Influence of different session timeouts thresholds on results of sequence rule analysis in educational data mining

Abstract

The purpose of using web usage mining methods in the area of learning management systems is to reveal the knowledge hidden in the log files of their web and database servers. By applying data mining methods to these data, interesting patterns concerning the users' behaviour can be identified. They help us to find the most effective structure of the e-learning courses, optimize the learning content, recommend the most suitable learning path based on student's behaviour, or provide more personalized environment. We prepare six datasets of different quality obtained from logs of the learning management system and pre-processed in different ways. We use three datasets with identified users' sessions based on 15, 30 and 60 minute session timeout threshold and three another datasets with the same thresholds including reconstructed paths among course activities. We try to assess the impact of different session timeout thresholds with or without paths completion on the quantity and quality of the sequence rule analysis that contribute to the representation of the learners' behavioural patterns in learning management system. The results show that the session timeout threshold has significant impact on quality and quantity of extracted sequence rules. On the contrary, it is shown that the completion of paths has neither significant impact on quantity nor quality of extracted rules. © 2011 Springer-Verlag Berlin Heidelberg.