Artificial Intelligence in Master’s Education as A Driver of Transformation in The Educational Process: Pedagogical, Analytical, And Ethical Issues
Abstract
This article examines the impact of artificial intelligence (AI) technologies on the transformation of master’s-level education, with a focus on changes in cognitive, research, and pedagogical processes. It is demonstrated that modern generative models are shifting from an instrumental function toward the role of a cognitive intermediary in students’ scientific activities. The empirical part of the study is based on a survey of 198 master’s students and 24 faculty members using a structured checklist questionnaire. The results indicate a high level of AI integration into educational and research activities, including data analysis (80.6%), text generation (74.3%), and table creation (77.9%). It was found that 87.8% of respondents reported improved performance in academic tasks; however, 17.6% identified errors in AI outputs, highlighting the need to develop critical digital literacy. The study concludes that a hybrid “human–artificial intelligence” model is emerging in master’s education, where technology functions as an enhancer rather than a substitute for cognitive activity.