The AI disruption in engineering education: an analysis of changing student norms through cultural historical activity theory
Artikel i vetenskaplig tidskrift, 2026

This article explores the transformative impact of generative Artificial Intelligence (GenAI) on engineering education from a student perspective. Employing Cultural-Historical Activity Theory (CHAT), the study analyzes how GenAI challenges and changes established norms, and practices in and outside the classroom. Through thematic analysis of interviews with 25 students from a technical university in Northern Europe, we identify four themes of challenges or undergoing transformation due to GenAI: (1) the self-directiveness of students, (2) the objectives of learning, (3) the role of the teacher, and (4) the ethical aspects. The study reveals that participating students are developing new implicit rules for using GenAI to enhance their skills and understanding. These changes are driven by contradictions between traditional academic tools and the new expectations for self-directed and efficient learning support. While these students demonstrate awareness of GenAI’s flaws and the challenges for academic integrity, they appreciate the immediate and personalized support provided by GenAI, which contrasts with the slower, more dependent nature of teacher interactions. This shift in expectations is leading to a re-evaluation of the division of labor between these students and their teachers. The study concludes by discussing the implications for the investigated educational practice and the potential development of theory, emphasizing the need for similar engineering education institutions to respond to the specific challenges and transformations observed in this context.

Engineering education · Students’ norms · Generative AI strategies · Cultural-historical activity theory · Challenges and transformations · Contradiction

Författare

Tiina Leino Lindell

Chalmers, Vetenskapens kommunikation och lärande, Ingenjörsutbildningsvetenskap

Christian Stöhr

Chalmers, Vetenskapens kommunikation och lärande, Ingenjörsutbildningsvetenskap

Journal of Computing in Higher Education

1042-1726 (ISSN) 18671233 (eISSN)

Vol. In Press

Navigating Large Language Models: Rules, Challenges, and Fair Transformations for STEM Education

Chalmers, 2024-06-01 -- 2026-05-31.

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier (SSIF 2025)

Utbildningsvetenskap

Lärande och undervisning

Pedagogiskt arbete

DOI

10.1007/s12528-025-09488-8

Mer information

Senast uppdaterat

2026-01-30