Teaching Large-Scale Data Management to Large Cohorts of Undergraduate Students

Teaching data management at scale presents unique challenges, particularly in large university courses with diverse student backgrounds. The “Information Systems and Data Analysis” module at Technische Universität Berlin enrolls up to 1000 students per semester, requiring scalable yet student-oriented teaching solutions. This paper presents tools and techniques we developed to enhance student learning and reduce instructor workload. We introduce isda-streaming, a lightweight Python library that simplifies data stream processing concepts, and discuss our approach to creating engaging SQL and data streaming assignments. Additionally, we describe moodle-tools, our framework for automating the lifecycle of Moodle-based exercises, improving assessment efficiency. Our open-source tools provide valuable resources for fellow educators teaching data management at scale. We report on their practical impact across multiple semesters and discuss our insights from large-scale deployment. Our experiences contribute to the growing body of research on scalable and accessible computer science education.