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Anatomizing online collaborative inquiry using directional epistemic network analysis and trajectory tracking

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成果类型:
期刊论文
作者:
Ba, Shen;Hu, Xiao;Stein, David;Liu, Qingtang
通讯作者:
Ba, S;Hu, X
作者机构:
[Ba, Shen] Educ Univ Hong Kong, Dept Curriculum & Instruct, Hong Kong, Peoples R China.
[Hu, Xiao] Univ Hong Kong, Fac Educ, Hong Kong, Peoples R China.
[Stein, David] Ohio State Univ, Coll Educ & Human Ecol, Columbus, OH USA.
[Liu, Qingtang] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Peoples R China.
[Ba, Shen; Ba, S] Educ Univ Hong Kong, Dept Curriculum & Instruct, Tai Po, 10 Lo Ping Rd, Hong Kong, Peoples R China.
通讯机构:
[Ba, S ] E
[Hu, X ] U
Educ Univ Hong Kong, Dept Curriculum & Instruct, Tai Po, 10 Lo Ping Rd, Hong Kong, Peoples R China.
Univ Hong Kong, Fac Educ, Pokfulam, Room 209, Runme Shaw Bldg, Hong Kong, Peoples R China.
语种:
英文
关键词:
community of inquiry;epistemic network analysis;learning analytics;online discussion;trajectory tracking
期刊:
British Journal of Educational Technology
ISSN:
0007-1013
年:
2024
卷:
55
期:
5
基金类别:
Humanities and Social Science Planning Fund of the Ministry of Education, China
机构署名:
本校为其他机构
院系归属:
教育信息技术学院
摘要:
AbstractAccurate assessment and effective feedback are crucial for cultivating learners' abilities of collaborative problem‐solving and critical thinking in online inquiry‐based discussions. Based on quantitative content analysis (QCA), there has been a methodological evolvement from descriptive statistics to sequential mining and to network analysis for mining coded discourse data. Epistemic network analysis (ENA) has recently gained increasing recognition for modelling and visualizing the temporal characteristics of online discussions. Howe...

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