Author
Listed:
- Rushil Raghavjee
(Discipline of Computer Science, University of KwaZulu-Natal, Pietermaritzburg 3201, South Africa)
- Prabhakar Rontala Subramaniam
(Discipline of Computer Science, University of KwaZulu-Natal, Pietermaritzburg 3201, South Africa)
- Irene Govender
(Discipline of Computer Science, University of KwaZulu-Natal, Pietermaritzburg 3201, South Africa)
Abstract
Advancements in data storage and data processing technologies has compelled higher education institutions to optimise the use of their data. Many universities globally have begun to implement learning analytics at their institutions to better understand and improve teaching and learning. African higher education institutions have been slow to implement learning analytics despite the continued accumulation of digital data. The research related to this study presents a dataset of Information Systems and Technology (IS&T) students from the University of KwaZulu-Natal, a South African university. The dataset comprises approximately 14,000 registered student records from 10 IS&T courses, primarily consisting of demographic data, academic performance (including past IS&T courses and school records), and Learning Management System (LMS) interaction data. The dataset exhibits an imbalance, characterised by a higher proportion of students who have successfully completed courses compared to those who have not. The dataset will be of interest to researchers engaged in learning analytics application studies, including early pass/fail prediction and grade classification, as well as those who want to test their techniques on a real-world dataset.
Suggested Citation
Rushil Raghavjee & Prabhakar Rontala Subramaniam & Irene Govender, 2025.
"Anonymized Dataset of Information Systems and Technology Students at a South African University for Learning Analytics,"
Data, MDPI, vol. 11(1), pages 1-11, December.
Handle:
RePEc:gam:jdataj:v:11:y:2025:i:1:p:1-:d:1822414
Download full text from publisher
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:gam:jdataj:v:11:y:2025:i:1:p:1-:d:1822414. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.