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<p>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.</p>

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The AI disruption in engineering education: an analysis of changing student norms through cultural historical activity theory

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月12日

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  • Tiina Leino Lindell,
  • Christian Stöhr

摘要

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.