Iryna Poliakova ACADEMIC INTEGRITY IN THE USE OF ARTIFICIAL INTELLIGENCE IN THE PROCESS OF TRAINING FUTURE PHILOLOGISTS

(2026) Science and education, 3, 136-141. Odessa.

DOI:https://doi.org/10.24195/2414-4665-2026-3-15

Iryna Poliakova,
Candidate of Pedagogic Sciences,
Director of the Kharkiv Pedagogical Professional College,
Associate Professor at Ukrainian Linguistics,
Literature and Teaching Methods,
Municipal Establishment «Kharkiv Humanitarian-
Pedagogical Academy» of the Kharkiv Regional Council,
7, Lane Rustaveli Str., Kharkiv, Ukraine,
ORCID ID: https://orcid.org/0000-0002-4931-2203

 

ACADEMIC INTEGRITY IN THE USE OF ARTIFICIAL INTELLIGENCE IN THE PROCESS OF TRAINING FUTURE PHILOLOGISTS

SUMMARY:

The article analyzes the problem of adhering to the principles of academic integrity in the context of the mass introduction of generative artificial intelligence technologies into the process of training future teachers of the Ukrainian language and literature. The relevance of the study is due to the paradigmatic crisis of traditional models of academic control and the emergence of a regulatory vacuum regarding the regulation of the use of neural networks in higher education. The axiological, ontological-legal and didactic-methodological dimensions of the transformation of the category of authorship in the era of AI, where the role of a higher education student moves from ordinary text creation to critical creation and verification of information, are analyzed. The differences between traditional plagiarism and the latest phenomena of dishonesty («AI-giarism») are systematized, the essence of the «detection crisis» of generated content is substantiated. Special attention is paid to the specifics of philological education, where language and text are direct objects of professional training. Specific risks of hidden delegation of tasks to AI are identified in three components: methodological (loss of didactic individuality, template nature of NUS lesson summaries), literary studies (simulation of personal aesthetic experience of analyzing works, refusal to read primary sources) and linguistic (complicity in the falsification of scientific truthfulness through «artificial hallucinations» of AI). The concept of «digital surrogate» as intellectually devalued content and imitative activity, which leads to the erosion of internal responsibility and the destruction of the linguistic and ethical competence of the future linguist, is explored. The emphasis is placed on the ineffectiveness of the punitive-reactive approach and the need to transition to proactive design of the educational environment, where the evaluation is not the final text, but the process of cognitive and methodological activity of the student.

KEYWORDS:

academic integrity, artificial intelligence, generative language models, training of philologists, New Ukrainian School

FULL TEXT:

REFERENCES:
  1. Kudla, M. V. (2024). Formuvannia akademichnoi dobrochesnosti maibutnikh pedahohiv u protsesi profesiinoi pidhotovky: teoretychnyi aspekt [Formation of academic integrity of future teachers in the process of professional training: a theoretical aspect]. Perspektyvy ta innovatsii nauky (Seriia «Pedahohika», Seriia «Psykholohiia», Seriia «Medytsyna»), 3 (37), 360–369. https://doi.org/10.52058/2786-4952-2024-3(37)-360-369 [in Ukrainian].
  2. Verkhovna Rada of Ukraine. (2025). Pro akademichnu dobrochesnist [On academic integrity] (Law of Ukraine № 4742-IX). Retrieved from https://zakon.rada.gov.ua/laws/show/4742-20#Text. [in Ukrainian].
  3. Ministry of Digital Transformation of Ukraine, Ministry of Education and Science of Ukraine, UK International Development, & EF. (2025). Rekomendatsii shchodo vidpovidalnoho vprovadzhennia ta vykorystannia tekhnolohii shtuchnoho intelektu v zakladakh vyshchoi osvity [Recommendations on the responsible implementation and use of artificial intelligence technologies in higher education institutions]. Retrieved from https://mon.gov.ua/static-objects/mon/sites/1/news/2025/04/24/shi-v-zakladakh-vyshchoi-osvity-24-04-2025.pdf [in Ukrainian].
  4. Sobolieva, S. M., Filippova, L. V., & Krasylnykova, I. V. (2025). Akademichna dobrochesnist v epokhu shtuchnoho intelektu ta validnist instrumentiv vyiavlennia porushen [Academic integrity in the era of artificial intelligence and the validity of violation detection tools]. Pedahohichna akademiia: naukovi zapysky [Pedagogical Academy: Scientific Notes], (11). https://doi.org/10.5281/zenodo.17523489 [in Ukrainian].
  5. Sopova, D. (2018). Akademichna dobrochesnist u systemi profesiinoi pidhotovky maibutnoho pedahoho [Academic integrity in the system of professional training of the future teacher]. Neperervna profesiina osvita: teoriia i praktyka (Seriia: Pedahohichni nauky) [Continuing Professional Education: Theory and Practice (Series: Pedagogical Sciences)], (3–4), 52–56. https://doi.org/10.28925/1609-8595.2018(3-4)5256 [in Ukrainian].
  6. Torchynska, N. M., & Torchynskyi, M. M. (2021). Formuvannia kompetentnostei akademichnoi dobrochesnosti v studentiv-filolohiv [Formation of competencies of academic integrity in students-philologists]. In L. H. Bilyi (Ed.), Akademichna dobrochesnist: praktychnyi dosvid [Academic integrity: practical experience] (Iss. 1, pp. 127–133). Khmelnytskyi: Vyd-vo MAUP. [in Ukrainian].
  7. Avsheniuk, N., Seminikhyna, N., Ruban, L., & Sviatiuk, Y. (2025). Exploring Overreliance on AI Tools in English for Specific Purposes Courses: Challenges and Implications for Learning and Academic Integrity. Arab World English Journal, (Special Issue on Artificial Intelligence), 3–20. https://dx.doi.org/10.24093/awej/AI.1 [in English].
  8. Committee on Publication Ethics. (2023). COPE Position Statement: Authorship and AI tools. Retrieved from https://publicationethics.org/cope-focus/artificial-intelligence [in English].
  9. Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. Retrieved from https://www.unesco.org/en/articles/guidance-generative-ai-education-and-research [in English].
  10. Matjola, I. (2025). Academic integrity and generative AI research for higher education: a systematic literature review. In Human, Technologies and Quality of Education (pp. 358–371). University of Latvia. https://doi.org/10.22364/htqe.2025.25 [in English].
  11. Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity. [in English].
  12. Ji, Z., Lee, N., Frieske, R., Yu, T., Su, D., Xu, Y., & [et al.]. (2022). Survey of Hallucination in Natural Language Generation. ACM Computing Surveys, 1(1), 1–41. https://doi.org/10.1145/3571730 [in English].
  13. Sanz-Tejeda, A., Domínguez-Oller, J. C., Baldaquí- Escandell, J. M., Gómez-Díaz, R., & García-Rodríguez, A. (2026). The impact of generative AI on academic reading and writing: a synthesis of recent evidence (2023–2025). Frontiers in Education, 10, Article 1711718. https://doi.org/10.3389/feduc.2025.1711718 [in English].