A classification framework for determining permissible levels of generative artificial intelligence use in engineering education
2026, vol.18 , no.3, pp. 67-78
Article [2026-03-07]
The integration of generative artificial intelligence into engineering education raises the question of how to define permissible forms of its use in different learning activities without replacing the student’s personal contribution. The aim of this study is to propose a methodology for classifying these activities according to the permissible degree of generative AI use. The methodology considers the learning objective, expected outcome, required independence, risk of substitution, and possibilities for verification and traceability. As a result, a five-level framework, L0-L4, is developed, linking each level to permissible forms of use and control mechanisms. Its practical application is illustrated through a matrix of main learning activities and examples from engineering disciplines. The framework shows that generative AI can support learning when its use is transparent and controlled but should be restricted when it replaces the knowledge and skills being assessed.
generative artificial intelligence, engineering education, learning activities, academic integrity, controlled use of AI
https://doi.org/10.59035/JCEV4877
Aldeniz Rashidov, Fatme Rashidova. A classification framework for determining permissible levels of generative artificial intelligence use in engineering education. International Journal on Information Technologies and Security, vol.18 , no.3, 2026, pp. 67-78. https://doi.org/10.59035/JCEV4877