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Problem-based and project-based learning as promising frameworks for generative AI-supported education: Emerging evidence from a systematic review and three-level meta-analysis

Truvace record
TRV-2026-2757raw data (JSON)
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v1Published
First published
Evidence type
Systematic review or meta-analysis
Sources
1 sourcePeer-reviewed
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As AI advances, specifying which competencies learners will need grows harder, making it urgent to identify stable approaches for cultivating competencies that remain valuable regardless of which AI tools emerge next. Problem-based learning (PBL) and project-based learning (PjBL) may provide one suitable learning context for this: by integrating generative AI (GenAI) into authentic problem solving and meaningful production, they may help cultivate the judgment to evaluate AI outputs and the capacity to coordinat…

The gain

A meta-analysis of 22 controlled studies (66 effect sizes) found generative AI used in problem- and project-based learning raised learner outcomes by g = 0.819 overall, falling to g = 0.378 after adjusting for small-study effects.

What this doesn’t fix

Small-study effects suggest the unadjusted effect may be inflated, and the prediction interval for product and solution performance crossed zero, so the authors call the evidence promising but preliminary.

Sources

1 on file
  1. Acta Psychologicadoi:10.1016/j.actpsy.2026.107734
    Peer-reviewed2026-09-08

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v1

Truvace Impact Record TRV-2026-2757, v1: “Problem-based and project-based learning as promising frameworks for generative AI-supported education: Emerging evidence from a systematic review and three-level meta-analysis.” Truvace, 2026-11-12. /record/TRV-2026-2757 (accessed on the day you copy it). sha256 743b2dfdc626f2d6…

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