Text Practice with AI
New Fellowship for Innovations in Digital Higher Education
Dr. Susanne Stamm, an expert in higher education and media didactics, and Dr. Benedikt Schubert, a musicologist, were successful in submitting a project proposal to the Stifterverband für die Deutsche Wissenschaft e.V. They will receive funding for the “LISZT—Reading, Interpreting, Writing: Future-Proof Text-Based Practice with AI” tandem fellowship as part of the Fellowship for Innovations in Digital Higher Education in Thuringia. The application was supported by the university administration, specifically Dr. Jens Ewen, Vice President for Strategic University Development.
“We on the Executive Board are very pleased to receive this award and congratulate the two fellows: It confirms our approach of actively shaping how we use artificial intelligence and viewing it as a university-wide management task,” says Vice President Dr. Jens Ewen. “Both students and faculty need AI skills to be able to use these tools thoughtfully and independently. The fellowship of Dr. Susanne Stamm and Dr. Benedikt Schubert exemplifies how this can be achieved by making the use of AI transparent, embedding it in teaching, and practicing it as an independent academic discipline.”
The “LISZT” Tandem Fellowship is developing a teaching concept for source-based courses in historical musicology in which the use of AI is tied to documented procedural steps. The project relies on tools that students already use (Claude, NotebookLM)—without technical barriers—and the provision of licenses ensures equal participation for all students.
The assessment format is a portfolio that transparently documents the work process and the use of AI. Learning objectives, methods, and assessment formats are jointly coordinated by subject-matter experts (Dr. Benedikt Schubert) and higher education/media didactics specialists (Dr. Susanne Stamm) and build upon a pilot phase that began in the 2024–25 winter semester. All materials are made available as Open Educational Resources (OER) via the eTeach Network Thuringia; the approach is transferable to other source-based disciplines.
More information: https://www.stifterverband.org/digital-lehrfellows-thueringen/2026/schubert_benedikt_stamm_susanne
[August 26, 2026]