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Abstract The rise of e-learning systems has revolutionized education, enabling the col- lection of valuable students’ activity data for continuous improvement. While existing studies have predominantly focused on prolonged learning paths, short- term tutorials offer a flexible and efficient alternative that is recently gaining increasing popularity. This article presents a framework for investigating e- learning systems for short-term tutorials leveraging user behaviour tracking and process mining techniques. A case study involving a web-based tutorial with approximately one hour of learning explores the learning processes of 250 students in Italy. The study analyzes learning outcomes and investigates the impact of dif- ferent learning paths on student progress. The research questions concern i) the extraction of behavioural patterns to study learning outcomes; ii) the prediction of outcomes in the early stages of the learning process. The proposed framework not only provides descriptive insights into the learning process but it can also be used to offer prescriptive guidance to refine tutorial design and improve overall learning outcomes.
Nai et al. (Mon,) studied this question.