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Artificial Intelligence-Supported Flipped Learning and Academic Achievement: A Systematic Review and Meta-Analysis with Implications for Sustainable, Quality Education

Truvace record
TRV-2026-2764raw data (JSON)
Version
v1Published
First published
Evidence type
Systematic review or meta-analysis
Sources
1 sourcePeer-reviewed
sha256
316c0b61ee02…check it

This study meta-analyzed the incremental contribution of artificial intelligence (AI) to flipped learning on students’ academic achievement, relative to flipped learning without AI. Following a protocol registered on the Open Science Framework (OSF), systematic searches were conducted in Web of Science and Scopus, supplemented by an ERIC search, with coverage through 25 July 2026; eligible studies used experimental or quasi-experimental designs comparing an AI-supported flipped condition with a matched non-AI fl…

The gain

A meta-analysis of ten experimental studies (937 learners) found students in AI-supported flipped classes scored higher on achievement than those in flipped classes without AI (Hedges' g = 0.67, 95% CI 0.32 to 1.02).

What this doesn’t fix

The evidence base is small (ten studies) and varied, with a significant small-study effect; the estimate fell to g = 0.53 when the smallest studies were excluded, and overall certainty was rated low.

Sources

1 on file
  1. Sustainabilitydoi:10.3390/su18178715
    Peer-reviewed2026-08-25

What the review found when it combined the studies

These are the review’s own pooled results, copied from its abstract. Truvace did not recalculate them.

  • Student academic achievement with AI-supported flipped learning compared with flipped learning without AI

    Hedges' g 0.67 (95% CI 0.32 to 1.02)

    937 people · search to 25 July 2026

    The review’s own words
    Using Hedges’ g in a random-effects model (REML with the Knapp–Hartung adjustment), the pooled effect was positive, moderate and statistically significant: g = 0.67, 95% CI [0.32, 1.02], t(9) = 4.36, p = 0.002.

Code checks every number above against the review’s text before it is shown. The short labels are an AI model’s reading of that text, so the review’s own sentence sits under each one. A pooled figure is only as strong as the studies behind it. How Truvace uses pooled results

Cite this record

v1

Truvace Impact Record TRV-2026-2764, v1: “Artificial Intelligence-Supported Flipped Learning and Academic Achievement: A Systematic Review and Meta-Analysis with Implications for Sustainable, Quality Education.” Truvace, 2026-11-12. /record/TRV-2026-2764 (accessed on the day you copy it). sha256 316c0b61ee02f127…

Change history

1 version

Every change made to this record since it was first published, and why. Nothing has changed since it went up.

  1. Publishedv1316c0b61ee02…

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