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Exploring the Impact of Generative AI-Powered Conversational Agents on Student Learning: A Systematic Review and Meta-Analysis Grounded in Activity Theory

2026·0 Zitationen·Journal of Educational Computing Research
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4

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2026

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Abstract

Grounded in activity theory, this study conducted a systematic review and meta-analysis, following PRISMA guidelines, to evaluate the impact of generative AI-powered conversational agents on students’ learning outcomes in both cognitive and non-cognitive skills. Twenty-seven empirical studies published between 2022 and 2025 were analyzed. The results revealed that generative AI-powered conversational agents had moderately positive effects on both cognitive ( g = 0.462, p < .001) and non-cognitive skills ( g = 0.519, p < .001). Moderator analyses identified several contextual variables—educational levels, knowledge types, intervention durations, agent roles, and instructional modes—as significant or marginally significant. These findings offer practical implications for educators, developers, and researchers, aiming to enhance the effectiveness of generative AI-powered conversational agents in improving learning outcomes in educational settings.

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