期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：12
页码：1-6
出版社：Science and Information Society (SAI)
摘要：Emergence of universities towards “digital
university” has already been present for some years. The use of
digital is largely developed to ensure a good quality of education.
Universities therefore use large-scale learning management
systems to manage the interaction between learners and teachers.
Teachers can provide online training and educational materials
for students following their classes and courses, monitor their
participation and evaluate their performance. Students can use
interactive features such as discussion threads, videoconferences,
and discussion forums. These online tools make it possible to
create new social networks or connect online social interactions.
This will allow us to understand the structure of this complex
network and extract useful information. In this article, we report
our research on the detection of student learning communities
based on learner activity. We found that it is possible to group
students in communities through their messages and response
structures using standard community detection algorithms. Also,
that their behaviours can be strongly correlated with their closest
peers who belong to the same community.
关键词：Student’s learning communities; complex network;
learner activity; community detection
