Artificial Intelligence in Teaching

Artificial Intelligence (AI) also influences digital teaching at the university. Here you will find an introduction to the topic.

What is AI?

Artificial intelligence (AI) is the ability of a machine to mimic human abilities such as reasoning, learning, planning and creativity. This brings challenges and potential. Here you will find a service offering with information about AI.

What is artificial intelligence?

Here is a compilation of interesting links on AI:

University of Applied Sciences Potsdam: FHPgpt is offered at the University of Applied Sciences Potsdam as a data protection-compliant AI assistant for lecturers, staff and students. A Campus.Account is required for this. The guidelines on AI use must be read before use. FHPgpt offers access to various AI models, including

  • OpenAI 4.0 (based on ChatGPT)
  • Meta Llama and Llma
  • Codestral (based on Mstral for generating programme code)
  • DeepSeek
  • InternVL (multimodal AI for visual perception, e.g. analysing images, diagrams and tables)
  • Qwen

FHPgpt online training course by Christian Niemczik. Can be used free of charge with a Campus.Account.

Competence models

Best practice examples for the competence-oriented use of AI

Recommendations

AI in higher education is fundamentally changing the way we teach and learn. The development is so dynamic that it can quickly lead to a feeling of being overwhelmed. Where to start? How much time should you invest when resources are scarce? What skills will be needed in the future? In view of this, it is understandable that the initial desire is for a quick ‘everything about AI in an hour’ training course. However, it is more realistic to take about a week and start with these steps:

  1. Self-study course on prompting in higher education teaching
  2. Self-study course on AI skills in higher education administration
  3. Subscribe to the AI Campus newsletter

The sqb offers AI training courses for higher education teachers in Brandenburg. Select an AI and exams course from the range on offer. You can choose between attending a workshop or completing a self-study course.

With these 3-4 steps, you have a good foundation for getting started with digital teaching using AI. The real steep learning curve begins when you start applying AI to teaching areas in which you yourself have a high level of expertise. There, you can quickly recognise where AI can help you and where it has its limitations. You can then deepen your knowledge as needed. You will find many more recommendations on this website. This website is continuously updated.

 

AI Campus Network and Platform

AI in higher education is a process and a discourse with other innovative teachers. Therefore, the key recommendation is that you register on the AI Campus platform. Subscribe to the newsletter there. Then you will always be up to date on current developments and discussions. There is a high-quality self-study course offering that is constantly being updated and expanded. Be sure to sign up for the AI Campus newsletter.

AI Campus Newsletter

Prompt laboratory

Click here to access the Prompt Lab Moodle course
Module 1: Planning phase with AI

Course: Module 1

sqb: Workshops and self-study courses

The Brandenburg Study Quality Network (sqb) offers university lecturers in Brandenburg the latest workshops and self-study courses on AI in teaching.

Some of the certificates of participation obtained can be credited toward the certificate program for university lecturers.

Online self-study courses on AI

Legal basis for AI

This is only a collection of current information. All information is provided without guarantee. Due to the novelty of the legal subject matter and the rapid development of generative AI, no final legal assessment can be made at this time.

The European AI Regulation was adopted in May 2025. This still needs to be transposed into national law. More specific guidelines for implementation also still need to be formulated. The aim of the regulation is to ensure that AI is used responsibly and ethically in the European Union and to address the risks. At the same time, innovation should be made possible.

  • EU law on artificial intelligence (EU Artificial Intelligence Act)
  • Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 laying down harmonised rules on artificial intelligence and amending Regulations (EC) No 300/2008, (EU) No 167/2013, (EU) No 168/2013, (EU) 2018/858, (EU) 2018/1139 and (EU) 2019/2144 and Directives 2014/90/EU, (EU) 2016/797 and (EU) 2020/1828 (Artificial Intelligence Act) (Text with EEA relevance). PE/24/2024/REV/1. OJ L, 2024/1689, 12.7.2024, ELI: http://data.europa.eu/eli/reg/2024/1689/oj (BG, ES, CS, DA, DE, ET, EL, EN, FR, GA, HR, IT, LV, LT, HU, MT, NL, PL, PT, RO, SK, SL, FI, SV)
    ELI: http://data.europa.eu/eli/reg/2024/1689/oj
  • The Legal Information Center for Digital Education Baden-Württemberg offers an up-to-date and easy-to-understand overview of the European AI Regulation and its implications in the context of higher education law in a video series published by the Karlsruhe Institute of Technology (KIT): The EU AI Regulation: legal framework, opportunities and challenges for universities. Legal experts speak on topics such as the AI Regulation, AI competence, data protection, copyright and AI and examination law.
  • Prof. Dr. Thomas Hoeren: Legal opinion on the significance of the European AI Regulation for universities, 2025, DOI: https://doi.org/10.13154/294-13421

