The Impact of AI on Learners’ Self-Efficacy: A Meta-Analysis

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Authors: Liling Ren, Jason M. Stephens, Kerry Lee
Cited by: 10
References: 54

Abstract

With the rise of generative artificial intelligence, the application of AI in learning environments has received widespread attention. Although empirical studies have explored the effect of AI on self-efficacy, the results have not been consistent. This study conducted a meta-analysis on the results from 23 empirical studies on the impact of AI use on self-efficacy. These studies were published between January 2005 and February 2025 and indexed in one or more of the three major educational research databases: Web of Science, Scopus, and ERIC. The results indicated that AI had a significant positive impact on self-efficacy in learning contexts (effect size of 0.758). Specifically, discipline (Q = 10.348, p < 0.05) and the specific role played by AI (Q = 3.991, p < 0.05) significantly moderated the effect of AI on self-efficacy. In our discussion, suggestions are provided for enhancing learner self-efficacy and improving the effectiveness of AI in the learning contexts.

Fields of Study & Subjects

AI in Service Interactions Intelligent Tutoring Systems and Adaptive Learning Technology-Enhanced Education Studies

Publication details

Journal / source
Behavioral Sciences
Publisher
MDPI AG
Volume
16
Issue
1
Pages
158–158
Publication date
22 January 2026
Language
EN