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TRUVACE RECORD VERSION
record: TRV-2026-2809
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:27:03.237523Z
status: published
lens: g_space
sector: education
headline: The effectiveness of artificial intelligence on learning achievement and learning perception: A meta-analysis
dek: Recently, artificial intelligence (AI) technologies have been widely used in the field of education, and artificial intelligence in education (AIEd) has gained increasing attention. However, no quantitative meta-analysis has been conducted on the overall effectiveness of AI on learning achievement and learning perception. To close this research gap, this study conducted a comprehensive meta-analysis of the effects of AI on learning achievement and learning perception. The present meta-analysis synthesized 24 art…
gain_title: A meta-analysis of 24 studies with 2,908 participants from 2001 to 2020 found AI had a high effect size on learning achievement and a small effect size on learning perception.
problem_title: (none)
trace_subject: (none)
gain_reading: A meta-analysis of 24 studies with 2,908 participants from 2001 to 2020 found AI had a high effect size on learning achievement and a small effect size on learning perception.
gain_evidence: AI had a high effect size on learning achievement and a small effect size on learning perception
problem_reading: (none)
problem_evidence: (none)
quick_read: A meta-analysis pooled 24 articles published between 2001 and 2020, covering 2,908 participants, to test how AI in education affects learning. It found a high effect size on learning achievement and only a small effect size on how learners perceived their learning.

The authors say no earlier quantitative meta-analysis had covered the overall effect of AI on both outcomes. The work therefore gives a first pooled estimate for the field, though it rests on a modest number of studies.

Effects were not uniform. Sample size, sample level, learning domains, types of organization, roles of AI and hardware significantly moderated how well AI worked.
limitation: 
tag: Evidence-backed gain
key_points: The meta-analysis synthesized 24 articles with 2,908 participants, published from 2001 to 2020. | AI had a high effect size on learning achievement. | AI had only a small effect size on learning perception. | Thirteen moderator variables were analyzed, including sample level, learning domain, research design, intervention duration and AI technologies. | Sample size, sample level, learning domains, types of organization, roles of AI and hardware significantly moderated effectiveness.
rundown: The authors say that despite wide use of AI in education, no quantitative meta-analysis had examined its overall effect on learning achievement and learning perception. They pooled 24 articles with 2,908 participants from 2001 to 2020 to fill that gap.

The pooled results show a high effect size for achievement but a small one for perception. The analysis also tested 13 moderators, covering sample levels, learning methods, research design, research settings, intervention duration, role of AI, areas of AI application, AI software, AI hardware and AI technologies.

Six of those moderators made a significant difference: sample size, sample level, learning domains, types of organization for treatment, roles of AI and hardware.
sources:
- peer_reviewed | Interactive Learning Environments | https://doi.org/10.1080/10494820.2021.2015693 | 2021-12-19
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