Level: Lecturers

The University of Bamberg has developed a very helpful AI policy generator for lecturers with text modules on the use of AI in a course. The following legal levels are defined:

  1. Basic stance on AI (general positioning, learning objectives in relation to AI)
  2. Permitted and prohibited use (permitted use without mandatory labeling, permitted use with mandatory labeling, prohibited AI use)
  3. Copyright and data protection (dealing with copyrighted materials, data protection aspects)
  4. Labeling of AI use (format of labeling, exceptions to the labeling obligation)
  5. Equal opportunities and access (access to AI tools, examination principles and AI use)
  6. Practical tips on AI use (prompt strategies, dealing with AI errors, support with AI issues)
  7. Subject-specific aspects

Example of a code of conduct for the use of AI for a course and a Moodle course, which was created with the AI policy generator of the University of Bamberg.

 

European AI Liability Directive and Data Act

This is a proposal by the European Parliament and the Council to adapt the rules on non-contractual civil liability to artificial intelligence.

General platforms and collections on AI

In this section you will find materials that you can use free of charge in your teaching, such as comprehensive self-study courses on AI, videos and other tips. You will also find tips on didactic application scenarios and on dealing with AI in university teaching.

Speaker: Prof. Dr. Ulrike Hanke

The course can be used free of charge by members of Brandenburg universities.

  • Self-study course “EU AI Act Essentials” by Prof. Dr. Boris Paal, Dr. Till Klein, ed. KI-Campus. Confirmation of participation possible.
  • Self-study course “Data and Algorithm Ethics” by Prof. Dr. Claudia Lemke and Prof. Dr. Dagmar Monett Díaz, ed. Berlin School of Economics and Law, available via KI-Campus. Confirmation of participation possible.

Entscheidungsbaum Prüfen mit KI
Aus dem sqb Selbstlernkurs: "Prüfungen und Leistungsnachweis in einer Welt mit generativen KI-Tools wie ChatGPT. © CC BY-SA 4.0, PD Dr. Ulrike Hanke

Above, under ‘Legal information on AI’ in the tab ‘Requirements for the use of AI in teaching,’ you will find a helpful AI policy generator for teaching.

  • AI Campus
    A learning platform for artificial intelligence with online courses, videos and podcasts on the topic of AI. The main topics are chatbots and language assistants, data literacy, AI in medicine and AI in schools.
    Target group: Teachers, students and anyone interested.
  • The AI Campus is currently providing a free chatbot, which can also be used to use ChatGPT in compliance with data protection regulations at
    https://chat.ki-campus.org
  • Further information on AI tools can also be found here on the website of the FernUniversität in Hagen: ki-campus.org/tool-tip-tuesday
  • Prof Niels Can Quaquebeke has compiled an extensive collection of AI tools for the research workflow: AI Tools for Research Workflow in Academia
  • AI tools overview of the Frankfurt UAS

Good practice at the FHP! AI in teaching

Here we present some "good practice" examples on the topic of AI in teaching, from committed teachers at the University of Applied Sciences Potsdam. They are sorted by date of publication. You will always find the most recent contributions at the top of the accordion.

If you would also like to publish an example of your teaching on the topic, please contact us at digitale-lehre@fh-potsdam.de.

The project focuses on building skills among young people and disadvantaged groups to promote good work and cohesion in Brandenburg. It will run from 1 September 2025 to 28 February 2026 and is funded under the guideline ‘Social Innovations for Brandenburg – Model Programme for Promoting New Approaches to Brandenburg's Labour Policy in the 2021–2027 Funding Period’ (MWAE).

It addresses key challenges facing rural regions, such as skills shortages, unemployment, inequality of opportunity, the transformation of the world of work and adaptation to technological change. It focuses on social innovation in the field of work as the key to social cohesion.

