Abstract
This study focuses on understanding classroom interaction using epistemic and social network analysis. Based on the classroom interaction data concerning an online course named Justice with 12 episodes, we demonstrate epistemic and social network analyses’ advantages in evaluating the quality of classroom interaction, instructors’ performance in promoting students’ higher-order thinking, and individual students’ performance in the classroom interaction. Results suggest that to promote productive classroom interaction and students’ high-level cognitive contributions, instructors can 1) ask questions that explicitly require explanations, 2) encourage students to think with others, 3) encourage children to think about counterexamples or to challenge others’ opinions or ideas, and 4) arrange group discussion activities.
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Acknowledgements
The research has been supported by the Teaching Development Grant (102489) at Lingnan University, Hong Kong, the One-off Special Fund from Central and Faculty Fund in Support of Research from 2019/20 to 2021/22 (MIT02/19-20), and the Research Cluster Fund (RG 78/2019-2020R), The Education University of Hong Kong.
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Chen, X., Zou, D., Cheng, G., Xie, H. (2022). Understanding Classroom Interaction Using Epistemic and Social Network Analysis. In: Li, R.C., Cheung, S.K.S., Ng, P.H.F., Wong, LP., Wang, F.L. (eds) Blended Learning: Engaging Students in the New Normal Era. ICBL 2022. Lecture Notes in Computer Science, vol 13357. Springer, Cham. https://doi.org/10.1007/978-3-031-08939-8_14
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