TY - JOUR
T1 - Investigating the effects of nudges to promote knowledge-sharing behaviours on MOOC forums
T2 - a mixed method design
AU - Shi, Yingnan
AU - Haller, Armin
AU - Reeson, Andrew
AU - Li, Xinghao
AU - Li, Chaojun
N1 - Publisher Copyright:
© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
PY - 2024
Y1 - 2024
N2 - Knowledge-sharing in forums is an integral part of many MOOCs (Massive Open Online Courses). However, forum usage for knowledge-sharing in MOOCs is often inadequate. This study adopts a mixed-methods approach to investigate problems behind MOOC learners’ problematic forum participation and propose real-time sharing-quality-monitoring mechanisms to mitigate the problems. We explore different designs and implementation of computerised nudges to enhance knowledge contribution, considering challenges such as vast data, user aversion to AI monitoring, and complex user interactions. Through testing graphical (Model A), numerical (Model B), and textual message (Model C) interface designs, we found that graphical and numerical designs were most effective in improving performance. However, Model C received conflicting judgments, with some users feeling controlled by the AI while others found algorithmic guidance valuable. Our findings shed light on leveraging computerised nudges for meaningful contributions and address concerns related to AI monitoring. The complex nature of user interactions, behaviours, and the abundance of data present significant challenges that require innovative approaches. This study contributes to understanding the issues in MOOC forum participation and provides insights into effective computerised nudges. We discuss directions for refining the current design, emphasising the need for more design science research in this domain.
AB - Knowledge-sharing in forums is an integral part of many MOOCs (Massive Open Online Courses). However, forum usage for knowledge-sharing in MOOCs is often inadequate. This study adopts a mixed-methods approach to investigate problems behind MOOC learners’ problematic forum participation and propose real-time sharing-quality-monitoring mechanisms to mitigate the problems. We explore different designs and implementation of computerised nudges to enhance knowledge contribution, considering challenges such as vast data, user aversion to AI monitoring, and complex user interactions. Through testing graphical (Model A), numerical (Model B), and textual message (Model C) interface designs, we found that graphical and numerical designs were most effective in improving performance. However, Model C received conflicting judgments, with some users feeling controlled by the AI while others found algorithmic guidance valuable. Our findings shed light on leveraging computerised nudges for meaningful contributions and address concerns related to AI monitoring. The complex nature of user interactions, behaviours, and the abundance of data present significant challenges that require innovative approaches. This study contributes to understanding the issues in MOOC forum participation and provides insights into effective computerised nudges. We discuss directions for refining the current design, emphasising the need for more design science research in this domain.
KW - architectures for educational technology system
KW - distance education and online learning
KW - Human–computer interface
UR - http://www.scopus.com/inward/record.url?scp=85187479537&partnerID=8YFLogxK
U2 - 10.1080/0144929X.2024.2316287
DO - 10.1080/0144929X.2024.2316287
M3 - Article
AN - SCOPUS:85187479537
SN - 0144-929X
SP - 1
EP - 12
JO - Behaviour & information technology
JF - Behaviour & information technology
M1 - 2316287
ER -