Automatic Personalisation of Study Guides in Flipped Classroom: A Case Study in a Distributed Systems Course

In Computer Science programs, teaching the subject of Distributed Systems (DS) presents many challenges, especially related to the students’ prior knowledge. Some new Learning Approaches emerged and can aid to improve learning processes in this scenario, such as Flipped Classroom and Adaptive Learning. Using these approaches together enables students to explore content in a personalised way while meeting the professor-defined course objectives. In this context, our work presents a study of the integration of Flipped Classes with Adaptive Learning techniques for supporting the learning of Distributed Systems. We developed a tool to assist in the creation and generation of personalised study guides. To evaluate it, we conducted a Case Study mixing quantitative and qualitative analysis with 26 students during an entire semester of a DS course. The results indicate most students positively evaluated our approach and felt motivated in following new flipped classes with personalised study guides.