A community-based AI laboratory* is being developed at the Luckenwalde site. This laboratory combines skills development, further training, integration and cooperation in experimental formats of social innovation. The target groups are (future) skilled workers with refugee experience as well as women and/or queer people with migration experience, especially those with links to the media and creative industries.

The project offers target group-oriented support services (spatial, material, digital) and empowers participants to develop and offer their own (further) education formats. This teaching peers approach ensures that the target groups not only benefit, but also actively transfer knowledge and skills to their communities and other social groups. The offerings are not created for the target groups, but are developed by them in collaboration with the partner network. This form of ownership creates a lasting impact and strengthens social cohesion by anchoring social innovations in and between communities.

Project participants: Christian Berkes, Marta Domurat-Linde, Wiebke Loeper, Antje Michel, Tina Steiger (project coordination) and many other (international) partners.

If you are interested in the project and would like to receive updates, please send a brief email to: praesenzstelle@fh-potsdam.de

www.praesenzstelle-luckenwalde.de

www.zukunftimgewerbehof.de

As part of a two-semester practical seminar led by Dr Katrin von Kap-herr in the European Media Studies (EMW) programme, students worked with the public access channel ALEX Berlin to develop innovative talk show formats on socially relevant topics.

In the summer semester of 2024, the students laid the groundwork for a mobile interview booth, the so-called ALEX Talkbox, which toured Brandenburg in the summer of 2024. In small groups, they researched five socially relevant topics in advance, including artificial intelligence.

Based on this research, the students developed questions and produced video clips designed to encourage visitors to the Talkbox to express their opinions on the topic of AI.

The practical implementation followed in the winter semester of 2024/2025: based on the opinions gathered, the students independently designed TV talk shows, researched guests, set key topics and took on the role of moderators. The intensive examination of the topics – especially the complex field of artificial intelligence – was just as central as the translation of these discourses into a format that was convincing in terms of journalism and media practice.

A recent result of this work is the programme ‘AI in Focus: Opportunities, Risks and Creative Applications,’ which was broadcast on 12 and 13 April 2025 on ALEX Berlin and is still available on ALEX Kosmos.

In the programme, EMW students discuss the Escape Game AI.CUBE, which makes AI a playful experience, with Marius Zoschke (MIZ Babelsberg), and talk to Dr Aljoscha Burchardt (DFKI) and Moritz Demmig (rbb) about dealing with AI-generated misinformation and its impact on the media and society.

The programme is supplemented by voices from the talk box, which impressively show how citizens perceive the opportunities and risks of AI.

The resulting programmes demonstrate how media practice, teaching and social engagement can be innovatively combined – and how topics such as artificial intelligence can be made tangible and publicly relevant in digital teaching.

In the winter semester 2023/2024, this cooperation course between HTW Berlin and the University of Applied Sciences Potsdam, led by Prof. Henrik Spohler and Prof. Wiebke Loeper, explored the technologies currently being developed to produce photographs with the help of artificial intelligence.

What are the far-reaching possibilities and risks of artificial intelligence in the field of image production? Special attention was paid to the absurd basic grammar of AI-based image generation:

Every newly created image has its basis in the past because the technical intelligence has been trained with existing image material. We live in a time when we can no longer believe any digitally transmitted voice.

The focus of the project work is the new, difficult to grasp reference to reality of generated images. The result is over 25 different works about new worlds, lost stories, new traditions and the limits of artificial intelligence with critical observations.

 

A four-person team of researchers from various institutions analysed the use of ChatGPT by social work students. The University of Applied Sciences Potsdam was represented in the team by Dr. Julius Späte and its students from various semesters of the social work degree programme contributed extensively to the data set.

In their study, the research team states that artificial intelligence systems are having a fundamental impact on the educational landscape and are expected to become increasingly relevant. The large language model ChatGPT in particular has led to a profound perturbation of the higher education landscape. ChatGPT has also found its way into social work studies and university members are faced with the challenge of developing an appropriate way of dealing with it. An essential starting point for developing a way of dealing with such systems can be found in a description of the current usage behaviour of students.

This quantitative study was dedicated to this task and offers such a starting point specifically for the field of social work studies. Across Germany and across all semesters, 875 social work students from various universities were surveyed on their usage behaviour of ChatGPT. In addition to usage behaviour, the study also surveyed students' evaluation of the AI tool, its thematisation in their studies and their affinity for technology. 
 

