Track 1: (Planning) Teaching with AI

Generative AI as a Tool for Creating Qualitative Rubrics
Sebastian Meisel, University St. Gallen and Jacqueline Gasser-Beck, University St. Gallen

Track 2: AI in the students' lifeworld

A proposal for a revised meta-architecture of intelligent tutoring systems to foster explainability and transparency for educators
Florian Gnadlinger, University of Applied Sciences, Berlin and Simone Kriglstein, Masaryk University

Track 3: AI and Data Literacy

 A track report

The 3rd Seamless Learning Conference at WU Vienna took place on 11 April, 2024. While the general topic of the conference was “AI as a Co-Teacher”, there were tracks for breakout sessions where we were able to dig a bit deeper into some topics. Andrea Ghoneim facilitated the track “AI and Data Literacy”, hosted by Petra Oberhuemer, Head of Digital Teaching Services at WU.

In this track, Mareike Schoop from the University of Hohenheim gave an insight into what AI actually is and where, within this field, AI tools such as RapidMinder and ChatGPT can be located. The field of AI includes Machine Learning, Generative AI, and Large Language Models (LLMs) - and AI tools like ChatGPT are a relatively small subset of the set of LLMs. The topic of Mareike Schoop's presentation was "AI Competencies in Non-Technical Courses of Study". It also demonstrated curriculum design for the acquisition of AI competencies for different student groups, such as business students. The course "Applied AI" at the University of Hohenheim for around 700 students runs successfully in its third year. Mareike Schoop shared its content and discussed the extensive planning phase. You can find background information on the topic in the paper An Integrative Model of AI Competencies for Business Students and Where to Acquire Them.

Douglas MacKevett and Patricia Feubli from Lucerne University of Applied Sciences and Arts chose competence-oriented assessments and exams as a starting point of their presentation. As AI tools like Elicit and Perplexity increase the efficiency of student’s outcomes, an assessment alternative with a focus on the process and on project-based learning in groups was presented. The use of AI tools was explicitly included in the assessment workflow. The presentation slides: Transforming Higher Education: The Role of AI Assistants in Exams.

“AIComp – Developing a competence framework for a world shaped by AI” was the topic of Ulf-Daniel Ehlers and Martin Lindner from Baden-Wurttemberg Cooperative State University in Karlsruhe. Based on an analysis of competence models and competences relevant for the work with AI, a first prototype of an AI competence model has been developed, a second prototype was drafted based on qualitative interviews. In a 3rd step, a qualitative survey led to the final outcome: the AI Comp model with 12 areas of competence. The presentation can be found at the AIcomp website.

The breakout session for track 3 was concluded by Lilit Sargsyan from Yerevan State University. She focused on critical thinking skills and their development in the era of AI. Her presentation was based both on theory and on teaching practice with a focus on HEIs in Armenia. One of the conclusions: Evidence assessment of AI generated content can be done (by students) on the basis of source reliability, currency and objectivity. Awareness of relevance, accuracy and credibility of a source are part of critical thinking. The presentation slides: Fostering Critical Thinking Skills in the HEIs of Armenia in the Age of AI-driven Transformation