Teaching

Technology-enhanced, student-centered learning

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We offer lectures, seminars, and practical courses in learning technologies, web technologies, data science and visual analytics for students of Applied Computer Science, Komedia, and ISE at bachelor and master level. We teach how data analytics and visualization can open up new ways of interactions in social media, in learning environments and at the workplace. We follow a technology-enhanced, student-centered learning approach, by giving students the opportunity to learn self-paced, project-oriented and active in groups, mediated by technology-enhanced learning environments. Our students can thus get familiar with a self-regulated, inquiry- and problem-based approach to learning that can drive their practice when they graduate from university.

Current Courses (Winter Semester 2021)

Type

Title

Lecturer / Supervisor

Lecture

Learning Analytics Prof. Dr. Mohamed Amine Chatti

Check out our list of courses in the previous semesters.

Open Theses

Type

Topic

Contact

Master's Thesis Semantic Interest Modeling Using Embeddings Prof. Mohamed Chatti
Master's Thesis Recommending Learning Resources Based on Educational Knowledge Graphs Prof. Mohamed Chatti
Master's Thesis What-if? Interactions with an Explainable Scientific Literature Recommender System M.Sc. Mouadh Guesmi
Master's Thesis Explainable Learner Modeling M.Sc. Mouadh Guesmi
Master's Thesis (Komedia) An Evaluation Framework for Visually Explainable Recommender Systems M.Sc. Mouadh Guesmi
Master's Thesis Spark-based Indicator Execution in OpenLAP Prof. Mohamed Chatti
Master's Thesis Supporting Indicator Reuse and Recommendation in OpenLAP Prof. Mohamed Chatti


Additional topics in the areas of data science, learning analytics, visual analytics, and human-AI interaction are available on request.

Check out our theses overview page for more details on how to apply.