The results of the present research show a high usage of the tool at over 80% and thus emphasise the relevance of addressing the use of AI tools such as ChatGPT in social work studies and provide a basis for future research and didactic innovations.

Witter, S., Meinhardt-Injac, B., Siemer, L. & Späte, J. (2024). ChatGPT-Nutzung von Studierenden der Sozialen Arbeit. Eine quantitative Studie zur Nutzung, Bewertung und Thematisierung in der Hochschule aus Studierendensicht. 

 

In the course Design Against the Machine – Nonlinear Narratives of the Near Future by Prof. Boris Müller, students are working intensively on interface design and AI.

In this course, students will work intensively with - and against - generative ‘AIs’. Experimental websites will be developed that play with the results of generative ‘AIs’ and provide a visionary outlook on the influences of ‘AIs’.

Artificial intelligence technologies have reached a new level, particularly in the area of text, code and image generation. Generative ‘AIs’ can produce results that are difficult to distinguish from man-made, creative works.

However, the use of ‘AI-generated’ products raises a number of legal, ethical and creative questions. It is obviously problematic to use texts and images that are based on the creative, intellectual and – above all – unpaid work of a large number of authors, illustrators or photographers. It is also problematic to use ‘AI-generated’ products and present them as the result of your own work. Generative ‘AIs’ call entire professions into question. Do we still need illustrators when Midjourney is cheaper and faster - and still creates high-quality images at the same time?

In this course, we want to take a targeted, proactive and creative look at the use of artificial intelligence in the design process. Based on concrete designs, we will reflect on legal, ethical and creative problems. We will use generative ‘AIs’ to create code, images and texts. These will be published in the form of an experimental website and then intensively processed, modified, destroyed and recombined as the course progresses.

Basic knowledge of HTML is required to participate in the course. However, workshops on HTML and CSS will also be offered during the course.

The seminar "AI in Film" in the winter semester 2203/24 for Bachelor students of European Media Studies (lecturers: Dr. Katrin von Kap-herr, FHP and Dr. Katharina Rein, UP) deals with the intertwining of media studies and AI in a multi-layered way. It promotes an open approach to AI through interactive discussions, critical reflection and the analysis of specialist literature and media artefacts such as films and series.

The focus is on critically analysing the concept and definitions of AI as well as ethical issues surrounding the use of AI. Practical applications and the use of AI in production are also analysed. The teaching concept contributes to the development of AI skills by enabling students to analyse complex issues, make informed decisions and critically reflect on the impact of AI on society.

About the project:

The aim of the research and development project "Any-Cubes" was to make it as easy as possible for children to play and experiment with artificial intelligence and networked objects. More information can be found on the project page Any-Cubes – Discovering Artificial Intelligence through Play.

Awards:

The project was awarded the delina-Award 2022 in the category "Early Childhood Education and School" at the LEARNTEC fair in Karlsruhe.

Press release on the delina Award for Any-Cubes

 

Lecturers from the Department of Information Sciences work together in small groups to test and reflect on the potential uses and challenges of generative AI for planning, implementing and evaluating their own teaching in a Prompt Lab, which was developed by the AI Campus as OER material. The Moodle course and the workbook of the Prompt Lab are adapted to specific subjects and needs in dialogue with the Dean's Office and can then be further developed independently by the Department of Information Sciences as OER material and format.

  • Module 1: Planning phase with AI – preparing lessons
  • Module 2: Implementation phase with AI – teaching scenarios
  • Module 3: Evaluation phase with AI – feedback and examinations

Trainer: Julia Lee

Format: Blended learning (approx. 1 hour online and 2 – 3 hours face-to-face per module)

Target group: Lecturers in the Department of Information Sciences at the FHP

Location and further information will be communicated via the Dean's Office of the Department of Information Sciences in the faculty.

This is a model project. If other departments are interested, a 30-minute presentation of the Prompt Lab concept can be requested; for the teaching conference of your own department via digitale-lehre@fh-potsdam.de.

The seminar "AI – but practical by Malte Völkner and Prof. Constanze Langer (Department of Design) dealt intensively with the use of AI in design processes in the summer semester 2023.

The students tested – also experimentally – the use and limits of current AI tools for various phases of a design process – from brainstorming and interface design to storytelling and logo design. They explored topics such as health, music, industrial design, law and education.

