Clustering Methods Applied to the Tracking of User Traces Interacting With an e-Learning System
Many research works are carried out on the analysis of traces in a digital learning environment. These studies produce large volumes of usage tracks from the various actions performed by a user. However, to exploit these data, compare and improve performance, several issues are raised. To remedy this, several works deal with this problem seen recently. This research studied a series of questions about format and description of the data to be shared. The authors goal is to share thoughts on these issues by presenting their experience in the analysis of trace-based log files, comparing several approaches used in automatic classification applied to e-learning platforms. Finally, the obtained results are discussed.