Abstract:

The development of large language models (LLMs) and the resulting advances in knowledge processing, knowledge retrieval, and individualized knowledge transfer have led to far-reaching changes in the corporate world, society, and in schools and universities in recent years. At the same time, particularly in the technical sciences, a diverse range of developments and implementations of so-called “digital twins”- i.e., digital representations of real objects - have been created to produce virtual representations as detailed as possible, possessing comparable features and characteristics. The goal is to enable faster, easier, and more effective analysis, processing, further development, and research of real objects in a digital environment. Digital twins have now found an essential place in various research and production concepts, as well as in education.

The combination of digital twins with LLM is already showing the way toward “Personal Digital Twins”. This virtual representation of one's own personality enables the expansion of personal knowledge, the parallelization of everyday tasks (e.g., scheduling appointments), communication when unavailable, or the preservation of lasting personality traits for posterity.

In the context of higher education, the concepts of the Personal Digital Twin can be adapted and expanded accordingly: The “Professional Teaching Digital Twin” is the virtual representation of a teacher with a comparable appearance, knowledge base, characteristics, and personality.

In the future, this digital twin could change, if not revolutionize, the understanding of individual, sustainable, and temporally and spatially independent teaching and learning.

The potential for using a “Professional Teaching Digital Twin” is enormous and cannot yet be fully predicted. The fundamental influence of Professional Teaching Digital Twins in teaching could lead to significant changes and improvements in almost all areas of university work, for example, making professional teaching, supervision, and tutoring more flexible, scaling teaching and learning with experts to nearly any extent, and providing individualized support and exam preparation. Taking this idea further, exam formats (e.g., oral exams) could also be scaled without any problems.

The project “Professor Digital Twin” is the winner of the internal “Future Learning Initiative 2025” at the Technical University of Munich (TUM). Over a period of 12 months, at TUM, as one of the first universities in Europe, concepts and practical experiences with personal digital twins in the university environment will be developed. The goal is to implement and evaluate digital twins in specific cases in order to analyze more closely both the effectiveness of learning and the perception and acceptance of digital twins in teaching and examinations.

This contribution first explains the essential basics and application scenarios for digital twins and then discusses Personal Digital Twins. The contribution then focuses on the concept of the “Professional Teaching Digital Twin” in education, particularly on various application scenarios for digital twins within the university context. It explores the innovative potential as well as the risks that can be expected when using Professional Teaching Digital Twins. The contribution concludes with initial experiences of a personal digital twin in a teaching and learning context, as well as the further implementation of practical scenarios.

Keywords:

Digital Twin, Teaching and Learning with AI.