Understanding Classroom Interaction Using Epistemic and Social Network Analysis

Xieling CHEN; Di ZOU; Gary CHENG; Haoran XIE

doi:10.1007/978-3-031-08939-8_14

Understanding Classroom Interaction Using Epistemic and Social Network Analysis

Xieling CHEN, Di ZOU^*, Gary CHENG, Haoran XIE

^*Corresponding author for this work

Department of Computing and Decision Sciences

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Referred Conference Paper › peer-review

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.

Original language	English
Title of host publication	ICBL 2022: Blended Learning: Engaging Students in the New Normal Era
Editors	Richard Chen LI, Simon S. K. CHEUNG, Peter H. F. NG, Leung-Pun WONG, Fu Lee WANG
Publisher	Springer, Cham
Pages	157-167
Number of pages	11
ISBN (Electronic)	9783031089398
ISBN (Print)	9783031089381
DOIs	https://doi.org/10.1007/978-3-031-08939-8_14
Publication status	Published - 18 Jun 2022

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	13357
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Bibliographical note

Funding Information:
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.

Publisher Copyright:
© 2022, Springer Nature Switzerland AG.

Keywords

Classroom interaction
Epistemic network analysis
Social network analysis
Visualization

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-031-08939-8_14

https://link.springer.com/10.1007/978-3-031-08939-8_14

Cite this

CHEN, X., ZOU, D., CHENG, G., & XIE, H. (2022). Understanding Classroom Interaction Using Epistemic and Social Network Analysis. In R. C. LI, S. S. K. CHEUNG, P. H. F. NG, L.-P. WONG, & F. L. WANG (Eds.), ICBL 2022: Blended Learning: Engaging Students in the New Normal Era (pp. 157-167). Article Chapter 14 (Lecture Notes in Computer Science; Vol. 13357). Springer, Cham. https://doi.org/10.1007/978-3-031-08939-8_14

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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{\textquoteright} advantages in evaluating the quality of classroom interaction, instructors{\textquoteright} performance in promoting students{\textquoteright} higher-order thinking, and individual students{\textquoteright} performance in the classroom interaction. Results suggest that to promote productive classroom interaction and students{\textquoteright} 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{\textquoteright} opinions or ideas, and 4) arrange group discussion activities.",

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author = "Xieling CHEN and Di ZOU and Gary CHENG and Haoran XIE",

note = "Funding Information: 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. Publisher Copyright: {\textcopyright} 2022, Springer Nature Switzerland AG.",

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CHEN, X, ZOU, D, CHENG, G & XIE, H 2022, Understanding Classroom Interaction Using Epistemic and Social Network Analysis. in RC LI, SSK CHEUNG, PHF NG, L-P WONG & FL WANG (eds), ICBL 2022: Blended Learning: Engaging Students in the New Normal Era ., Chapter 14, Lecture Notes in Computer Science, vol. 13357, Springer, Cham, pp. 157-167. https://doi.org/10.1007/978-3-031-08939-8_14

Understanding Classroom Interaction Using Epistemic and Social Network Analysis. / CHEN, Xieling; ZOU, Di; CHENG, Gary et al.
ICBL 2022: Blended Learning: Engaging Students in the New Normal Era . ed. / Richard Chen LI; Simon S. K. CHEUNG; Peter H. F. NG; Leung-Pun WONG; Fu Lee WANG. Springer, Cham, 2022. p. 157-167 Chapter 14 (Lecture Notes in Computer Science; Vol. 13357).

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Referred Conference Paper › peer-review

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N1 - Funding Information: 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. Publisher Copyright: © 2022, Springer Nature Switzerland AG.

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N2 - 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.

AB - 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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CHEN X, ZOU D, CHENG G, XIE H. Understanding Classroom Interaction Using Epistemic and Social Network Analysis. In LI RC, CHEUNG SSK, NG PHF, WONG LP, WANG FL, editors, ICBL 2022: Blended Learning: Engaging Students in the New Normal Era . Springer, Cham. 2022. p. 157-167. Chapter 14. (Lecture Notes in Computer Science). Epub 2022 Jun 18. doi: 10.1007/978-3-031-08939-8_14

Understanding Classroom Interaction Using Epistemic and Social Network Analysis

Abstract

Publication series

Bibliographical note

Keywords

UN SDGs

Access to Document

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