Development of a Learning Analytics extension in Open edX

Abstract

Persistence in online courses remains a concern for various institutions. The case of (Massive Open Online Courses) MOOCs represents a particular situation of online courses with an even higher dropout rate. This type of training highlights problems that have already been identified such as sociological isolation of the learner, loss of motivation, empowerment of the learner, acquisition of identity within a group and appreciation of the group pedagogical progress. In this context, the importance of a follow-up by a human tutor is unanimously recognized by the different a ctors. Despite the numerous services offered by open and distance learning platforms, one of the main difficulties encountered by tutors in this task is to have a sufficient understanding of what the distant learners are doing. One way that seems particularly promising to solve this problem is the exploitation of interaction traces left by learners within MOOCs, and the elaboration of indicators that can help the tutor in monitoring learners’ activities. This is why it seems imperative to me to propose a tool to visualize the work accomplished by each learner. The system must provide indicators that help the tutor to appreciate the work of the learners.