Teaching Philosophy
Teaching is more than the transfer of knowledge. My goal is to create inclusive, engaging, and intellectually challenging learning experiences that support critical thinking, self-directed learning, and the ability to apply AI methods responsibly in academia and industry.
I combine interactive lectures, digital learning environments, hands-on experimentation, formative feedback, and transparent assessment. My courses often begin with digital pre-tests to understand students’ backgrounds and adapt the course structure to the cohort.
Didactic Approach
- Open, low-anxiety learning environments with active participation.
- Socratic questioning and guided reasoning instead of frustration-based correction.
- Flipped-classroom and hybrid elements where useful.
- Interactive Moodle and H5P tasks for practical, self-paced learning.
- Rubrics, transparent expectations, and constructive feedback.
Evidence-based Development
Courses are iteratively improved through mid-course feedback, learning analytics with consent, intermediate tests, and teaching evaluations. Student feedback repeatedly highlights a positive atmosphere, practical relevance, intensive feedback, and well-structured Moodle courses.
Courses Taught
University of Potsdam
- WiSe20/21: Digitale Transformation des Lernens
- SoSe21: KI in der Bildung
- WiSe21/22: Reorganisation der Forschung und Praxis des Lernens
Humboldt-Universität zu Berlin
- SoSe22: Data Science
- SoSe23: Onlinekurse selbst gestalten – Wissenstransfer in der Praxis
- SoSe24: Onlinekurse selbst gestalten – Wissenstransfer in der Praxis
- SoSe25: Onlinekurse als Instrument des Wissenstransfers
- SoSe25: Prompt-Engineering in Education
- WiSe25/26: Prompt-Engineering & Prompt-Evaluation
Supervision
I supervise and review Bachelor’s and Master’s theses in areas such as automatic question generation, adaptive learning plans, AI feedback, argumentation analysis, error analytics in notebooks, Moodle personalization, learner trajectories, and no-code AI for knowledge transfer.