Artificial intelligence in higher education

Capa

Citar

Texto integral

Acesso aberto Acesso aberto
Acesso é fechado Acesso está concedido
Acesso é fechado Somente assinantes

Resumo

This article is devoted to the application of artificial intelligence technology in higher education. The relevance of the topic is due to the fact that at present there is a significant gap between interest in the use of artificial intelligence in education and its real implementation. The scientific and practical works of Russian and foreign scientists in the field of economics and ethics of artificial intelligence in education were used as the methodological basis of the study. The authors identify two main directions of the influence of artificial intelligence on the higher education system. The article discusses artificial intelligence tools in education by subjects of application. The authors focus on identifying the economic and ethical issues of introducing artificial intelligence algorithms into the higher education system. It is necessary to apply an interdisciplinary approach to teaching today's students how to interact with artificial intelligence technology. Particular attention is paid to the problems of application the ChatGPT program in the educational process. The results of the scientific research can be useful for specialists in the field of artificial intelligence, scientists whose area of scientific interest is the study of the processes of improving the economy and ethics of higher education.

Sobre autores

Pavel Lukichyov

Baltic State Technical University «VOENMEH» named after D.F. Ustinov

Email: loukitchev20@mail.ru
профессор кафедры менеджмента организации, доктор экономических наук, профессор

Oleg Chekmarev

Saint-Petersburg State Agrarian University

Email: oleg1412@mail.ru
профессор кафедры организации аграрного производства и менеджмента, доктор экономических наук, доцент

