Competencies of higher education teachers in implementing artificial intelligence technologies in education
результаты опроса (N=608)
Keywords:
teacher competencies, artificial intelligence in education, generative AI models, student survey, professional developmentAbstract
The article presents results of an online survey of 608 students from Russian universities aimed at identifying student expectations regarding teacher competencies in the context of artificial intelligence integration. Based on analysis of closed and open-ended questions, three main findings are identified. First, students prioritize a universal teacher combining subject expertise with practical experience and methodological mastery: 65.1% select an experienced methodologist-pedagogue as the preferred type of teacher for core disciplines. Second, 55.4% perceive AI as a contemporary tool of the educational process, while another 40.5% accept its use subject to methodological supervision and control. Third, a systemic deficit of field-based and practice-oriented learning formats is documented: 78.6% had no experience with such activities, against an articulated demand of 80.5% for practice-oriented learning. Comparison with the UNESCO AI Competency Framework for Teachers (2024) and the Russian academic and methodological discourse reveals a gap between the official digitalization agenda and student expectations: teachers require not basic ICT literacy, but the ability to integrate AI tools into hybrid educational trajectories while maintaining authentic professional dialogue. Limitations of the study and directions for further research are discussed.
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Copyright (c) 2026 Юлия Белозёрова
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