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Game-based self-regulated language learning: Theoretical analysis and bibliometrics
Ruofei Zhang1, Gary Cheng2, Xieling Chen2
1Department of English Language Education, The Education University of Hong Kong, Hong Kong SAR, China.
Plos One
|December 16, 2020
Summary
Game-based self-regulated language learning (GBSRLL) integrates game-based and self-regulated learning. This new field shows promise, with research focusing on strategies, affective states, and game features.
Area of Science:
- Education
- Computer Science
- Psychology
Background:
- Game-based learning and self-regulated learning are established effective methods in language education.
- Limited research exists on the integration of these two approaches, termed game-based self-regulated language learning (GBSRLL).
Purpose of the Study:
- To conceptualize game-based self-regulated language learning (GBSRLL).
- To analyze the emerging interdisciplinary field of GBSRLL by examining existing research.
Main Methods:
- Theoretical analysis of relevant literature.
- Thematic evolution analysis of research articles.
- Social network analysis of publications in game-based language learning and self-regulated language learning.
Main Results:
- GBSRLL emerged as an interdisciplinary field between 2018-2019.
- Key research topics include self-regulated learning strategies, affective states, and game features within GBSRLL.
- The theoretical foundation links learner motivation, self-efficacy, and autonomy with GBSRLL, supported by game mechanics.
Conclusions:
- GBSRLL is a feasible and promising area for language education.
- Further research is needed on long-term academic effects and implementation tools for GBSRLL.
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