Abstract:

In this paper, we are interested in educational data on WhatsApp. Despite the fact that Moodle is a popular e-learning platform used in different African universities, students prefer WhatsApp instant messaging to communicate with each other and with their teachers. Many WhatsApp groups are created by students and teachers with educational goals. There are more and more learning activities that occur on this messaging platform through these small communities to the detriment of forum and chat of the e-learning platform. We identified many WhatsApp groups created by Science, technology, engineering, and mathematics (STEM) students from the Université Norbert Zongo and the Burkina Institute of Technology. As WhatsApp does not provide any plugin to fetch group discussions, we manually exported the chat by the group's administrators. This feature is provided in WhatsApp groups. We used NTLK, a Natural Language Processing tool, to analyze the data fetched from WhatsApp groups. We observed in the group’s discussion learning activities and academic information. Many learning resources are shared. We also found some traces of social and collaborative learning: students who ask comprehension questions and others who provide answers, discussions on course concepts. WhatsApp has implemented the end-to-end encryption that makes it difficult neither to have the created groups list nor to retrieve group data. This context implies that Educational Data Mining is out of reach for most West African countries, widening the educational gap between universities. In order to address this problem, we propose to extend the features of traditional e-learning platforms with a WhatsApp-like mobile application. This mobile instant messaging application will interact with the platform in a backend.

Keywords:

WhatsApp, Educational Data Mining, West Africa, University.