Facilitating Students’ Emotional Engagement in Synchronous Online Learning: A Systematic Literature Review

Tu, Yaxin; Wang, Qiyun; Huang, Changqin

doi:https://doi.org/10.19173/irrodl.v26i1.7732

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Abstract

Learners’ emotional engagement in synchronous online learning (SOL) is critical for improving learning persistence and performance. Nevertheless, there is currently a lack of comprehensive and systematic reviews of emotional engagement in SOL. This review synthesizes the strategies to promote emotional engagement in SOL found in published empirical studies. A total of 32 articles were systematically analyzed by following the grounded theory approach. The primary themes were grouped into four categories: (a) instructor actions (e.g., interacting informally before and after class, encouraging the expression of ideas), (b) learner behaviors (e.g., building rapport with peers, recognizing individual accountability), (c) environment characteristics (e.g., creating a supportive atmosphere, selecting communication modes), and (d) activity design (e.g., using breakout rooms, embedding diverse elements). These findings offer comprehensive understanding and guidance for promoting emotional engagement in SOL for instructors, researchers, and course developers.

Keywords:

synchronous learning,
emotional engagement,
online learning,
strategies,
technology

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Biographical notes

Yaxin Tu is currently pursuing a PhD degree with the College of Teacher Education, Zhejiang Normal University, Jinhua, China. Her research interests include intelligent technology in education, and online learning intervention.

Qiyun Wang is currently a tenured Associate Professor at the Department of Learning Sciences and Assessment, National Institute of Education, Nanyang Technological University, Singapore. His research interests include blended synchronous learning, learner engagement in online learning, online learning environment design, and design-based research.

Changqin Huang is currently a Distinguished Professor at Zhejiang Normal University, Jinhua, China. His research interests include big data in education, machine learning, and intelligent service computing. He serves as an Associate Editor for the IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES and an active reviewer for a number of conferences and journals.

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