Author
Listed:
- Yingnan Shi
- Armin Haller
- Andrew Reeson
- Xinghao Li
- Chaojun Li
Abstract
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.
Suggested Citation
Yingnan Shi & Armin Haller & Andrew Reeson & Xinghao Li & Chaojun Li, 2025.
"Investigating the effects of nudges to promote knowledge-sharing behaviours on MOOC forums: a mixed method design,"
Behaviour and Information Technology, Taylor & Francis Journals, vol. 44(2), pages 289-314, January.
Handle:
RePEc:taf:tbitxx:v:44:y:2025:i:2:p:289-314
DOI: 10.1080/0144929X.2024.2316287
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tbitxx:v:44:y:2025:i:2:p:289-314. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tbit .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.