Muhammad Kassim

Distance learning has become a popular medium of education with the spread of the internet since the early 2000s. To leverage this phenomenon, learning analytics and data mining can provide insights for improving pedagogy and assessing student engagement. To that end, a student centric dataset was constructed by extracting data from the Universiti Malaya’s Moodle-based Virtual Learning Environment (VLE), serving approximately 25,000 students annually. In this paper, we present the Student Engagement Dataset (SED). The dataset consists of 16,609 students and 2,407 courses.