Discovering students use of learning resources with educational data mining

Educational data is in abundance due the nature of education in the 21^st century where a significant amount of education occurs online through the advent of digital learning. There is an increase in the use of Learning Management Systems (LMS) to provide education without boundaries, and these systems hold large amounts of data. Educational data mining is the process of tapping into this rich educational data with the aim of improving the education process through the knowledge that is obtained from the mining process. This paper aims to apply the association rule to a postgraduate course dataset that has been extracted from Moodle LMS. This can lead to actionable decisions which can be used to improve the process of teaching and learning. The results show that students mostly access the resources available to them last minute before the exam and have a tendency to procrastinate online submissions.