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September 10, 2025Vysshee Obrazovanie v Rossii = Higher Education in Russia17 citationsOpen Access

Falling Behind and Getting Ahead: Student Use of Generative AI in Education

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YKYaroslav KuzminovEKEkaterina KruchinskaiaIGIvan Gruzdev

Key Points

  • The study reveals that generative AI exacerbates educational inequality, affecting STEM and non-STEM students differently.
  • Data from a survey of 4207 students suggests that AI enhances learning for high-achieving students but hinders others.
  • Observational analysis aims to identify specific challenges posed by AI in the educational landscape of Russia.
  • Addressing the disparities in AI integration is essential for developing effective educational strategies and promoting equity.

Abstract

With the rise of generative artificial intelligence (AI), the relationship between these emerging technologies and education, as well as educational practices, has become a central topic of scholarly debate. Research in this area is rapidly expanding, particularly regarding the potential benefits and drawbacks of AI use by students in education. However, despite the growing interest, certain gaps remain. Firstly, research often lacks a strong empirical foundation with rigorous hypothesis testing using validated methodologies, especially within the Russian context. Secondly, existing studies tend to focus primarily on opportunities for development rather than potential challenges. The authors believe that identifying these challenges is crucial for effectively managing the integration of AI into education, and this serves as the primary goal of this study. The core objective of this research is to provide empirical evidence supporting the existence of such challenges and to delineate their specific nature. To achieve this, we analyze data from a survey conducted by the authors in 2025, involving students from leading Russian universities (N=4207). One of the most significant challenges identified by the study is the exacerbation of inequality within the educational landscape. This is particularly evident in the disparate AI usage patterns between students in STEM fields and those in non-STEM disciplines. Furthermore, significant heterogeneity exists among students with varying academic performance (GPA). For highachieving students, AI tends to serve as a tool for enhancement, whereas for others, the opposite effect is observed. These findings are partially consistent with existing literature reviews, both domestic and international, as well as other surveys conducted on the topic. However, they contribute to a more defined understanding of the challenges associated with increasing educational inequality due to AI. Addressing the divisions within the educational sphere resulting from unequal levels of AI integration and utilization represents a crucial first step toward developing appropriate educational strategies that leverage AI as a tool to empower students, rather than the contrary.

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Cite This Study

Kuzminov et al. (2025) studied this question.

synapsesocial.com/papers/68c1a13354b1d3bfb60dc789https://doi.org/10.31992/0869-3617-2025-34-6-9-35
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