Within the framework of our degree courses in Sport, Health and Sport Science and Health at the University of Kaiserslautern-Landau (RPTU) in Kaiserslautern, we want to prepare students in the best possible way for the professional world of the future and incorporate AI into the our students' education in the long term. To this end, we want to teach theoretical and practical content relating to the application of AI in the field of sport and health and empower students to scrutinise the use of the methods critically in a context-specific manner. The courses at the AI Campus in this context represent an essential component of the blended learning setting. Two pillars are characteristic of our Fellow project: (I) the teaching of fundamentals and (II) , the practical application of methods from the field of AI in research projects and final papers in the context of sport.  

In this Fellow project, machine learning methods are integrated in a practical way into the module "Heat Pump System Technology" at RWTH Aachen University.  The teaching subject prepares future engineers for the challenges associated with heat pumps in the energy systems of tomorrow. Machine learning methods are a tool for increasing the energy efficiency of heat pumps. Live coding sessions in Python with Jupyter notebooks offer students a practical insight into typical areas of application.  Widely used ML libraries such as Scikit-Learn and Tensorflow are used here. The theoretical knowledge is conveyed using selected content from the AI Campus learning platform.

This Fellow project is aimed at students enrolled in the module "Digital Economy" (Business Administration B.Sc., Mainz University of Applied Sciences). The aim is to convey basic skills relating to business models and processes in the digital context. One aspect of this is the analysis of potentials and challenges, but also the related risks of artificial intelligence (AI) and the Internet of Things (IoT). Using the AI Campus learning tool "City | Country | Data Flow", students familiarise themselves with the associated fundamentals. In addition, they conceptualise their own AI or IoT solution relevant to their own digital business model. In future, the students will contribute to decision-making process relating to the use of such technologies. The module offers an introduction to understanding and evaluating the complex issues surrounding AI and IoT. 

Artificial intelligence already plays an important role in everyday life today; and in the future, the significance of the topic will multiply many times over. Accordingly, it is of enormous importance that a differentiated examination of the topic also takes place in teacher education programmes. As multipliers, teachers play a central role in bringing the topic of AI closer to students. Within the framework of the fellowship, students develop smaller teaching-learning research projects on the topic of AI during their practical phase in schools in Berlin. In addition, a larger online course is planned in which students plan and test their own lesson plans on the topic of AI.

The aim of this Fellow project is to impart knowledge about AI-based applications in psychological training within the framework of two applied subject areas, each with a high potential for the application of the corresponding solutions: (I) Primarily, within the framework of a course for teaching occupational and organisational psychology content using the example of AI use in the world of work in the area of leadership (incl. personnel management, team development, organisational change) and; (II) secondly, within the framework of a course on the research-oriented consolidation of health psychology methods using the example of AI-assisted digital applications for measuring physical and mental health (instrument development, adaptive testing, analysis of behavioural data).  

With this Fellow project, I would like to expand learning resources and didactic concepts on the topic of AI at Schleswig-Holstein Cooperative State University (DHSH) and contribute to digitalisation at the DHSH in that teacher staff learn how to use digital teaching formats and students learn AI application contexts supported by AI Campus resources. To this end, I intend to use AI Campus resources in the sense of blended learning as part of a module on data science and machine learning. Basic machine learning methods, an introduction to artificial neural networks and an outlook on the area of deep learning will be covered. Furthermore, I would like to raise awareness of the social consequences and encourage critical reflection on the technologies used through corresponding courses.  

The seminars on "Social-Media Communication meets AI" are established in the field of applied linguistics with a focus on digital communication and approaches in cultural studies to AI. They provide insight into the analysis of social media communication with a focus on AI topics, and the indexing and analysis of social media data. In addition to approaches in media linguistics, the role of social bots is also brought into focus. Students also build their own bots and evaluate communication processes linguistically. In this context, attention will also be paid to critical reflection on the influence that bots have on public discourse. The contents of the seminar are specifically channelled through the "Language and Word" linguistics channel on Instagram in order to make the seminar results accessible to a broader audience in the long term.