The teaching fellows and their projects of the year 2020/21

Out of 79 applicants, 12 projects by 19 Fellows were selected by a jury. 

AI in Journalism

Artificial intelligence is already shaping processes and content in journalism. We want to examine this on two levels within the framework of the fellowship: In teaching, we are developing basic scientific and practical features of AI and virtual organisation of newsrooms and media in a cooperative project (with Bayerischer Rundfunk and SPIEGEL) for the Journalism master's programme. In research, we see links to our international DFG project "Innovations in Journalism in Democratic Societies" (runtime 2020–2023). In addition, exciting impulses for further projects will arise in the fellowship network.

AI in Business Education Training for Vocational School Teachers

In the project, the "Introduction to AI" and "School Does AI" learning opportunities of the AI Campus are implemented in the Business Education master's programme. Against the background of the students' future professional practice, they should develop an awareness of the challenges and opportunities of AI in education as future teachers in the vocational education system and critically reflect on their use. Design options are also developed. Special emphasis is placed on the specifics of vocational education and training. A practical transfer is realised with partners from the vocational training practice.

AI at the Interface of Technology and Law

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 and the Global Governance of Digital Technologies

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 - Subject Content and Field of Application in Psychology

Following the idea of "learning to learn", machine and human learning processes as well as the possibilities for applying AI in the educational-psychological field are explicitly outlined. With the help of OER offerings, the importance of innovative, professionally relevant content is to be promoted directly at the beginning of studies, and students will be empowered to develop their own competencies in a future-oriented manner, in order to avoid perceiving digital possibilities as an unknown threat but instead recognise and reflectively evaluate the potential support they offer.

AI in English Linguistics for School and Work

The project makes use of two different AI Campus programmes. On the one hand, the "Launchpad to Fundamental Questions on AI" is tested in the non-teaching master's programme, since for these students the professional transitions between digital humanities and English linguistics – which works empirically with digital text corpora – are particularly important. On the other, the "School Does AI" course will be integrated into the doctrine of the teaching master's degree, since AI can play an important role in language education at school, such as in future vocabulary learning programmes. Another goal of the project is to gain experience in the use of OER materials.

AI Competence Promotion in the Field of Mechanical Engineering

As part of the teaching fellowship, the "Data Science and Machine Learning in Engineering" module at TH Köln (Cologne University of Applied Sciences) is enriched with material from the AI Campus offering. Employing innovative teaching methods – such as using of Python-based Jupyter notebooks and working in projects – mechanical engineering students build AI competencies. Emphasis is placed on working with real-world engineering data. In parallel, the students' perspective on integrating external material as well as assimilating engineering application examples into the teaching-learning unit is explored.

AI in the Field of Health and Medical Technology

In the field of health and medical technology, the use of AI promises great potential, such as the evaluation of medical data for prevention, diagnostics or in clinical assistance systems. Due to its relevance in the profession, one goal is to provide students with competencies in the field of AI. The offerings of the AI campus will therefore be integrated into several courses, like data mining and machine learning, personalised health technologies, information systems in healthcare, digital systems, microcontroller technology, and computer-assisted surgery.

AI in the Geosciences

Geology and computer science - at first glance, for many they do not fit well together. A big motivation for me is to change this view. With the AI Campus Fellowship Programme, there is now an excellent opportunity to expand my own teaching, with aspects that will also become increasingly important for geosciences in the future. In particular, the "Explainable Machine Learning for Engineering" and "Launchpad to Fundamental Questions on AI" offerings can be very well integrated into my teaching. Furthermore, I will adapt or develop content in the format of Jupyter Notebooks and make it available for use as well.

AI in the Field of Public Management

At HAW Hamburg, the Department of Public Management is working with students to develop a training tool for simulating AI deployment contexts. The project teaches interdisciplinary competencies, among other things, for assessing ethical and economic impacts in the digital transformation of public administration. Embedding the learning resources of the AI Campus will support the students of the bachelor's and master's programmes in the self-learning phases and seminars towards acquiring the basic knowledge. In addition, the resources of the AI Campus will enrich my teaching assignments at the Nordakademie and FOM colleges.

AI Meets Media Dramaturgy

The comparative examination of media dramaturgical design of analogue, virtual and hybrid spaces focusses on medial forms of agency and interactive spectatorship. With the help of the to-be-integrated "Launchpad to Fundamental Questions on AI" course, how AI permeates various medial habitats and influences human action and efficacy will be examined. In order to be able to transfer the opportunities and risks of AI into practice, assess and use or circumvent them, students will be introduced to the topic of AI-supported learning analytics and work in teams on how AI-supported learning analytics can change their learning spaces, or expand or limit their possibilities for representation and design in the educational process.

AI as a Tool for Artists and Designers

AI topics will be anchored as a basic building block in university teaching at BURG on a long-term and sustainable basis. The aim is to strengthen the understanding of the effects and the ensuing artistic and creative concerns of this technology. Students should understand the potential and risk and acquire competence in the application of existing tools as creative collaborators. A special focus lies on the connection with physical processes in space with the help of robotics.