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

1 Citation (Scopus)

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	Blended Learning: Engaging Students in the New Normal Era: 15th International Conference, ICBL 2022, Hong Kong, China, July 19–22, 2022, Proceedings
Editors	Richard Chen LI, Simon S. K. CHEUNG, Peter H. F. NG, Leung-Pun WONG, Fu Lee WANG
Publisher	Springer Nature Switzerland AG
Chapter	14
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 - 2022
Event	15th International Conference on Blended Learning, ICBL 2022 - , Hong Kong, China Duration: 19 Jul 2022 → 22 Jul 2022

Publication series

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

Conference

Conference	15th International Conference on Blended Learning, ICBL 2022
Abbreviated title	ICBL 2022
Country/Territory	Hong Kong, China
Period	19/07/22 → 22/07/22

Bibliographical note

Publisher Copyright:
© 2022, Springer Nature Switzerland AG.

Funding

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.

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

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.), Blended Learning: Engaging Students in the New Normal Era: 15th International Conference, ICBL 2022, Hong Kong, China, July 19–22, 2022, Proceedings (pp. 157-167). (Lecture Notes in Computer Science; Vol. 13357). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-031-08939-8_14

CHEN, Xieling ; ZOU, Di ; CHENG, Gary et al. / Understanding Classroom Interaction Using Epistemic and Social Network Analysis. Blended Learning: Engaging Students in the New Normal Era: 15th International Conference, ICBL 2022, Hong Kong, China, July 19–22, 2022, Proceedings. editor / Richard Chen LI ; Simon S. K. CHEUNG ; Peter H. F. NG ; Leung-Pun WONG ; Fu Lee WANG. Springer Nature Switzerland AG, 2022. pp. 157-167 (Lecture Notes in Computer Science).

@inproceedings{f93e1ac5affa487eb1d039dc3b5361ec,

title = "Understanding Classroom Interaction Using Epistemic and Social Network Analysis",

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.",

keywords = "Classroom interaction, Epistemic network analysis, Social network analysis, Visualization",

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

note = "Publisher Copyright: {\textcopyright} 2022, Springer Nature Switzerland AG.; 15th International Conference on Blended Learning, ICBL 2022, ICBL 2022 ; Conference date: 19-07-2022 Through 22-07-2022",

year = "2022",

doi = "10.1007/978-3-031-08939-8\_14",

language = "English",

isbn = "9783031089381",

series = "Lecture Notes in Computer Science",

publisher = "Springer Nature Switzerland AG",

pages = "157--167",

editor = "LI, \{Richard Chen\} and CHEUNG, \{Simon S. K.\} and NG, \{Peter H. F.\} and Leung-Pun WONG and WANG, \{Fu Lee\}",

booktitle = "Blended Learning: Engaging Students in the New Normal Era: 15th International Conference, ICBL 2022, Hong Kong, China, July 19–22, 2022, Proceedings",

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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), Blended Learning: Engaging Students in the New Normal Era: 15th International Conference, ICBL 2022, Hong Kong, China, July 19–22, 2022, Proceedings. Lecture Notes in Computer Science, vol. 13357, Springer Nature Switzerland AG, pp. 157-167, 15th International Conference on Blended Learning, ICBL 2022, Hong Kong, China, 19/07/22. 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.
Blended Learning: Engaging Students in the New Normal Era: 15th International Conference, ICBL 2022, Hong Kong, China, July 19–22, 2022, Proceedings. ed. / Richard Chen LI; Simon S. K. CHEUNG; Peter H. F. NG; Leung-Pun WONG; Fu Lee WANG. Springer Nature Switzerland AG, 2022. p. 157-167 (Lecture Notes in Computer Science; Vol. 13357).

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

TY - GEN

T1 - Understanding Classroom Interaction Using Epistemic and Social Network Analysis

AU - CHEN, Xieling

AU - ZOU, Di

AU - CHENG, Gary

AU - XIE, Haoran

PY - 2022

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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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KW - Social network analysis

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SN - 9783031089381

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BT - Blended Learning: Engaging Students in the New Normal Era: 15th International Conference, ICBL 2022, Hong Kong, China, July 19–22, 2022, Proceedings

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A2 - CHEUNG, Simon S. K.

A2 - NG, Peter H. F.

A2 - WONG, Leung-Pun

A2 - WANG, Fu Lee

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ER -

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, Blended Learning: Engaging Students in the New Normal Era: 15th International Conference, ICBL 2022, Hong Kong, China, July 19–22, 2022, Proceedings. Springer Nature Switzerland AG. 2022. p. 157-167. (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

Conference

Bibliographical note

Funding

Keywords

UN SDGs

Access to Document

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