research-article

Characterising Student Engagement Modes through Low-Level Activity Patterns

Authors:

Aitor Apaolaza,

Sabine Barthold,

Franziska Günther,

Markel VigoAuthors Info & Claims

UMAP '21: Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization

Pages 88 - 97

https://doi.org/10.1145/3450613.3456818

Published: 21 June 2021 Publication History

Abstract

Existing approaches to characterise engagement in online learning focus on features of the interaction of students with the learning platform including the number of posts in forums, downloads of learning materials and time spent watching videos. However, little is known about what students actually do within the learning resources and whether these activities are indicators of learning outcomes. To bridge this gap, we associate low-level activity patterns with particular student engagement modes on a connectivist MOOC (cMOOC) that ran for four weeks and involved 224 students. Our findings indicate that our approach isolates meaningful interactive behavioural markers that are indicators of engagement, and are amenable to computation.

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Cited By

Chong KIbrahim NHuspi S(2023)Multiclass Student Engagement Level Prediction using Belief-Rule Based Labelling2023 Sixth International Conference of Women in Data Science at Prince Sultan University (WiDS PSU)10.1109/WiDS-PSU57071.2023.00044(174-179)Online publication date: Mar-2023
https://doi.org/10.1109/WiDS-PSU57071.2023.00044
Yu HHarper SVigo M(2023)Modeling Search Behavior Evolution on a Specialist Search EngineIT Professional10.1109/MITP.2023.324341325:2(30-35)Online publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1109/MITP.2023.3243413
Orji FVassileva J(2022)Automatic modeling of student characteristics with interaction and physiological data using machine learning: A reviewFrontiers in Artificial Intelligence10.3389/frai.2022.10156605Online publication date: 3-Nov-2022
https://doi.org/10.3389/frai.2022.1015660

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cover image ACM Conferences

UMAP '21: Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization

June 2021

325 pages

ISBN:9781450383660

DOI:10.1145/3450613

Editors:
Judith Masthoff
Utrecht University, The Netherlands and University of Aberdeen, UK
,
Eelco Herder
Radboud University, The Netherlands
,
Nava Tintarev
University of Maastricht, The Netherlands
,
Marko Tkalčič
University of Primorska, Slovenia

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Published: 21 June 2021

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UMAP '21: 29th ACM Conference on User Modeling, Adaptation and Personalization

June 21 - 25, 2021

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Cited By

Chong KIbrahim NHuspi S(2023)Multiclass Student Engagement Level Prediction using Belief-Rule Based Labelling2023 Sixth International Conference of Women in Data Science at Prince Sultan University (WiDS PSU)10.1109/WiDS-PSU57071.2023.00044(174-179)Online publication date: Mar-2023
https://doi.org/10.1109/WiDS-PSU57071.2023.00044
Yu HHarper SVigo M(2023)Modeling Search Behavior Evolution on a Specialist Search EngineIT Professional10.1109/MITP.2023.324341325:2(30-35)Online publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1109/MITP.2023.3243413
Orji FVassileva J(2022)Automatic modeling of student characteristics with interaction and physiological data using machine learning: A reviewFrontiers in Artificial Intelligence10.3389/frai.2022.10156605Online publication date: 3-Nov-2022
https://doi.org/10.3389/frai.2022.1015660

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