kaz29Вестник Казахстанско-Британского технического университетаHerald of the Kazakh-British Technical University1998-66882959-8109Казахстанско-Британский Технический Университет10.55452/1998-6688-2023-20-3-17-25kaz29-760Research ArticleКОМПЬЮТЕРНЫЕ НАУКИCOMPUTER SCIENCEГЕНЕРАТИВНЫЙ ИИ: ПРОБЛЕМЫ АКАДЕМИЧЕСКОГО КАЧЕСТВАGENERATIVE AI: CHALLENGES TO ACADEMIC QUALITYhttps://orcid.org/0000-0002-8689-5268СенджербейЕраланSencerYeralan

Сенджербей Ералан, Профессор

Баку

Sencer Yeralan, PhD Professor

Baku

sencer.yeralan@gmail.comhttps://orcid.org/0000-0002-9930-6119ЛаураАнкона ЛиLauraAncona Lee

Лаура Анкона Ли, PhD, декан офиса интернационализации

Сан Паоло

Laura Ancona Lee, PhD, Dean Academic Internationalization 

S˜ao Paulo

internacionalizacaoacademica2@unip.brУниверситет АДААзербайджанADA UniversityAzerbaijanUNIPБразилияUNIPBrazil2023011020232031725Copyright © Сенджербей Е., Лаура А.Л., 20232023Сенджербей Е., Лаура А.Л.Sencer Y., Laura A.L.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://vestnik.kbtu.edu.kz/jour/article/view/760

Данное исследование посвящено пересечению генеративного искусственного интеллекта и академического качества. Обе эти области широко представлены в технической и исторической литературе. Поскольку области исследований разнородны, любой поиск значимого ответа на влияние одной на другую должен включать как минимум воздействие каждой из них. Мы даем краткий обзор этих областей, чтобы облегчить дальнейшее обсуждение и представить соответствующие мысли об ожидаемом влиянии новой технологии на академическое качество. В документе также обсуждается положительное влияние генеративного ИИ на высшее образование и демонстрируются будущие направления использования ИИ в будущем общении и коллективной работе.

This study explores the intricate relationship between Generative Artificial Intelligence and Academic Quality, two domains that have robust technical and historical underpinnings. Originating from divergent research fields, an understanding of the impact of one on the other necessitates a foundational familiarity with both. We offer a comprehensive review that serves as a bedrock for future scholarly dialogue. We articulate key insights into how emerging generative technologies are anticipated to influence academic quality. Concurrently, we note that these technological advancements are emerging at a time of significant transformation and diversification within higher education. While it is premature to proffer definitive predictions, we argue that the impact of these technologies will be institution-specific, contingent upon the unique mission and vision of each educational entity. Our analysis and reflection suggests that institutions emphasizing critical thinking and innovation stand to gain more from the integration of Generative Artificial Intelligence technologies than those primarily focused on career preparation for students.

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The authors declare that there are no conflicts of interest present.