The Fellowship Programme of the AI Campus

The AI Campus Fellowship Programme is aimed at university teachers from all departments who want to bring the future topic of AI into their teaching and are testing the integration of AI Campus learning opportunities for this purpose.  

The fellowship programme provides didactic and professional support as well as interconnecting and access to networks,  
... to achieve effective integration of learning opportunities of the AI Campus into university teaching
... evaluate the impact of using open educational resources for teaching AI competencies, and
... ensure a connectable knowledge transfer towards these objectives.   

The fellowship programme incentivises the further development of university teaching to include digital learning opportunities provided by the AI Campus. 



The Current Teaching Fellows and Their Projects

The third fellowship programme runs from October 2022 until the end of the summer semester 2023.   

AI in sports science and health

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.  

AI-based solutions and business models

In the course on business informatics, I discuss business models used by successful digital companies that operate sustainably. In addition, third term Bachelor's students apply Wirtz's and Gassmann's sustainability and digital principles to Google, Threema and AI-based business models from the AI map. Once the foundations of Machine Learning (ML) have been established, its capabilities discovered in a playful manner and use cases in the field of education explored in greater depth, the second half of the course moves on to a Design Thinking Challenge. Sustainable digital business models for ML applications in the field of education are developed in teams. The concepts developed can be fleshed out further in the Venture Lab and used to prepare for a start-up.

Artificial intelligence in energy technology

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.

AI Campus in teacher training

In this Fellow project, I aim to integrate learning opportunities into teacher training in computer science and other teacher training subjects at the University of Hamburg. This holds particular potential, because teachers are important multipliers. What is more, teachers are consonantly on the lookout for suitable and quality-assured teaching materials. If teachers are offered suitable materials for further use, they can focus better on providing individual support to their students. 

In the context of both subject-didactic modules in computer science and in research workshops, I aim to use AI Campus courses for basic subject-specific and methodological training. In particular, I would like to create options for both AI and data literacy in order to prepare students for modern teaching.  

AI and IoT in the "Digital Economy" module

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. 

Learning AI in an interdisciplinary framework: Flexible teaching/learning concept for heterogeneous learning groups

The aim of this Fellow project is to develop a flipped classroom blended learning concept that can be used flexibly which is not tied to a single degree course but is designed in an interdisciplinary way. It addresses students in the studium generale who set individual priorities against the background of their respective disciplinary or professional field of reference. The learning outcomes to be achieved for all students consist of understanding the fundamentals of AI, becoming familiar with areas of application and technologies, and questioning the interrelationships between technology, taking AI and society as an example. Students can set individual priorities in the learning outcomes in the field of medicine, nursing or business. 

AI in teacher education

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.

AI as an integral part of medical training

This Fellow project aims to anchor the topic of AI as an integral part of medical training in the context of various digital innovations and technologies, for which I created my course, "New Ideas for Medicine (NIM) – New Technologies and the Health Care of Tomorrow" a while ago. The objective is to learn about AI and other digital innovations, classify and understand them and be able to use them with reflection and in the correct context. The digital learning offerings provided by the AI Campus should be embedded in the course in a variety of ways, both in the preparation, within the sessions and in the follow-up to the event, and in the preparation of the content for publications in specialist and non-specialist media.   

AI support in research & application

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).  

Teaching AI, learning AI at the DHSH

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.  

Social media communication meets AI

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. 

AI in public administration

Owing to the forthcoming digitalisation drive in public administration, it is expected that employees in this field will in future increasingly come into contact with artificial intelligence (AI). The dual Bachelor's degree course in Public Management at Hamburg University of Applied Sciences (HAW), where future civil servants for the Free and Hanseatic City of Hamburg are trained, also intends to prepare its students for this encounter and provide them with the necessary application-related knowledge and skills. This project serves to develop exemplary demo systems for the didactic support of this teaching, which currently consists of an interdisciplinary seminar with the involvement of computer science, psychology, law, economics and ethics.