Between Support and Substitution: AI in University Learning, Teaching, and Assessment
The course examines how artificial intelligence can be used in university learning and teaching in ways that effectively support students’ learning processes without replacing their independent intellectual work and thereby undermining the basis of fair assessment. It starts from the participants' practical experiences with AI tools in their respective degree programs.
During the course, students experiment with various AI applications, compare their results, and systematically reflect on the didactic, normative, and assessment-related consequences of their use. Sessions combine short theoretical inputs—some created using AI itself—with discussion-oriented formats.
As a joint deliverable, participants develop a policy paper that can serve as a basis for further discussions in faculties, examination boards, and other academic bodies.
Prof. Dr. Jens Harbecke
Als Inhaber des Lehrstuhls für Theoretische Philosophie und Philosophie der Sozialwissenschaften bin ich Mitglied sowohl des Departments für Philosophy, Politics and Economics (PPE) als auch des Departments für Psychologie und Psychotherapie. In meiner Forschung befasse ich mich mit konstitutiven, mechanistischen und computationalen Erklärungen in den Sozial- und Kognitionswissenschaften. Weitere Schwerpunkte meiner Arbeit liegen in der Philosophie des Geistes, der Metaphysik, insbesondere in theoretischen Fragen der Kausalität, sowie inkontrafaktischen und Regularitätstheorien der Verursachung. Seit meiner Zeit als Prodekan für Lehre der Fakultät für Wirtschaft und Gesellschaft befasse ich mich intensiv mit der Entwicklung der Hochschullehre in Zeiten von künstlicher Intelligenz. Zu dieser Thematik soll das Seminar einen Beitrag leisten.
Ziele & Kompetenzen
The course is structured around three main thematic areas. First, it introduces the foundations of generative AI in the university context. Students learn how these systems work, what kinds of data they are based on, and in what sense AI can meaningfully be said to possess “knowledge.” Typical use cases of AI in academic study are discussed, as well as the question of whether AI merely recombines existing knowledge or can generate genuinely new knowledge. Particular attention is paid to the fairness of assessment under conditions of varying degrees of AI use.
Building on this, the course addresses didactic and ethical questions, including the role of AI as a learning aid and its associated opportunities and risks. The latter include potential declines in independent and creative thinking as well as deception in assessments. A third focus concerns legal and institutional frameworks, especially with regard to examinations and accreditation.
By the end of the course, students are able to critically evaluate different forms of AI use in academic study and to distinguish between legitimate support and problematic substitution of their own intellectual work. As a final outcome, they develop a policy paper on the transparent and fair design of AI-supported learning and assessment formats.
Maximale Teilnehmendenzahl
30 Teilnehmer