Student participation in computing studies to understand engagement and grade outcome

Abstract

Aim/Purpose This paper focuses on understanding undergraduate computing student-learning behaviour through reviewing their online activity in a university online learning management system (LMS), along with their grade outcome, across three subjects. A specific focus is on the activity of students who failed the computing subjects. Background Between 2008 and 2020 there has been a multiplicative growth and adoption of Learning Analytics (LA) by education institutions across many countries. Insights gained through LA can result in actionable implementations at higher institutions for the benefit of students, including refinement of curriculum and assessment regimes, teacher reflection, and more targeted course offerings. Methodology To understand student activity, this study utilised a quantitative approach to analyse LMS activity and grade outcome data drawn from three undergraduate computing subjects. Data analysis focused on presenting counts and averages to show an understanding of student activity. Contribution This paper contributes a practical approach towards LA use in higher education, demonstrating how a review of student activity can impact the learning design of the computing subjects. In addition, this study has provided a focus on poor performing students so that future offerings of the computing subjects can support students who are at risk of failure.