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Cited by 269Online Learning and AnalyticsSentiment Analysis and Opinion MiningIntelligent Tutoring Systems and Adaptive Learning

Automated detection of emotional and cognitive engagement in MOOC discussions to predict learning achievement

Liu, Sannyuya, Liu, Shiqi, Liu, Zhi, Peng, Xian, Yang, Zongkai·2022·Computers & Education
DOI 10.1016/j.compedu.2022.104461
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Crossref · 10.1016/j.compedu.2022.104461

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7 of 7 references verified0 citation errors · 0 not checkable

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  • Leveraging use cases of LLMs in tasks such as creating knowledge representation and classifying cognitive levels could potentially facilitate transition from outcome-focused to process-focused assessments.

    “Intriguingly, leveraging the use cases of LLMs in tasks such as creating knowledge representation (Zheng et al., 2023) and classifying cognitive levels (Liu et al., 2022) could potentially facilitate the transition from outcome-focused to process-focused assessments.”

    From Practical and ethical challenges of large language models in education: A systematic scoping review (2024) · cites this paper as Liu et al., 2022

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Authors
Liu, S., Liu, S., Liu, Z., Peng, X., & Yang, Z.
Affiliations
Central China Normal University (CN)
Corresponding author
Yang, Zongkai
ORCID
Venue
Computers & Education
Publisher
Elsevier BV
Published
2022-05
Volume
181
Pages
104461
ISSN
0360-1315 (ISSN-L)
DOI
10.1016/j.compedu.2022.104461
OpenAlex
W4210820433
Cited by
269
References
7
Citations by year
2026: 43 · 2025: 95 · 2024: 62 · 2023: 54 · 2022: 15
FWCI
43.66
Type
journal article
Language
en
Open access
closed
Licence
Locations
Computers & Education (publishedVersion)
Funders
  • Natural Science Foundation of Hubei Province (2021CFB140)
  • Fundamental Research Funds for the Central Universities (30106200548, CCNU19ZN012, CCNU20TS032)
  • Ministry of Education of the People's Republic of China (21YJC880057)
  • National Natural Science Foundation of China (61937001, 61977030, 62077017, 62107016)
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
  • Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
Keywords
emotional engagement, cognitive engagement, text classification, emotion recognition, student engagement, MOOC completion rates, emotion-cognition interaction

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