This paper investigates the application of data-driven analysis and visualisation to enhance project-based courses within a higher education setting. The research focuses on a digital course where students utilise digital tools such as Jira and Confluence, which generate event logs capturing students' actions. These event logs were leveraged in conjunction with process mining and business intelligence (BI) techniques to collect and analyse the data, visualised through the iterative development and evaluation of an artefact in the form of BI dashboards following the design science research paradigm. The dashboards provide lecturers with insights into student behaviour and progress, enabling them to derive actionable suggestions for adapting student behaviour. The findings demonstrate that incorporating data-driven approaches positively impacted student engagement and improved learning outcomes. This case study contributes to the fields of learning analytics and educational data mining, offering insights into utilising data-driven approaches to enhance project-based learning experiences.
Simic, Dejan; Leible, Stephan; Schmitz, Dennis; Gücük, Gian-Luca; and Kučević, Emir, "Enhancing Project-based Learning through Data-driven Analysis and Visualisation: A Case Study" (2023). ACIS 2023 Proceedings. 139.