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Title: Analytics for WhatsApp chats: tracking and visualising students' collaboration in project teams

Authors: Fedor Duzhin; Joo-Seng Tan

Addresses: School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, 637371, Singapore ' Nanyang Business School, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore

Abstract: COVID-19 and remote learning have accelerated online collaboration. Capturing online collaboration in terms of quantitative and qualitative description of students' interaction to achieve learning outcomes remains a challenge. We introduce a framework for describing and visualising students' interactions in WhatsApp group chat. We present five studies (N = 123, N = 64, N = 106, N = 55, N = 46) in courses taken by mathematics and business students. We found that mathematics students wrote more messages and shorter messages than business students. We also found that average number of words per message correlated with the project mark positively in mathematics but negatively in business courses. We suggest a way to visualise a WhatsApp chat as a network and tested the hypothesis that the centralisation coefficient of this network correlated negatively with the project score. The hypothesis was not confirmed. Implications and suggestions for further study are presented.

Keywords: learning analytics; collaboration visualisation; network science; student collaboration; WhatsApp chats.

DOI: 10.1504/IJMLO.2023.128355

International Journal of Mobile Learning and Organisation, 2023 Vol.17 No.1/2, pp.149 - 179

Received: 19 Mar 2021
Accepted: 20 Aug 2021

Published online: 18 Jan 2023 *

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