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MOOC-BERT: Automatically Identifying Learner Cognitive Presence from MOOC Discussion Data

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成果类型:
期刊论文
作者:
Liu, Zhi;Kong, Xi;Chen, Hao;Liu, Sannyuya;Yang, Zongkai
通讯作者:
Kong, X
作者机构:
[Yang, Zongkai; Liu, Sannyuya; Kong, Xi; Liu, Zhi; Kong, X; Chen, Hao] Cent China Normal Univ, Natl Engn Res Ctr Elearning, Natl Engn Lab Educ Big Data, Wuhan 430079, Peoples R China.
通讯机构:
[Kong, X ] C
Cent China Normal Univ, Natl Engn Res Ctr Elearning, Natl Engn Lab Educ Big Data, Wuhan 430079, Peoples R China.
语种:
英文
关键词:
Cognitive presence identification;community of inquiry model;MOOC-BERT;online discussions;pretrained language model;text analysis
期刊:
IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES
ISSN:
1939-1382
年:
2023
卷:
16
期:
4
页码:
528-542
基金类别:
This work was supported in part by the National Natural Science Foundation of China under Grant 62077017, Grant 61977030, Grant 61937001, and Grant 62007020, and in part by the Fundamental Research Funds for the Central Universities under Grant CCNU22LJ005
机构署名:
本校为第一且通讯机构
院系归属:
国家数字化学习工程技术研究中心
摘要:
In a massive open online courses (MOOCs) learning environment, it is essential to understand students' social knowledge constructs and critical thinking for instructors to design intervention strategies. The development of social knowledge constructs and critical thinking can be represented by cognitive presence, which is a primary component of the community of inquiry model. However, identifying learners' cognitive presence is a challenging problem, and most researchers have performed this task using traditional machine learning methods that r...

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