Detecting and visualizing research trends of blended learning: A bibliometric analysis of studies from 2013-2022
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1 Department of Mathematics and Information Technology, Education University of Hong Kong, Hong Kong SAR, CHINA2 Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, CHINA3 Department of Curriculum and Instruction, Education University of Hong Kong, Hong Kong SAR, CHINA* Corresponding Author
Abstract
Blended learning (BL), an innovative, technology-supported pedagogical approach, has been extensively adopted in schools and universities. The learning effectiveness of BL has been investigated in multiple domains of education, computer science, nursing, engineering, and psychology. To uncover the major trends of BL research, this study embarked on a bibliometric analysis of a total of 719 studies published in the recent 10 years (2013-2022) and indexed in the Web of Science core collection. Adopting a quantitative approach and the visual analytical tool of CiteSpace, the review study identified the development trends, the influential researchers and research institutions, and pivotal studies and topics of the field and informed its future progression. The findings revealed a growing trend in BL research in the past decade as reflected in the exponential growth in the number of publications and citations. Charles R. Graham, Chang Zhu, Robert A. Ellis, and Feifei Han were the most prolific, influential researchers in the field, and the Griffith University, the University of Hong Kong, the Vrije Universiteit Brussel, the Monash University, and the National Taiwan Normal University were the prominent research institutions, which engaged in frequent collaborations with others. The United States, China, and Australia were the top-3 contributors to BL research measured by the number of publications, and the studies conducted and reported by researchers in the USA, Turkey, Taiwan, and Spain were cited the most often. Document co-citation analysis unveiled the pivotal studies and topics of the research field, including blended course designs, institutional adoption, achievement, higher education, active BL, flipped classroom, and communication skills.
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Article Type: Review Article
EURASIA J Math Sci Tech Ed, Volume 19, Issue 10, October 2023, Article No: em2336
https://doi.org/10.29333/ejmste/13592
Publication date: 01 Oct 2023
Online publication date: 20 Aug 2023
Article Views: 1791
Article Downloads: 1251
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How to cite this article
APA
Chen, H., Sun, D., Yang, Y., Looi, C.-K., & Jia, F. (2023). Detecting and visualizing research trends of blended learning: A bibliometric analysis of studies from 2013-2022. Eurasia Journal of Mathematics, Science and Technology Education, 19(10), em2336. https://doi.org/10.29333/ejmste/13592
Vancouver
Chen H, Sun D, Yang Y, Looi CK, Jia F. Detecting and visualizing research trends of blended learning: A bibliometric analysis of studies from 2013-2022. EURASIA J Math Sci Tech Ed. 2023;19(10):em2336. https://doi.org/10.29333/ejmste/13592
AMA
Chen H, Sun D, Yang Y, Looi CK, Jia F. Detecting and visualizing research trends of blended learning: A bibliometric analysis of studies from 2013-2022. EURASIA J Math Sci Tech Ed. 2023;19(10), em2336. https://doi.org/10.29333/ejmste/13592
Chicago
Chen, Huie, Daner Sun, Yuqin Yang, Chee-Kit Looi, and Fenglin Jia. "Detecting and visualizing research trends of blended learning: A bibliometric analysis of studies from 2013-2022". Eurasia Journal of Mathematics, Science and Technology Education 2023 19 no. 10 (2023): em2336. https://doi.org/10.29333/ejmste/13592
Harvard
Chen, H., Sun, D., Yang, Y., Looi, C.-K., and Jia, F. (2023). Detecting and visualizing research trends of blended learning: A bibliometric analysis of studies from 2013-2022. Eurasia Journal of Mathematics, Science and Technology Education, 19(10), em2336. https://doi.org/10.29333/ejmste/13592
MLA
Chen, Huie et al. "Detecting and visualizing research trends of blended learning: A bibliometric analysis of studies from 2013-2022". Eurasia Journal of Mathematics, Science and Technology Education, vol. 19, no. 10, 2023, em2336. https://doi.org/10.29333/ejmste/13592