eduGraph: A Dashboard for Personalised Feedback in Massive Open Online Courses

Abstract

Learning Analytics is concerned with the design and implementation of tools and processes for collecting, analysing, and communicating information about teaching and learning. It is enabled by data, but not driven by it, rather it tries to empower human judgements by presenting meaningful facts. This thesis explores the data generated in Open edX courses to understand how it can be analysed and used to impact learners' motivation in online courses. It is carried out using Design Science, a research methodology aiming to produce artefacts that can improve the interaction with problems. In this thesis I present the eduGraph dashboard, a dashboard that uses Learning Analytics to present meaningful insights about learners' learning process in Massive Open Online Courses (MOOCs). Results indicate that learners perceive the dashboard as useful and effective at motivating them to take part in online courses, and that it enables them to keep track of their progress in the courses. I posit that the biggest problem facing Learning Analytics today are the lack of accessible data, and that it is possible for reasearchers to create more accurate learner models by using Learning Anaytics theories and methods in combination with the iterative and technical process of Information Systems development.