Tendências de transformação do ensino superior no contexto da digitalização: o caso das tecnologias de inteligência artificial

Gulyusa Ismagilova; Leisan Miftakhova; Irina Kurmaeva; Grigoriy Bazhin; Anatolii Shapovalov; Gennadiy Kuzmitskiy; Darya Gvozdeva

doi:10.22633/rpge.v29i00.20815

Authors

Gulyusa Ismagilova Kazan (Volga Region) Federal University https://orcid.org/0000-0003-0442-5770
Leisan Miftakhova Kazan Federal University https://orcid.org/0009-0003-5152-4154
Irina Kurmaeva Kazan Federal University https://orcid.org/0000-0001-8498-5529
Grigoriy Bazhin Moscow State University of civil Engineering https://orcid.org/0009-0006-5986-8471
Anatolii Shapovalov Kuban State Agrarian University named after I.T. Trubilin https://orcid.org/0000-0003-0345-641X
Gennadiy Kuzmitskiy Perm Military Institute of the National Guard Troops https://orcid.org/0009-0005-3113-6044
Darya Gvozdeva Southern Federal University https://orcid.org/0000-0003-3577-7760

DOI:

https://doi.org/10.22633/rpge.v29i00.20815

Keywords:

Higher education, Digitization, Artificial intelligence (AI), ChatGPT, Generative AI

Abstract

The purpose of this study is to substantiate the transformational trends in higher education in the context of digitalization using artificial intelligence (AI) technologies as an example. Through expert surveys, the article identifies educational models emerging from the use of AI in higher education and outlines key challenges accompanying AI integration into academic environments. The most pressing issues include upholding academic integrity, data privacy and security, ethical concerns related to intellectual property, and the unintentional spread of misinformation. The authors propose strategies to address these challenges. They conclude that the integration of AI in higher education will serve as a catalyst for significant transformations—acting both as an innovative educational tool and an increasingly important academic discipline—shaping the future of higher education where the harmonious coexistence of human and machine intelligence will open new horizons for knowledge acquisition and dissemination.

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Author Biographies

Gulyusa Ismagilova, Kazan (Volga Region) Federal University

Kazan (Volga Region) Federal University, Kazan – Russia. Ph.D., Associate Professor at the Department of Contrastive Linguistics.

Leisan Miftakhova, Kazan Federal University

Kazan (Volga Region) Federal University, Kazan – Russia. Assistant Lecturer at the Department of Contrastive Linguistics.

Irina Kurmaeva, Kazan Federal University

Kazan (Volga Region) Federal University, Kazan – Russia. Ph.D., Associate Professor at the Department of Contrastive Linguistics.

Grigoriy Bazhin, Moscow State University of civil Engineering

Moscow State University of civil Engineering, Moscow – Russia. Senior Lecturer.

Anatolii Shapovalov, Kuban State Agrarian University named after I.T. Trubilin

Kuban State Agrarian University named after I.T. Trubilin, Krasnodar – Russia. PhD, Associate professor at the Department of theory and history of state and law.

Gennadiy Kuzmitskiy, Perm Military Institute of the National Guard Troops

Perm Military Institute of the National Guard Troops, Perm – Russia. Doctor, Doctor of Technical Sciences, Academician of the Russian Academy of Natural Sciences.

Darya Gvozdeva, Southern Federal University

Southern Federal University, Academy of Psychology and Pedagogy – Russia. Candidate of Psychological Sciences, Associate Professor at the Department of Personality Psychology and Counseling Psychology.

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