KI für Lehrende

In an increasingly digitalised world, the topic of artificial intelligence is also becoming more and more important in higher education. It is therefore essential for university lecturers to engage with generative AI in order to take advantage of the opportunities these technologies offer for teaching while also understanding the challenges they pose.

Since August, HeiCAD has been offering all university teachers an innovative online self-study course on the topic of ‘generative AI’.

In addition to technical background information and important legal and ethical aspects, the course also addresses university-specific issues such as exam adjustments and performance assessments. KI für Lehrende helps teachers develop realistic expectations of generative AI tools and use them responsibly.

The course is a self-study programme. The learning materials are divided into four blocks. These consist of several short videos averaging 6 minutes in length, transcripts with additional materials, and short exercises. At the end of each block, there is also a reflection section. A reflection question is designed to encourage participants to critically examine what they have learned and to discuss it with other course participants.

All course materials are made available as Open Educational Resources (OER). These materials are licensed under a Creative Commons licence and may be shared, edited and modified for personal use free of charge.

The course is freely accessible on the AI Campus.

After completing the course, teachers will be able to …

• describe how large language models work in principle and where their technical limitations lie.
• understand the social and ethical concerns surrounding generative AI systems.
• explain how generative AI tools can be used usefully and lawfully by students and teachers in a higher education context.
• describe how the use of generative AI tools affects examinations and their assessment
• apply these considerations to their own teaching.

The course is divided into four consecutive thematic blocks that promote a holistic understanding of generative AI at universities. Each block addresses an overarching topic from technical, ethical, legal and didactic perspectives that are relevant to considerations of generative AI at universities. This structured approach gives participants a comprehensive understanding of the various dimensions of generative AI and its opportunities and risks in the higher education sector.

Block 1: An introduction to generative AI at universities

You will gain an initial insight into the terms ‘AI’ and ‘generative AI’ and learn how a highly relevant technology, artificial neural networks, works. We will also consider the initial considerations arising from the spread of generative AI technologies, such as large language models, at universities.

Block 2: A holistic understanding of generative AI

Now we will delve deeper into how generative AI works, particularly large language models. This topic block aims to promote technical, legal and ethical awareness of the training process and the use of generative AI tools.

Block 3: An in-depth look at generative AI at universities

The use of generative AI tools by students, including for examination purposes, will be examined, along with the impact this may have on your own courses. You will also learn how the use of generative AI tools is influenced by trust and why generated output needs to be checked.

Block 4: Applying generative AI yourself

Now it's time to put what you've learned into practice. Having already gained valuable insights into the technical, ethical and didactic aspects of generative AI tools at universities, the focus now shifts to practical application.

Since 2024, HeiCAD has been increasingly focusing on the topic of AI literacy. The online course ‘AI in Teaching’ was developed by Selina Müller, a HeiCAD employee, as part of the AI:edu.nrw project in the sub-project ‘AI Literacy’. AI:edu.nrw is being implemented under the umbrella of the Digital University NRW in cooperation with the Ruhr University Bochum, RWTH Aachen University and HHU and is funded by the Ministry of Culture and Science (MKW) of the State of North Rhine-Westphalia. HeiCAD has developed a programme for the University of Düsseldorf on how to teach university lecturers skills in dealing with AI.