Within the framework of this application, the three universities involved (TU Clausthal, TU Braunschweig and Ostfalia) are striving to further develop the existing courses in a cooperative manner so that they can be used across universities via a common platform. In addition, the significant additional demand for basic and specialized AI skills is to be coordinated and expanded in a sustainable and synergistic manner across locations through the generation of diverse new learning content. Although subject-specific AI study programs already exist at all participating university partners, the applicants believe that there is a significant need for more, far beyond a subject-specific student body. For the broader university public and society, this requires the creation of didactically sound teaching and learning materials to impart basic competencies in data or AI literacy in order to gain a general appreciation of the possibilities and limitations as well as the significance of data protection and ethical aspects of AI methods and to be able to participate in the use and development of AI innovations via participatory formats. In addition to traditional courses, this includes modules for self-study, events in the context of Studium Generale, as well as application-related labs and hackathons. In this context, the options for conducting digital courses, which have been further developed at all university locations over the past year, promote resource-saving and efficient delivery at the locations and to university outsiders.

The development of such complementary and coherent subject-specific, as well as interdisciplinary, learning content for the different target groups requires coordinated control and project support in the form of the envisaged AI hub, which is to be implemented and established jointly by the three university partners involved in this project.

The needs described are to be addressed by a comprehensive and participatory approach to the development, expansion and implementation of teaching and learning materials and the implementation of courses, in particular interdisciplinary formats such as application-oriented projects with cross-location and cross-stakeholder use.

In doing so, the participating universities pursue the following goals:

  • Teaching of interdisciplinary and subject-specific AI methods and development of formats for application orientation and innovation promotion
    • Horizontally across different interest and demand groups
      • university internal for interdisciplinary subject groups
      • external to the university for business and the public with a continuing education and transfer focus in the region
    • Vertical by addressing different levels of competence
      • basic competencies for a broad target group in the sense of AI literacy
      • basic skills and advanced methods in AI with a focus on engineering and science
      • subject-specific methods, projects and workshops in defined fields of application
      • provide generic AI tools for interdisciplinary use
  • Establishment of a joint decentralized platform (AI hub) of the three universities for cooperative development, provision and communication of joint teaching contents
  • Support of transformation processes for the regional service and industrial companies with regard to AI and generally data-based approaches

The participation effect is realized by actively involving learners in a so-called steering board in all aspects of content development and implementation and by taking into account both requirements analyses for AI literacy and didactic aspects in the creation of subject-specific and cross-subject content.