AI Inspirations

We will get to the bottom of why this is the case by highlighting how the academic practices of  citation and source management  differ in GenKI texts. Together, we will examine which alternatives are required within the framework of good academic practice to demonstrate the originality of work. We will also present recommended citation formats  for Bremen University of Applied Sciences.

Lecturer: Dr Anna Kaim / Tanja Müller 

Artificial intelligence is transforming universities, businesses and society – yet for many, terms such as ‘embeddings’, ‘RAG’ or ‘AI agents’ remain a mystery. This keynote talk opens up these mysteries: in an accessible way, without unnecessary technical jargon, but with the necessary technical foundation.

The focus is on the question of how modern AI systems actually “think” and work: What are vector representations and why do they form the basis of today’s language models? How does Retrieval-Augmented Generation (RAG) enable AI systems to access up-to-date knowledge rather than relying solely on what they have previously learnt? And what lies behind AI agents that are increasingly planning and executing tasks independently?

The lecture is aimed at lecturers, students and staff from all disciplines who not only use AI but also wish to understand it and apply it in a reflective manner.

Lecturer: Niklas Bölter
 

Students’ attitudes towards AI are the subject of intense debate both in the press and among teaching staff. A number of studies have now been conducted to examine students’ usage patterns and shed light on the implications for learning processes. In this session, the findings of these studies will be presented and put into context. We will then discuss the implications for the university.

Lecturer: Dr Anna Kaim
 

Literature research is part of everyday student life – but it takes time. AI-powered web browsers promise to take on this work: searching autonomously, evaluating sources, and identifying connections. Sounds good – but does it really work?

This talk uses practical demos to show what agent-based AI browsers are capable of today: how they independently research the web, identify academic sources and process results. It will not only demonstrate what is possible, but also where the limits lie – and what to look out for when critically evaluating AI-generated research results.

A practical insight for anyone who wants to make their research work more efficient – without switching off their own brain.

Lecturer: Niklas Bölter
 

The precise formulation of learning outcomes according to taxonomic levels is a key foundation of every module description and an important part of course planning. However, it can be quite challenging to find the right wording that makes pedagogical sense and meets accreditation requirements.
In this presentation, we will demonstrate how generative AI can serve as a useful tool to specifically support this process – and in doing so, help save valuable time. Two questions are central to this:

• Quality check: How can AI be used effectively without replacing the teacher’s didactic and subject-specific responsibility?
• Prompting strategies: How can AI prompts be designed to produce precise, comprehensible and accreditation-relevant learning outcomes?

The presentation demonstrates in a practical way how AI can be used as a supportive tool – as a complement to subject-specific and pedagogical expertise, not as a replacement.

Lecturers: Andrea Broens, Johanna Brauns