Improving retention in first-year mathematics using learning analytics

Despite the importance of mathematical skills in quantitative disciplines, high failure rates in first-year university mathematics subjects have been observed in many parts of the world. Mathematics support provisions are established in many tertiary institutions in order to assist at-risk students to master and pass mathematics subjects. However, while a significant amount of data is being collected on students (e.g. entry scores, backgrounds), their behaviour (e.g. access of support services, engagement with online resources) and their performance (e.g. in assignments, tests), not much analysis is currently done with this data to predict a student’s chances of success, and to better guide the services of mathematics support centres and target intervention procedures. This paper reviews relevant literature and describes a proposed research project to improve retention in first-year mathematics using a learning analytics approach.