Year: 2026
Type: review
Study designs: Systematic Review, Meta-Analysis
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.
Source: Behavioral Sciences
DOI: 10.3390/bs16010158
Authors: Liling Ren, Jason M. Stephens, Kerry Lee
Institution: University of Auckland
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $2,654
OpenAlex ID: W7125519850