Using Learning Analytics to Investigate Student Performance in Blended Learning Courses

Abstract

Many higher education institutions today offer online delivery as an alternative or addition to provide more flexibility to learners. However, students being confronted with such services come with different expectations to what that means to their learning paths and behaviours. Learning Analytics is a rather new and innovative way of making student behaviour and performances explicit through analysing large sets of learner data. In this article, we take the case of online and blended learning from the University of Mauritius and hold the analysis of student interaction data against their performances and achievements. The study encompasses the entire population of first year students over two consecutive academic years of an undergraduate programme in Web and Multimedia Development. We classified the data into distinctive parts namely participation (or engagement), coursework marks, exam marks, and overall results to identify relationships that may influence student retention. 29.03.2017 | Wolfgang Greller, Mohammad Issack Santally, Ravindra Boojhawon, Yousra Rajabalee & Roopesh Kevin Sungkur