Mining Educational Data: A Case Study of Kathmandu University
Online Learning platforms generate vast amount of data from each user interactions in the course and most of these platforms also offer sophisticated monitoring and reporting tools to keep track of these data. However, it is often incomprehensible, poorly organized and difficult to follow, because of the tabular format that most platforms use. This research aims to provide an initial step in the direction of creating a user-friendly monitoring tool that can help educators get information about the interactions in the course easily. So, data of approximately 2000 students, who were registered to Online Learning platform (Moodle) were analyzed. These logs were then used to determine the relationship between student’s grades and student’s participation/interactions in their respective courses. Finally, a decision tree was generated using J48 classifier which can be integrated directly in the Moodle platform.
Keywords - Educational Data Mining, Learning Analytics, Moodle