Detecting cognitive engagement in online course forums: A review of frameworks and methodologies

A key aspect of online learning in higher education involves the utilization of course discussion forums. Assessing the quality of posts, such as cognitive engagement, within online course discussion forums, and determining students’ interest and participation is challenging yet beneficial. This res...

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Main Authors: Nazmus Sakeef, M. Ali Akber Dewan, Fuhua Lin, Dharamjit Parmar
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Natural Language Processing Journal
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2949719125000226
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author Nazmus Sakeef
M. Ali Akber Dewan
Fuhua Lin
Dharamjit Parmar
author_facet Nazmus Sakeef
M. Ali Akber Dewan
Fuhua Lin
Dharamjit Parmar
author_sort Nazmus Sakeef
collection DOAJ
description A key aspect of online learning in higher education involves the utilization of course discussion forums. Assessing the quality of posts, such as cognitive engagement, within online course discussion forums, and determining students’ interest and participation is challenging yet beneficial. This research investigates existing literature on identifying the cognitive engagement of online learners through the analysis of course discussion forums. Essentially, this review examines three educational frameworks - Van Der Meijden’s Knowledge Construction in Synchronous and Asynchronous Discussion Posts (KCSA), Community of Inquiry (CoI), and Interactive, Constructive, Active, and Passive (ICAP), which have been widely used for students’ cognitive engagement detection analyzing their posts in course discussion forums. This study also examines the natural language processing and deep learning approaches employed and integrated with the above three educational frameworks in the existing literature concerning the detection of cognitive engagement in the context of online learning. The article provides recommendations for enhancing instructional design and fostering student engagement by leveraging cognitive engagement detection. This research underscores the significance of automating the identification of cognitive engagement in online learning and puts forth suggestions for future research directions.
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spelling doaj-art-fd289069f48c44d8bb7ea63a36a6a5bf2025-08-20T03:21:59ZengElsevierNatural Language Processing Journal2949-71912025-06-011110014610.1016/j.nlp.2025.100146Detecting cognitive engagement in online course forums: A review of frameworks and methodologiesNazmus Sakeef0M. Ali Akber Dewan1Fuhua Lin2Dharamjit Parmar3School of Computing and Information Systems, Faculty of Science and Technology, Athabasca University, Alberta T9S 3A3, CanadaCorresponding author.; School of Computing and Information Systems, Faculty of Science and Technology, Athabasca University, Alberta T9S 3A3, CanadaSchool of Computing and Information Systems, Faculty of Science and Technology, Athabasca University, Alberta T9S 3A3, CanadaSchool of Computing and Information Systems, Faculty of Science and Technology, Athabasca University, Alberta T9S 3A3, CanadaA key aspect of online learning in higher education involves the utilization of course discussion forums. Assessing the quality of posts, such as cognitive engagement, within online course discussion forums, and determining students’ interest and participation is challenging yet beneficial. This research investigates existing literature on identifying the cognitive engagement of online learners through the analysis of course discussion forums. Essentially, this review examines three educational frameworks - Van Der Meijden’s Knowledge Construction in Synchronous and Asynchronous Discussion Posts (KCSA), Community of Inquiry (CoI), and Interactive, Constructive, Active, and Passive (ICAP), which have been widely used for students’ cognitive engagement detection analyzing their posts in course discussion forums. This study also examines the natural language processing and deep learning approaches employed and integrated with the above three educational frameworks in the existing literature concerning the detection of cognitive engagement in the context of online learning. The article provides recommendations for enhancing instructional design and fostering student engagement by leveraging cognitive engagement detection. This research underscores the significance of automating the identification of cognitive engagement in online learning and puts forth suggestions for future research directions.http://www.sciencedirect.com/science/article/pii/S2949719125000226Online learningCognitive engagement detectionICAPCoIKCSACourse forum analysis
spellingShingle Nazmus Sakeef
M. Ali Akber Dewan
Fuhua Lin
Dharamjit Parmar
Detecting cognitive engagement in online course forums: A review of frameworks and methodologies
Natural Language Processing Journal
Online learning
Cognitive engagement detection
ICAP
CoI
KCSA
Course forum analysis
title Detecting cognitive engagement in online course forums: A review of frameworks and methodologies
title_full Detecting cognitive engagement in online course forums: A review of frameworks and methodologies
title_fullStr Detecting cognitive engagement in online course forums: A review of frameworks and methodologies
title_full_unstemmed Detecting cognitive engagement in online course forums: A review of frameworks and methodologies
title_short Detecting cognitive engagement in online course forums: A review of frameworks and methodologies
title_sort detecting cognitive engagement in online course forums a review of frameworks and methodologies
topic Online learning
Cognitive engagement detection
ICAP
CoI
KCSA
Course forum analysis
url http://www.sciencedirect.com/science/article/pii/S2949719125000226
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AT dharamjitparmar detectingcognitiveengagementinonlinecourseforumsareviewofframeworksandmethodologies