Technology-enhanced, student-centered learning
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 2021/22)
|Master's Thesis||Semantic Interest Modeling Using Embeddings||M.Sc. Mouadh Guesmi|
|Master's Thesis||Recommending Learning Resources Based on Educational Knowledge Graphs||M.Sc. Qurat Ul Ain|
|Master's Thesis||Visual Explanations in a 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||M.Sc. Shoeb Joarder|
|Master's Thesis||Supporting Indicator Reuse and Recommendation in OpenLAP||M.Sc. Shoeb Joarder|
|Master's Thesis||Semantic Search and Recommendation of Educational Data Science Literature using Embeddings||M.Sc. Shoeb Joarder|
|Master's Thesis||A Toolkit for xAPI-based Data Collection in OpenLAP||M.Sc. Shoeb Joarder|
|Master's Thesis||Privacy-Preserving Learner Data Management in OpenLAP||M.Sc. Shoeb Joarder|
Additional topics in the areas of data science, learning analytics, visual analytics, explainable recommendation, and human-AI interaction are available on request.