Unlocking the potential of artificial intelligence in improving learning achievement in blended learning: a meta-analysis

作者：Jiajun Wu, Ahmed Tlili, Soheil Salha, Daria Mizza, Mohammed Saqr, Sonsoles López‐Pernas, Ronghuai Huang · 发表于：Frontiers in Psychology · 年份：2025 · DOI：10.3389/fpsyg.2025.1691414 · 被引用次数：4 · 研究领域：Technology-Enhanced Education Studies、E-Learning and COVID-19、AI in Service Interactions

Introduction While several studies investigated the effect of blended learning on students’ learning achievement, scant information exists on whether using artificial intelligence (AI) in blended learning could further contribute to the obtained effect. Methods To effectively address the challenges and opportunities presented by blended learning and AI, the present study conducts a meta-analysis to systematically examine the impact of AI-enhanced blended learning on students’ learning achievement, considering the significant role of multiple variables in shaping this achievement, including the type of AI technology, instruction duration, research design, and sample size as well as across different educational levels and subject areas. Specifically, 21 studies ( N = 2,873 participants) were meta-analyzed. Results The obtained results revealed that AI has a medium effect ( g = 0.5) on students’ learning achievement in blended learning. Particularly, personalized systems in blended learning had the highest effect (i.e., large) compared to chatbots and intelligent tutoring systems. Finally, it is seen that the educational context (grade level and educational subject), as well as the experiment type (research design, intervention duration, and sample size), moderate the effect of AI on students’ learning achievement in blended learning. Discussion The findings of this study can help researchers and practitioners better understand the effects of AI in blended learning, thereby cont...