Learning Analytics & AI in Education — Summer Course
5 ECTS · Open to students worldwide
Overview
This intensive summer course provides a hands-on introduction to learning analytics and artificial intelligence in education. Designed for researchers, graduate students, and professionals from any discipline, it covers the practical application of data-driven methods to understand and improve learning. Participants work with real educational datasets, learn to use R for analytics, and explore how AI techniques can be applied to educational contexts.
What You Will Learn
The course covers a broad range of topics including the foundations of learning analytics, data collection and preparation, predictive modeling, network analysis of learning interactions, sequence and process mining, and the use of AI tools for educational decision-making. Each topic is paired with practical exercises using real datasets and reproducible R code.
Format
The course combines synchronous online sessions with asynchronous activities, collaborative group projects, and individual assignments. There are no final exams — assessment is based on practical exercises, a group project, and reflective assignments. Guest lectures from international experts in the field complement the core sessions.
Who Should Take This Course
The course is suitable for anyone interested in understanding how data and AI can be used in educational contexts — whether you are a PhD student exploring learning analytics for your research, a teacher curious about data-driven approaches, or a professional looking to bring analytics into your educational practice. No prior programming experience is required.