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Title: Metacognition research in education : topic modeling and bibliometrics
Authors: Chen, X
Li, X
Zou, D 
Xie, H
Wang, FL
Issue Date: Jun-2025
Source: Educational technology research & development, June 2025, v. 73, no. 3, p. 1399–1427
Abstract: Metacognition, which involves the deliberate awareness and analysis of one’s own learning and thought processes, has gained significant traction among educational researchers. The burgeoning volume of metacognition studies underscores the importance of examining its current status and evolving trends. Leveraging topic modeling and bibliometrics on a dataset comprising 2568 papers spanning from 2000 to 2023, this study seeks to address questions like “What are the prevailing research themes in metacognition?” and “How has the level of research attention to these themes evolved over time?” This study also scrutinizes major journals, countries/regions, academic institutions, and collaborative networks, presenting a visual representation of their interconnections. Considering the analyses conducted, this study proffers several recommendations for the future of metacognition research. Firstly, it suggests the integration of metacognitive instruction, assessment, and feedback mechanisms into various educational domains, encompassing design, healthcare, language, teacher training, as well as special and early childhood education. Secondly, it advocates for the exploration and utilization of diverse metacognitive instructional strategies and analytics technologies to effectively bolster students’ metacognitive processes. Lastly, it underscores the significance of interdisciplinary collaborations between metacognition experts, educators, psychologists, computer scientists, and data scientists. Such collaborative efforts are envisioned to harness the potentials of big data and learning analytics technologies to inform pedagogical practices that nurture metacognitive skills. This study offers a comprehensive overview of metacognition research in the realm of education, shedding light on emerging trends in metacognitive instructional practices and providing valuable insights for charting the course of future investigations in this field.
Keywords: Bibliometrics
Education
Metacognition
Research topics
Topic evolution
Topic modeling
Publisher: Springer New York LLC
Journal: Educational technology research & development 
ISSN: 1042-1629
EISSN: 1556-6501
DOI: 10.1007/s11423-025-10451-8
Rights: © The Author(s) 2025
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
The following publication Chen, X., Li, X., Zou, D. et al. Metacognition research in education: topic modeling and bibliometrics. Education Tech Research Dev 73, 1399–1427 (2025) is available at https://doi.org/10.1007/s11423-025-10451-8.
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