Generative AI technologies and educational outcomes: a comprehensive meta-analysis comparing traditional and AI-driven approaches

Abstract

With the exponentially rapid development of information technologies, generative artificial intelligence (GenAI) technologies have been widely applied to various fields, including education. However, few studies have synthesized the pooled effect of GenAI on educational outcomes, which is an important research gap this study aims to address. Through the PRISMA-based meta-analysis and systematic review, this study concludes a central finding: GenAI technologies may generally outperform traditional and non-GenAI educational approaches in the improvement of educational outcomes, especially strengthening academic achievements, higher-order thinking abilities, and writing skills more effectively than non-GenAI-assisted approaches, with GenAI feedback yielding superior results as well. Although subgroup analyses regarding countries and different interventions have identified nuanced findings, the core value of the current study lies in the evidence-based, unified assessment of GenAI’s role in education, which possibly enables stakeholders to optimize AI-integrated educational strategies, effectively guides researchers to prioritize meaningful areas for further exploration, and efficiently equips policymakers to make informed decisions in educational practice. Future researchers should delve into the impact of GenAI technologies on students with disabilities and design personalized teaching strategies tailored to their needs.

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