Effectiveness of blended learning on students’ learning performance: a meta-analysis

Abstract

Blended learning (BL) has become a significant way to promote education reform and development. However, the effectiveness of BL on students’ learning is questioned, and some pedagogy and course design issues also need to be clarified. This meta-analysis investigated the effects of BL while also examining whether eleven moderators would affect BL’s effects. A total of 133 empirical studies consisting of 18,464 participants were identified. The results showed that BL had an upper-medium effect on students’ learning performance (Hedges’ g = 0.651, p < 0.001). Further, moderator analyses showed that the teaching method, proportion of online learning, type of online interaction, region, and publication year had moderating effects. These new findings can improve BL. Finally, the impacts of BL and moderators were discussed, and the implications, limitations, and future directions were provided.

Keywords:

• Blended learning
• online learning
• learning performance
• meta-analysis

Acknowledgements

Thanks to Dr. Yu Li for her suggestions on this article. We are very grateful to the editors and three reviewers for their useful and constructive comments on our work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data will be made available from the corresponding author on reasonable request.

Additional information

Funding

This research was supported by grants from the National Education Sciences Planning General Project: Construction and Application Research of Human-Computer Collaborative Diagnostic Model for Classroom Teaching Video Analysis [grant number BHA230123].

Notes on contributors

Qing Yu

Qing Yu is a PhD student at the Institute of Higher Education, Fudan University, Shanghai, China. His research interests include AI in education, blended learning, teacher education, technology-enhanced learning, family education, educational management, and student learning and development.

Kun Yu

Kun Yu is a graduate student at the School of Social Development and Public Policy, Fudan University, Shanghai, China. His research interests include computer-assisted learning, online learning, family education, and student learning and development.

Baomin Li

Baomin Li is a Professor at the Faculty of Education, East China Normal University, Shanghai, China. Her research interests include intelligent education, teacher education and professional development, classroom teaching research, blended learning, and online education.

Qiyun Wang

Qiyun Wang is an Associate Professor at the National Institute of Education, Nanyang Technological University, Singapore. His research interests include blended synchronous learning, online learning, technology-supported learning environment, and education design-based research.