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TRUVACE RECORD VERSION
record: TRV-2026-2754
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:19:32.730251Z
status: published
lens: g_space
sector: education
headline: The Impact of Generative AI on Self-Efficacy: Evidence From a Meta-Analysis
dek: Generative artificial intelligence (genAI) tools such as ChatGPT are increasingly used in education. While many studies have examined how genAI tools affect learning, we know less about how genAI tools influence motivational factors such as learners’ self-efficacy, despite the central role self-efficacy plays in motivation and learning. We conducted a meta-analysis of experimental and quasi-experimental research to examine the effect of genAI tools on learners’ self-efficacy. Studies published between November 2…
gain_title: A meta-analysis of 84 independent effects from experimental and quasi-experimental studies found that using generative AI during learning raised learners' self-efficacy by a moderate amount, with tutor-style use producing larger gains.
problem_title: (none)
trace_subject: (none)
gain_reading: A meta-analysis of 84 independent effects from experimental and quasi-experimental studies found that using generative AI during learning raised learners' self-efficacy by a moderate amount, with tutor-style use producing larger gains.
gain_evidence: using genAI during learning improved learners’ self-efficacy with a moderate effect size | Implementations where genAI acted as a tutor that guided students’ learning produced larger improvements in self-efficacy
problem_reading: (none)
problem_evidence: (none)
quick_read: A meta-analysis of experimental and quasi-experimental research found that using generative AI tools during learning improved learners' self-efficacy, their belief in their own ability to learn, with a moderate effect size. The analysis pooled 84 independent effects from studies published between November 2022 and February 2026.

The size of the benefit depended on how the AI was used. Tutor-style implementations that guided students' learning produced larger improvements than uses where the AI only gave feedback, answered questions or replaced learner work.

Longer interventions produced stronger improvements than brief interactions. Effects did not differ across academic domains or learner age groups, which suggests the way AI is built into instruction matters more than the subject or the age of the students.
limitation: 
tag: Evidence-backed gain
key_points: The meta-analysis covered experimental and quasi-experimental studies published between November 2022 and February 2026. | It yielded 84 independent effects on learners' self-efficacy. | Generative AI use during learning improved self-efficacy with a moderate effect size. | Tutor-style AI that guided learning beat feedback-only, question-answering and work-replacing uses. | Longer interventions produced stronger improvements than brief interactions. | Gains did not differ across academic domains or learner age groups.
rundown: The researchers examined self-efficacy because it plays a central role in motivation and learning, yet most earlier work on generative AI in education looked at learning outcomes rather than motivation. They searched and screened studies systematically for experimental and quasi-experimental research on tools such as ChatGPT.

Moderator analyses showed the overall moderate gain hid differences by implementation. AI acting as a tutor that guided learning produced larger improvements than AI that only provided feedback, answered questions or replaced learner work.

The authors conclude that generative AI can support self-efficacy when used to scaffold learning and encourage active engagement, and that how it is integrated into instruction matters for designing AI-supported learning environments.
sources:
- peer_reviewed | Journal of Educational Computing Research | https://doi.org/10.1177/07356331261483943 | 2026-09-16
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