non-Presenting Author

• Lauren DeLuca
  Non-Presenting Author

• Jenna Landy, Harvard University
  Non-Presenting Author