Detection of Disengagement from Voluntary Quizzes: An Explainable Machine Learning Approach in Higher Distance Education

--Students disengaging from their tasks can have serious long-term consequences, including academic drop-out. This is particularly relevant for students in distance education. One way to measure the level of disengagement in distance education is to observe participation in non-mandatory exercises in different online courses. In this paper, we detect student disengagement in the non-mandatory quizzes of 42 courses in four semesters from a distance-based university. We carefully identified the most informative student log data that could be extracted and processed from Moodle. Then, eight machine learning algorithms were trained and compared to obtain the highest possible prediction accuracy. Using the SHAP method, we developed an explainable machine learning framework that allows practitioners to better understand the decisions of the trained algorithm. The experimental results show a balanced accuracy of 91%, where about 85% of disengaged students were correctly detected. On top of the highly predictive performance and explainable framework, we provide a discussion on how to design a timely intervention to minimise disengagement from voluntary tasks in online learning. HE advent of distance education has made learning more flexible than ever before. Instead of having to attend classes and solve tasks at specific time, students are granted more freedom in choosing when to engage with their academic workload. This flexibility attracts many non-traditional student groups to higher education, including students that are employed outside of their studies, either fully or part-time. While deadlines are still set in place, students are responsible themselves for planning and time management, especially as far as non-mandatory tasks and exercises are concerned. This freedom can also lead to satisficing behaviour, meaning students only do the bare minimum to pass their courses (see e.g., [1], [2]). Bergamin are with the Institute for Research in Open-, Distance-and eLearning, Swiss Distance University of Applied Sciences, Brig, CH-3900, Switzerland (e-mail addresses: behnam.parsaeifard@ffhs.ch, N. Bergamin (e-mail address: nicole.bergamin@ffhs.ch) is with Department of Informatics, Swiss Distance University of Applied Sciences, Brig, CH-3900, Switzerland. Bergamin is also with the North-West University, Potchefstroom, 2531, South Africa. The COVID-19 pandemic is thought to have fostered this kind of behaviour even more [4]. Non-completion of voluntary tasks, such as optional quizzes, is a form of behavioural disengagement strongly linked to academic drop-out or attrition [5]-[8].