Published 2026-08-01
Keywords
- Self-Regulated Learning, Mathematics Learning, Bibliometric Analysis
Abstract
This study aims to map the global research trends on Self-Regulated Learning (SRL) in mathematics learning during the 2016–2025 period through bibliometric analysis. The scope of the study includes publication patterns, the most frequently studied research topics, and the most productive researchers and institutions. Data were obtained from the Scopus database using the keywords “Self-Regulated Learning” AND “Mathematics Learning” in the title, abstract, and keywords fields, yielding 63 publications that were analyzed using Microsoft Excel and VOSviewer. The results indicate an overall upward trend in publications, peaking in 2024 (13 documents), and a surge in citations from 5 in 2019 to 173 in 2025. Indonesia was the most productive country with 28 publications, followed by China (9) and Hong Kong (7). Guo, W. and Wei, J. were the most productive authors, while the Australian Journal of Education recorded the highest number of citations. Keyword mapping identified four thematic clusters: learning systems, educational technology, e-learning, and learning strategies and reflection. The study’s conclusions affirm that SRL in mathematics learning is evolving toward the Technology-Enhanced Self-Regulated Learning paradigm and recommend future research exploring the integration of SRL with artificial intelligence as well as broader international research collaboration.
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