employee
The article examines the problem of integrating generative artificial intelligence technologies (using large language models as an example) into the training process of bachelor's students in the field of "Software Engineering." The relevance is driven by the rapid adoption of AI tools (ChatGPT, GitHub Copilot) in the software development industry, which creates a contradiction between employer demands and the risks of degrading students' fundamental competencies. The author identifies the main risks: cognitive laziness, a decline in algorithmic thinking, and academic dishonesty. A differentiated model for AI integration depending on the discipline is proposed: complete exclusion in the early years (algorithmization) and controlled use in the later years (architecture design, testing). The conclusion is drawn that it is necessary to develop students' metacognitive skills and responsible use of AI as a tool that expands, but does not replace, engineering thinking.
artificial intelligence, generative neural networks, software engineering, bachelor's degree program / undergraduate studies, cognitive laziness, methodological model, ChatGPT, GitHub Copilot, higher education, digital transformation
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