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A Bibliometric Analysis on Trends and Patterns in Self-Regulated Language Learning in Mobile-Assisted Learning Environments

A Bibliometric Analysis on Trends and Patterns in Self-Regulated Language Learning in Mobile-Assisted Learning Environments
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Author(s): Xing Wang (Universiti Malaya, Malaysia)and Zuwati Hasim (Universiti Malaya, Malaysia)
Copyright: 2024
Volume: 14
Issue: 1
Pages: 18
Source title: International Journal of Computer-Assisted Language Learning and Teaching (IJCALLT)
Editor(s)-in-Chief: Bin Zou (Xi'an Jiaotong-Liverpool University, China)and David Barr (Ulster University, United Kingdom)
DOI: 10.4018/IJCALLT.345401

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Abstract

This study analysed 498 articles published between 2005 and 2023 on Self-regulated Language Learning (SRLL) indexed in the core collection of the Web of Science database, using a bibliometric methodology based on scientific mapping, co-occurrence and burstness analysis. Results show China is the most influential contributor to SRLL research, with the largest number of total publications and citations. According to the keyword co-occurrence and burstness analysis, mobile-learning, higher education, learning context, learner strategies stand out in this field. It is also shown that listening as a significant linguistic skill is less explored in the SRLL field. It is proven that learners' language skills could be improved through mobile-assisted collaborative learning in informal settings. By identifying the developmental patterns in SRLL research, this paper can guide future researchers to explore in-depth the significant issues in this field and bring insight for further SRLL studies in terms of themes, pedagogy and methodologies.

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