About the teaching concept:

The topic of artificial intelligence (AI) is a black box for many. The aim of the seminar was to unravel the secrets of the black box together, to find out what AI can do and to promote cooperation across disciplinary boundaries in classroom teaching.
The focus was always on social interaction at eye level, and classic dichotomies such as lecturer/student or expert/layperson were weakened or reversed.
Workshops with external guests on areas of expertise such as design, computer science, industry, art, ethics and journalism also enabled direct exchange with external AI practitioners to reflect on and understand basic concepts of current AI research (such as Deep Learning, Explainable AI) and to relate them to their own questions and specialist interests.
The learning objective was to develop technical, ethical and subject-specific basic knowledge of AI in order to identify points of contact for cooperative and interdisciplinary AI projects in their own field of work.

Awards:

In 2022, Dr. Katrin von Kap-herr and Dr. Alexander Scheidt received the state teaching award for their seminar "... but you are a robot, aren't you? Artificial Intelligence in Theory and Practice". This was an interdisciplinary Interflex seminar.

Press release on the state teaching award for Dr. Katrin von Kap-herr together with Dr. Alexander Scheidt

About the project:

The offer was developed by the Media Innovation Centre Babelsberg in cooperation with the seminar "AI Escape Room" by Dr. Katrin von Kap-herr. The idea: to make the complex topic of AI, including its potential and challenges for the media world, accessible in a playful way. The project was awarded the audience award of the Potsdam prize for science communication in 2022 by proWissen Potsdam e.V..

The "AI.CUBE" is a live escape game with the aim of not only being a game about artificial intelligence (AI), but above all to provide an environment for knowledge transfer about AI and to explore which innovative possibilities for knowledge transfer can arise in an escape room. In workshops with experts and students of european media studies, indicators of gamification, playful media and storytelling were defined and topics related to AI were identified that can be translated into knowledge transfer elements via narrative and (audio-)visual tools. By playing the AI.CUBE – in contrast to commercial Escape Rooms – knowledge about artificial intelligence is conveyed to the players in a vivid and sustainable way.

Press release on the AI.CUBE Escape Room project

Awards:

The AI-Cube project won the 2022 audience award for science communication.

News about the Potsdam audience award for science communication for AI escape game

MaaS L.A.B.S. is a real-world project at the University of Applied Sciences Potsdam to develop a user-centred Mobility-as-a-Service platform with a project duration from may 2019 to May 2023.

The interdisciplinary MaaS L.A.B.S. project team from the social sciences, engineering and economics places transport users at the centre of its research and aims to test technologies and business models step by step in order to avoid planning errors. Four services are interlinked:

  • An app informs the citizens of a city about integrated mobility offers (public transport and sharing offers) and facilitates mobility planning and billing.
  • Intelligent sharing offers complement public transport to create an attractive overall offer that is competitive with private cars.
  • Demand-oriented shuttle buses pick up citizens at their doorsteps and thus improve the accessibility of large neighbourhoods.
  • Control systems ensure the smooth operation of this integrated transport system, which responds to current passenger requests in real time and in line with demand.

Together with the Berlin-based performance group Interrobang, the MaaS L.A.B.S. team invited people to a ride-sharing experiment on artificial intelligence and automated driving on 07 and 08 September 2021 in the north of Potsdam, simulating the use of an AI.

"Soulmachine – The self-learning Robobus" is a mobile interaction game between a group of passengers and an artificial intelligence. Five passengers take a seat in a converted minivan. Via tablet and voice control, they interact with an artificial intelligence and together take control of the vehicle. The machine develops the route and the driving experience from the collective decisions and behaviour of the passengers.

For more information, visit the Maas L.A.B.S. website.

Credits and editorial notes

The text on this page may be used as OER material, with the exception of legally designated materials, examples of good practice, proper names and trademarks, at your own responsibility under the following licence:

Content: Julia Lee, Potsdam University of Applied Sciences, Licence: CC BY-SA 4.0.

Editorial support: Leni König.

Disclaimer

Potsdam University of Applied Sciences does not guarantee the legal, technical and organisational framework conditions of the materials. Any further use is at your own risk. Most images, graphics and videos can also be reused and edited as OER material. The licence information for this can be found directly below the material or embedded in the video. External links or references to third-party content were carefully checked at the time of inclusion. No liability is assumed for the content of external websites; their operators are solely responsible for this.

Contact

Contact

Julia Lee, M. A. / Diplom
Studies and Teaching Unit
Head of the student e-learning team