Generative AI in the form of Large-Language Models (LLMs) such as Google’s Gemini or OpenAI’s ChatGPT are nowadays easily accessible and are increasingly being used for a variety of tasks, including studying and teaching at universities. While generative AI is here to stay, students and teachers are confronted with the question of how it can and should be integrated into learning and teaching.
There is broad agreement that generative AI should be used in a way that supports students to achieve central goals of academic education such as critical and logical thinking, creative problem solving, appropriate understanding of scientific literature, conducting own research, as well as disseminating research and own ideas in written and oral form. How this translates into daily practice is challenging. A worry is that students – for the lack of better knowledge and self-reflection – offload assignments to AI in a way that the AI and not the students are performing core steps necessary to achieve university level education. As inappropriate AI use may often also go undetected by teachers, students may pass assessments despite not reaching university level educational standards. This undermines a central strategic goal of UniDistance Suisse to deliver high quality education on a university level.
To address this problem, we propose to transmit knowledge about the brain and AI that effectively guides students in taking decisions about AI use for studying. We therefore propose to assess and refine a Brain-AI literacy course that is currently under development by EDUDL+ and will be released in October 2025 on the Kaïros platform from UniDistance Suisse. This course covers how generative AI works, what it can achieve and what not. Crucially, it also contains segments about how the brain works and what conditions are optimal for it to learn efficiently and lastingly, as well as for fostering a deep understanding. In the proposed experimental study, we will measure the participants’ pattern of AI-use for studying and their final grades before and after taking the literacy course. These data will be compared to data from a control group that enrolled in a to be developed course on time-management. We hypothesize that students in the experimental group but not the control group will adjust their AI use for learning in a way that helps them in achieving educational goals and increase their grades.
We will also analyze suggestions to improve the course obtained by participants after having completed the study. In a final phase of the project, the course will be refined based on the outcome of the empirical study.
This project will yield new insights in questions that are critical for innovative online teaching. By this it addresses a major challenge in achieving the strategic goal of UniDistance Suisse to deliver university-level academic education and will help us as an Institution to adapt to this emerging and disruptive technology.
