The fourth session took place on 15 January at 14:00 CET on Zoom. You can watch it here. It featured four different talks:
1) “Behind the scenes of genAI: Unmasking bias, hallucination, and AI slop in language learning” by Elke Höfler (University of Graz)
Artificial intelligence has become a constant companion in language learning – from automated translations to AI-generated feedback. Yet, with this convenience comes new responsibility.
In this talk, the speaker explored how language teacher education can foster critical awareness of AI, presenting three examples from language teacher education that invite future teachers to reflect critically on the promises and pitfalls of AI.
Through these examples, students were able to discuss how bias shapes output, how hallucinations distort meaning, and how “AI slop” affects linguistic accuracy and authenticity. By analysing their own interactions with AI tools, they learned to move from blind trust to informed awareness.
The aim was to empower pre-service teachers to guide their future learners not only in using AI, but also in understanding it as a cultural, linguistic, and cognitive phenomenon that reshapes what it means to learn and to communicate.
2) Custom GPT for formative feedback in undergraduate physics lab reports, by Arin Mizouri (Durham University).
This talk focused on a study at Durham Physics that developed a prompt-engineered, course-aligned GPT to provide formative feedback on first-year lab reports.
The speaker summarised the initial student survey, highlighting low confidence in writing, showed how the model was constrained with rubrics and exemplars, and presented evaluation data from 15 students on its usefulness and accuracy.
3) From manuscript to machine partner: AI as a co-author in graduate scholarship, by Alexander Godulla (Leipzig University)
This talk explored how generative AI reshapes the production of academic books and conferences at the Master’s level.
The speaker examined AI as a co-author, research assistant, and editorial tool, showing how it can support literature work, argument development, design of scholarly formats, and the creation of high-quality academic outputs.
4) Making chemistry machine-readable and creating datasets for improved GenAI chatbot performance in undergrad organic chemistry, by Sebastian Tassoti (University of Graz)
For higher chemistry, it is not surprising that GenAI chatbots do not have a lot of training data so it becomes crucial how you prompt the bot.
In this talk, the speaker presented evidence and the design of an intervention done with 45 students in Graz and New York City that focused on how to make organic chemistry machine-readable and how to write a prompt that trains an LLM to improve performance and use it to predict reactions with higher accuracy.
Elke Höfler is an assistant professor for Educational Technology and Design and language teaching at the University of Graz (Austria). Her research focuses on artificial intelligence, literature didactics, social media and reading didactics, among other topics. She is an educational blogger and co-founder of an educational network called #EduPnx.
Arin Mizouri is an Assistant Professor of Physics at Durham University, working on practical uses of generative AI in higher education. She has designed course-aligned custom GPTs to support student learning using evidence from student evaluations, providing formative feedback on lab reports, and creating tutor-style GPTs that guide learners rather than give solutions. Her teaching foregrounds accessibility, inclusive practice, and active learning.
Alexander Godulla is Professor of Empirical Communication and Media Research at Leipzig University. His work covers AI in media, deepfakes, digital journalism, strategic communication, and international photojournalism. He publishes widely, co-edits a handbook on AI-driven media disruption, and co-leads a research project on the effects of deepfakes.
Sebastian Tassoti is a Senior Lecturer in Chemistry Education at the University of Graz. He is a chemist by training and started working on chemistry education in his post-doc. Currently, he has several research projects on the use of GenAI in higher chemistry education settings. He does empirical research on students’ use of GenAI chatbots, with a focus on how productive use of such chatbots can be achieved.