Prof. Dr. Mohammed Saqr
Learning cannot be directly observed, but it becomes evident through the learning process and how it unfolds over time and across activities. The importance of learning process dynamics lies in the fact that learners’ actions reveal learning more accurately than their descriptions, intentions, or aptitude measures. To better capture the complexity of learning—particularly its timing, relationships, and dependencies—this workshop provides a hands-on introduction to these methods, offering novel analytical techniques and rigorous approaches.
The workshop is designed to be accessible to all participants, with no technical background required, and uses point-and-click tools that make sophisticated methods easy to apply and understand. The workshop will demonstrate these methods using human–AI learning interaction data as contemporary examples, though the analytical skills and techniques participants develop will be transferable to any learning context where understanding temporal patterns and learner pathways is essential. Attendees are also welcome to bring their own data (event- or time-stamped data).
ECTS: 1 (Pflicht- oder Wahlpflichtbereich GSDE, offen für (Post-)Doktorierende und fortgeschrittene MA-Studierende).
