Student Perceptions and Instructors Experiences of Generative AI in Computing Education : A Small-Scale Exploratory Mixed-Methods Study
Year: 2026
Type: dissertation
Study design: Observational Study
Abstract: The use of Generative AI has rapidly become widespread among students in computing education. In this study, we conduct a mixed-methods investigation consisting of a survey and semi-structured interviews to explore students’ and instructors’ per-spectives and experiences with Generative AI, with a particular focus on higher computing education at Blekinge Institute of Technology. The findings suggest that the majority of students perceive Generative AI as a beneficial tool that enhances both efficiency and understanding. However, they also express concerns about its impact on analytical and problem-solving skills. Instructors, in contrast, report concerns regarding shallow learning and reduced cognitive engagement, and describe how assessment practices have been adapted, including oral and pen-and-paper ex-aminations, to better ensure authenticity. The study concludes that there is a need for clearer guidelines and regulations at the institutional level, as acknowledged by both instructors and students. Furthermore, a clear need for guidance on how Generative AI tools can be used responsibly to nurture learning without compromising foundational knowledge has been identified. Future research could investigate how such guidelines and guidance can be developed and integrated, and what impacts they may have on students’ learning within computing education.
Authors: Andersson, Linus, Girard, Morgane
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7165425757