Gücük, Gian-LucaSimic, DejanLeible, StephanLewandowski, TomKučević, EmirKlein, MaikeKrupka, DanielWinter, CorneliaWohlgemuth, Volker2023-11-292023-11-292023978-3-88579-731-9https://dl.gi.de/handle/20.500.12116/43125This paper presents a real-time data analytics (DA) stack designed for a project-based course utilizing Jira for project management at a university. The DA stack follows an Extract, Transform, and Load process to visualize students’ usage data within dashboards. The DA stack supports course management by providing insights into students’ activities and progress. We demonstrate the DA stack’s effectiveness through an evaluative case study, which was found to support course objectives and foster improved behavioral adaptations from lecturers to students. Furthermore, we propose a generic DA stack for generalizing and adopting it for similar applications, considering the extensibility and maintainability inherent in the open-source tools used. Moreover, we provide the GitHub repository to view our source code. This study contributes to the relatively underexplored field of real-time learning analytics and offers a starting point for the customization and adoption of the proposed DA stack in different educational contexts.enLearning analyticseducational data miningdata analyticsproject-based learningbusiness intelligenceText/Conference Paper10.18420/inf2023_1961617-5468