Academic integrity in the context of using artificial intelligence tools to develop the writing competence of university students

Abstract

Abstract. The article aims to identify the opportunities and limitations of using artificial intelligence tools in the process of forming the writing competence of higher education students, taking into account the principles of academic integrity. An interdisciplinary approach was used to combine the analysis of the current regulatory framework of Ukraine, the comparison of university policies of leading institutions in the USA and Europe, the systematization of scientific research for 2023-2025, as well as the generalization of recommendations of the Ministry of Education and Science of Ukraine and the Ministry of Digital Transformation on the responsible implementation of AI technologies. Content analysis, classification and synthesis methods were used to structure the material. The study showed that the use of generative algorithms in teaching has an ambivalent effect: on the one hand, they increase the quality of writing (improved grammar, spelling and text organization, vocabulary enhancement, increased motivation, faster access to sources and personalized feedback), and, on the other hand, they create risks of plagiarism, falsification and loss of authorial individuality. At the same time, they require verification of the results, as they are characterized by “hallucinations” and forged citations. University practices in the USA and Europe have demonstrated different approaches: from strict prohibitions (University of Missouri) to flexible models with an emphasis on transparency and the development of critical thinking (Cornell, Oxford, Harvard, AAC&U). Based on this, a number of recommendations for students are proposed: clarifying the course policy before using AI; using AI only as an auxiliary tool; checking facts and references; transparent citation in the case of involving algorithms; protecting confidential data; developing media literacy for critical assessment of the results of the models work. An important achievement is the adaptation of recommendations of the Ministry of Education and Science and the Ministry of Digital Transformation (2025) to a specific educational specialization, which provides a practical value to the research. The results proposed in the article allow not only to outline the benefits and risks of using AI in higher education, but also to form applied recommendations that can minimize manifestations of academic dishonesty. The practical significance of the work lies in creating a system of guidelines for students of higher education institutions, which can be integrated into curricula and local university policies. Keywords: university policies, digital tools, grammar enhancement, text translation, idea generation, information reliability.