Bibliografia

  1. Защитина Е.К., Плешивцева А.А. Экономическая эффективность третичного сектора экономики (на примере туристической и образовательной сферы) // Вопросы инновационной экономики. – 2022. – № 4. – c. 2703-2716. – doi: 10.18334/vinec.12.4.116711.
  2. Education in 2030. The $10 Trillion dollar Question. Holoniq.com. [Электронный ресурс]. URL: https://www.holoniq.com/2030 (дата обращения: 23.01.2023).
  3. Правительство РФ (2021a) Распоряжение Правительства Российской Федерации от 02.12.2021 № 3427-р «Об утверждении стратегического направления в области цифровой трансформации образования, относящейся к сфере деятельности Министерства просвещения Российской Федерации». Publication.pravo.gov.ru. [Электронный ресурс]. URL: http://publication.pravo.gov.ru/Document/View/0001202112070025/ (дата обращения: 29.01.2023).
  4. Правительство РФ (2021b) Распоряжение Правительства РФ от 21.12.2021 № 3759-р «Об утверждении стратегического направления в области цифровой трансформации науки и высшего образования». Garant.ru. [Электронный ресурс]. URL: https://www.garant.ru/products/ipo/prime/doc/403203308/ (дата обращения: 29.01.2023).
  5. Шугаль Н.Б., Бондаренко Н.В., Варламова Т.А., Волкова Г.Л., Шкалева Е.В., Шматко Н.А. Цифровая среда в образовательных организациях различных уровней. / Аналитический доклад. - М: НИУ ВШЭ, 2023. – 164 c.
  6. Астратова Г.В. Цифровизация и ключевые мейнстримы развития высшего образования // Цифровой контент социального и экосистемного развития экономики: Сборник трудов Международной научно-практической конференции. Симферополь, 2021. – c. 16-19.
  7. Tahiru F. Ai in education: A systematic literature review // Journal of Cases on Information Technology. – 2021. – № 1. – p. 1-20. – doi: 10.4018/JCIT.2021010101.
  8. Zawacki-Richter O., Marín V.I., Bond M., Gouverneur F. Systematic review of research on artificial intelligence applications in higher education – where are the educators? // International Journal of Educational Technology in Higher Education. – 2019. – № 1. – doi: 10.1186/s41239-019-0171-0.
  9. Bates T., Cobo C., Mariño O., Wheeler S. Can artificial intelligence transform higher education? // International Journal of Educational Technology in Higher Education. – 2020. – № 42. – doi: 10.1186/s41239-020-00218-x.
  10. Wheeler S. Digital learning in organizations: Help your workforce capitalize on technology. Kogan Page Publishers. – 2019
  11. Gratton L. How leaders face the future of work // MIT Sloan Management Review. – 2018. – № 3. – p. 1-4.
  12. Хоменко Е.Б., Ватутина Л.А., Злобина Е.Ю. Современные тенденции цифровой трансформации промышленных предприятий // Вестник Удмуртского университета. Серия Экономика и право. – 2022. – № 4. – c. 676-682. – doi: 10.35634/2412-9593-2022-32-4-676-682.
  13. Xue M., Cao X., Feng X., Gu B., Zhang Y. Is College Education Less Necessary with AI? Evidence from Firm-Level Labor Structure Changes // Journal of Management Information Systems. – 2022. – № 3. – p. 865-905. – doi: 10.1080/07421222.2022.2096542.
  14. Dignum V. The role and challenges of education for responsible AI // London Review of Education. – 2021. – № 1. – p. 1-11. – doi: 10.14324/LRE.19.1.01.
  15. Baker T., Smith L. Educ-AI-tion rebooted? Exploring the future of artificial intelligence in schools and colleges. Retrieved from Nesta Foundation website. [Электронный ресурс]. URL: https://media.nesta.org.uk/documents/Future_of_AI_and_education_v5_WEB.pdf.
  16. Checmarev O.P., Kovalenko E.V., Sudorgina I.G., Timoshenko S.A., Lukichev P.M. Innovation in the Digitalization of Agroindustry. / The Challenge of Sustainability in Agricultural Systems Том 205, Volume 1. - Heidelberg: Springer International Publishing, 2021. – 257-265 p.
  17. Klutka J. et al. Artificial Intelligence in Higher Education: Current Uses and Future Applications. - Louisville: Learning house, 2018.
  18. Chen X., Zou D., Xie H., Cheng G., Liu C. Two Decades of Artificial Intelligence in Education // Educational Technology and Society. – 2022. – № 1. – p. 28-47.
  19. Guan C., Mou J., Jiang Z. Artificial intelligence innovation in education: A Twenty-year data-driven historical analysis // International Journal. – 2020. – № 4. – p. 134-147. – doi: 10.1016/j.ijis.2020.09.001.
  20. Chen X., Zou D., Xie H., Cheng G. Twenty years of personalized language learning: Topic modeling and knowledge mapping // Educational Technology and Society. – 2021. – № 1. – p. 205-222. – doi: 10.2307/26977868.
  21. Tsai S.C., Chen C.H., Shiao Y.T., Ciou J.S., Wu T.N. Precision education with statistical learning and deep learning: a case study in Taiwan // International Journal of Educational Technology in Higher Education. – 2020. – № 1. – p. 1-13. – doi: 10.1186/s41239-020-00186-2.
  22. The lessons of learning loss. The World Ahead 2023. November 18th 2022
  23. Lynch J. How AI Will Destroy Education. Buzzrobot.com. [Электронный ресурс]. URL: https://buzzrobot.com/how-ai-will-destroy-education-20053b7b88a6.
  24. Лукичев П.М., Чекмарев О.П. Экономика искусственного интеллекта: возможности и проблемы использования в здравоохранении // Вопросы инновационной экономики. – 2022. – № 2. – c. 1111-1130. – doi: 10.18334/vinec.12.2.114782.
  25. Nawaz Raheel, Quanbin Sun, Matthew Shardlow, Georgios Kontonatsios, Naif R. Aljohani, Anna Visvizi, Saeed-Ul Hassan Leveraging AI and Machine Learning for National Student Survey: Actionable Insights from Textual Feedback to Enhance Quality of Teaching and Learning in UK’s Higher Education // Applied Sciences. – 2022. – № 1. – p. 514. – doi: 10.3390/app12010514.
  26. Cramer H., Garcia-Gathright J., Springer A., Reddy S. Assessing and addressing algorithmic bias in practice // Interactions. – 2018. – № 6. – p. 58-63. – doi: 10.1145/3278156.
  27. Moore G.C., Benbasat I. Development of an instrument to measure the perceptions of adopting an information technology innovation // Information Systems Research. – 1991. – № 3. – p. 192-222. – doi: 10.1287/isre.2.3.192.
  28. Madsen M., Gregor S. Measuring human-computer trust // In 11th Australasian conference on information systems. Brisbane, Australia, 2000. – p. 6-8.
  29. Leur R. Challenges and approaches related to AI-driven grading in higher education: the procedural trust of students. - 2022
  30. Bygstad B., Øvrelid E., Ludvigsen S., Dæhlen M. From dual digitalization to digital learning space: Exploring the digital transformation of higher education // Computers Education. – 2022. – p. 104463.
  31. Köbis L., Mehner C. Ethical Questions Raised by AI-Supported Mentoring in Higher Education // Frontiers in Artificial Intelligence. – 2021. – № 21. – doi: 10.3389/frai.2021.624050.
  32. Borenstein J., Howard A. Emerging challenges in AI and the need for AI ethics education // AI and Ethics. – 2021. – № 1. – p. 61-65. – doi: 10.1007/s43681-020-00002-7.
  33. Лукичев П.М. Рынок труда будущего. - Санкт-Петербург: ФГАОУ ВО «Санкт-Петербургский политехнический университет Петра Великого», 2021. – 219 c.
  34. Holmes W., Bialik M., Fadel C. Artificial intelligence in education. - Boston, MA: The Center for Curriculum Redesign Boston, 2019.
  35. Manyika J., Chui M., Miremadi M., Bughin J., George K., Willmott P., Dewhurst M. A future that works: Automation, employment, and productivity. - New York: McKinsey Global Institute, 2017. – 1-28 p.
  36. Korinek A, Stiglitz J.E. Nber. / In: Agrawal A., Gans J., Goldfarb A.The economics of artificial intelligence. - Chicago: University of Chicago Press, 2019. – 349-390 p.
  37. Krugman P. Does ChatGPT Mean Robots Are Coming For the Skilled Jobs? // New York Times. - 2022
  38. Graeber D. Bullshit Jobs: A Theory. - London: Penguin UK, 2018. – 368 p.
  39. Brynjolfsson E. The turing trap: The promise peril of human-like artificial intelligence // Daedalus. – 2022. – № 2. – p. 272-287.
  40. Edwards B.I., Cheok A.D. Why not robot teachers: Artificial intelligence for addressing teacher shortage // Applied Artificial Intelligence. – 2018. – № 4. – p. 345-360. – doi: 10.1080/08839514.2018.1464286.

Declaração de direitos autorais © Lukichyov P.M., Chekmarev O.P., 2023

Este site utiliza cookies

Ao continuar usando nosso site, você concorda com o procedimento de cookies que mantêm o site funcionando normalmente.

Informação sobre cookies