Advancing Mobile Open Learning through DigiBot technology: a case study of using WhatsApp as a scalable learning tool

Journal article


Greeff, E., Rivers, L. and Wilson, T. 2024. Advancing Mobile Open Learning through DigiBot technology: a case study of using WhatsApp as a scalable learning tool. International Journal of Teaching and Case Studies. 14 (4), pp. 393-412. https://doi.org/10.1504/IJTCS.2024.139187
AuthorsGreeff, E., Rivers, L. and Wilson, T.
Abstract

This article presents a case study that outlines the potential of DigiBot technology, an interactive automated response program, in Mobile Open Learning (MOL) for Business subjects. The study, which draws on a project implemented in Sub-Saharan Africa, demonstrates the applications of DigiBots delivered via WhatsApp to over 650,000 learners. Employing a mixed-methods approach, the article reports on live event tracking, qualitative observations from facilitators and learning technologists, and a learner survey (N=304,000). The research offers practical recommendations and proposes a model for scalable DigiBot Learning. Findings reveal that in this case, DigiBot MOL had the potential to effectively address two key obstacles in open learning: accessibility and scalability. Leveraging mobile platforms such as WhatsApp mitigates accessibility restrictions, particularly in resource-constrained contexts, while tailored micro-learning enhances scalability.

KeywordsMobile learning; DigiBot learning; WhatsApp learning; Scalability; Micro-learning; Learning technology; Micro-credentials; e-Learning; Innovative learning; Mobile open learning; Open learning; Distance learning
Year2024
JournalInternational Journal of Teaching and Case Studies
Journal citation14 (4), pp. 393-412
PublisherInderscience Publishers
ISSN 1749-916X
Digital Object Identifier (DOI)https://doi.org/10.1504/IJTCS.2024.139187
Web address (URL)https://www.inderscience.com/info/inarticle.php?artid=139187
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Open
Accepted author manuscript
License
All rights reserved
File Access Level
Open
Output statusPublished
Publication dates
Online24 Jun 2024
Publication process dates
Accepted15 Mar 2024
Deposited01 Jul 2024
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