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The impact of generative AI on university students’ learning outcomes via Bloom’s taxonomy: a meta-analysis and pattern mining approach
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- TRV-2026-2837raw data (JSON)
- Version
- v1Published
- First published
- Evidence type
- Systematic review or meta-analysis
- Sources
- 1 sourcePeer-reviewed
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Higher education is facing a huge challenge with the development of Generative AI (GenAI). Many researchers have explored the effectiveness of GenAI in university students’ learning outcomes. However, despite its importance and the inconsistent results in existing research, a notable gap remains in systematically evaluating the impact of GenAI in higher education using a meta-analytic approach. To address this gap, this study investigates the impact of GenAI on university students’ learning outcomes through the…
The gain
A meta-analysis of studies on university students found generative AI effectively enhanced lower-order cognitive, higher-order cognitive and non-cognitive skills, framed through Bloom's Taxonomy.
What this doesn’t fix
The authors say the findings need cautious interpretation, and the positive benefits are discussed critically.
Sources
1 on file- Asia Pacific Journal of Educationdoi:10.1080/02188791.2025.2530503
Cite this record
v1Truvace Impact Record TRV-2026-2837, v1: “The impact of generative AI on university students’ learning outcomes via Bloom’s taxonomy: a meta-analysis and pattern mining approach.” Truvace, 2026-11-12. /record/TRV-2026-2837 (accessed on the day you copy it). sha256 ec2da901ecfe7dda…
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