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

IF 1.2 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS International Journal of Mobile Learning and Organisation Pub Date : 2023-01-01 DOI:10.1504/ijmlo.2023.128355
Fedor Duzhin, Joo Seng Tan
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引用次数: 2

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.
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WhatsApp聊天分析:跟踪和可视化学生在项目团队中的协作
从学生互动的定量和定性描述方面捕获在线协作以实现学习成果仍然是一个挑战。我们引入了一个框架来描述和可视化学生在WhatsApp群聊中的互动。我们在数学和商业学生的课程中进行了五项研究(N = 123, N = 64, N = 106, N = 55, N = 46)。我们发现数学专业的学生比商业专业的学生写更多更短的信息。我们还发现,每条信息的平均字数与项目分数在数学上呈正相关,但在商业课程上呈负相关。我们提出了一种将WhatsApp聊天可视化为网络的方法,并测试了该网络的集中化系数与项目得分负相关的假设。这一假设没有得到证实。提出了进一步研究的启示和建议。
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CiteScore
4.10
自引率
6.70%
发文量
31
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