English language and linguistics research seminar: Rafael Lomeu Gomes (University of Copenhagen): “We are really pushed into a corner here”: Study practices and AI in Danish higher education

Recent studies on text-generative artificial intelligence (genAI) in higher education have documented the common uses of this technology by university students, as well as concerns they might have (Hojer Bruun et al. 2024, Stöhr et al. 2024). Little is known, however, about the interplay between students’ everyday study practices and institutional and societal structures in which genAI technologies are embedded. In this presentation, I demonstrate the multiple scales students navigate as they make decisions about whether and how to use genAI in their studies. Particularly, I propose that students orient to intrapersonal, interpersonal, institutional, and social, political, and environmental scales in their engagement (or lack thereof) with genAI. The dataset for this study has been generated through linguistic ethnographic fieldwork initiated in January 2025 at a Danish higher education institution and consists primarily of participant observation, fieldnotes, and semi-structured interviews with first-year university studies. Anchored in the notion of enregisterment (Agha 2007), preliminary analysis shows how students’ understandings of what characterises academic writing and, ultimately, what it means to be a student (cf. Ulriksen 2009) are being reconfigured with the advent of genAI in educational landscapes.

Agha, A. 2007. Language and Social Relations. Cambridge: Cambridge University Press.

Ulriksen, L. 2009. The implied student. Studies in Higher Education 34(5): 517-532.

Hojer Bruun, M., J. Krause-Jensen, and C. Hasse. 2024. Pædagogisk indblik: Udfordringer og muligheder med store sprogmodeller og AI-chatbots på videregående humanistiske og samfundsvidenskabelige uddannelser. Pædagogisk indblik Nr. 26. Aarhus Universitetsforlag.

Stöhr, C. A. Wanyu Ou, and H. Malmström. 2024. Perceptions and usage of AI chatbots among students in higher education across genders, academic levels and fields of study. Computers and Education: Artificial Intelligence 7.