Artificial Intelligence and learning motivation

UDC (378-042.4:004.8):316.6
DOI 10.20339/AM.02-26.067

Alsu D. Battalova, Teaching assistant at the School of Advanced Studies, Tyumen State University. Master’s student of “Applied Pedagogy of Higher Education”, Tyumen State University, Tyumen, Russia, https://orcid.org/0009-0002-3411-4690, e-mail: a.battalova@utmn.ru

This article examines the impact of the frequency of artificial intelligence (AI) use on the academic motivation of first-year students at the School of Advanced Studies (SAS), Tyumen State University. The aim of the study was to determine whether there is a relationship between the frequency of general AI use, the use of AI-powered personas, and the level of academic motivation as measured by John Keller’s ARCS model (Attention, Relevance, Confidence, Satisfaction). Participants included first-year students at SAS, a program characterized by its interdisciplinary curriculum, student-led learning paths, and active use of digital tools. Data were collected via an online survey that included sections on AI usage and the CIS motivation scale. The results revealed a statistically significant positive correlation between the use of AI personas and all components of academic motivation, whereas general or academic use of AI technologies showed no significant associations. These findings suggest that personalized AI systems can effectively enhance and sustain student motivation in digital learning environments.

Keywords: AI, learning motivation, higher education

Acknowledgements. The study was conducted with the support of the Ministry of Science and Higher Education of the Russian Federation under agreement No. 075-03-2025-662 (dated January 17, 2025) related to project FSMG-2025-0086 “Applied research on the introduction of artificial intelligence technologies in higher education.”

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