BazEkon - Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie

BazEkon home page

Meny główne

Autor
Geryk Marcin (Jagiellonian University)
Tytuł
Artificial Intelligence in Higher Education Industry. Just a Brief Introduction to Complexity of an Issue of Future Challenges
Źródło
Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska, 2023, z. 172, s. 201-217, bibliogr. 80 poz.
Tytuł własny numeru
Współczesne zarządzanie = Contemporary Management
Słowa kluczowe
Sztuczna inteligencja, Szkolnictwo wyższe, Uniwersytet, Nauka, Etyka
Artificial intelligence, Higher education, University, Science, Ethics
Uwagi
summ.
Abstrakt

Purpose: The article was written for review purposes in order to bring the definition of artificial intelligence closer and briefly present the possibilities of its use in management and economic sciences, as well as in higher education.

Design/methodology/approach: In order to obtain the desired information, the author conducted a research of the scientific papers on the relationship between higher education and artificial intelligence and extracted the most important conclusions and theories.

Findings: The review of the literature allowed the author to determine that there are many applications for artificial intelligence in higher education, but it should be noted that it should always be under human control and verification.

Originality/value: Apart from a brief attempt at the definition of AI and its use in higher education, the author also presents a critical perspective and possible threats, as well as proposes solutions that can regulate the ways of using artificial intelligence not only in higher education, but also in other areas of industry and social life.

Pełny tekst
Pokaż
Bibliografia
Pokaż
  1. Akerkar, R. (2014). Introduction to artificial intelligence. New Delhi: Prentice-Hall.
  2. Allison-Hope, D., Park, J., Rohwer, M. (2018). 7 Things You Should Know About Artificial Intelligence. Available at: https://www.greenbiz.com/article/7-things-you-should-know- about-artificial-intelligence.
  3. Baker, T., Smith, L., Anissa, N. (2019). Educ-AI-tion rebooted? Exploring the future of artificial intelligence in schools and colleges. Retrieved May, 12(February), p. 2020. Available at: https://media.nesta.org.uk/documents/Future_of_AI_and_education_v5_ WEB.pdf.
  4. Bernius, J.P., Krusche, S., Bruegge, B. (2022). Machine learning based feedback on textual student answers in large courses. Computers and Education: Artificial Intelligence, 3(March), p. 100081. doi:10.1016/j.caeai.2022.100081.
  5. Bérubé, M., Giannelia, T., Vial, G. (2021). Barriers to the implementation of AI in organizations: Findings from a Delphi study. Proceedings of the Annual Hawaii International Conference on System Sciences, 2020-Januar, pp. 6702-6711. doi:10.24251/hicss.2021.805.
  6. Buolamwini, J., Gebru, T. (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. Proceedings of Machine Learning Research, 81, pp. 1-15.
  7. Canhoto, A.I., Clear, F. (2020). Artificial intelligence and machine learning as business tools: A framework for diagnosing value destruction potential. Business Horizons, 63(2), pp. 183-193. doi:10.1016/j.bushor.2019.11.003.
  8. Castañeda, L., Selwyn, N. (2018). More than tools? Making sense of the ongoing digitizations of higher education. International Journal of Educational Technology in Higher Education, 15(1), p. 22. doi:10.1186/s41239-018-0109-y.
  9. Chamot, F., Geradts, Z., Haasdijk, E. (2022). Deepfake forensics: Cross-manipulation robustness of feedforward- and recurrent convolutional forgery detection methods. Forensic Science International: Digital Investigation, 40, p. 301374. doi:10.1016/j.fsidi. 2022.301374.
  10. Chatterjee, S. et al. (2019). Are CRM systems ready for AI integration? The Bottom Line, 32(2), pp. 144-157. doi:10.1108/BL-02-2019-0069.
  11. Chen, P.-S.D., Lambert, A.D., Guidry, K.R. (2010). Engaging online learners: The impact of Web-based learning technology on college student engagement. Computers & Education, 54(4), pp. 1222-1232. doi:10.1016/j.compedu.2009.11.008.
  12. Chen, X., Xie, H., Hwang, G.-J. (2020). A multi-perspective study on Artificial Intelligence in Education: grants, conferences, journals, software tools, institutions, and researchers. Computers and Education: Artificial Intelligence, 1, p. 100005. doi:10.1016/j.caeai.2020. 100005.
  13. Chiu, T.K.F. et al. (2023). Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence, 4, p. 100118. doi:10.1016/j.caeai.2022.100118.
  14. Davenport, T.H., Beck, J.C. (2002). The Attention Economy: Understanding the New Currency of Business. Brighton: Harvard Business Review Press.
  15. Dereń, A.M., Skonieczny, J., Łukaszczykiewicz, S. (2022). E-Learning as an Instrument for Managing Knowledge in the Field of Sustainable Development in a Chemical Company in Poland. Sustainability, 14(14), p. 8351. doi:10.3390/su14148351.
  16. Dwivedi, Y.K. et al. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, p. 101994. doi:10.1016/j.ijinfomgt. 2019.08.002.
  17. Eke, D.O. (2023). ChatGPT and the rise of generative AI: Threat to academic integrity? Journal of Responsible Technology, 13(February), p. 100060. doi:10.1016/j.jrt.2023. 100060.
  18. European Commission (2020). Biała Księga . W sprawie sztucznej inteligencji Europejskie podejście do doskonałości i zaufania, pp. 1-31. Available at: https://ec.europa.eu/info/sites/ default/files/commission-white-paper-artificial-intelligence-feb2020_pl.pdf.
  19. Fayed, A.E. (2021). Artificial Intelligence for marketing plan: the case for e-marketing companies. Marketing and Management of Innovations, 1, pp. 81-95. doi:10.21272/ mmi.2021.1-07.
  20. Gandomi, A., Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), pp. 137-144. doi:10.1016/j.ijinfomgt.2014.10.007.
  21. Gans, J.S. (2016). Keep Calm and Manage Disruption. Available at: https://sloanreview.mit.edu/article/keep-calm-and-manage-disruption/, 10 March 2023.
  22. García, P. et al. (2007). Evaluating Bayesian networks' precision for detecting students' learning styles. Computers & Education, 49(3), pp. 794-808. doi:10.1016/j.compedu. 2005.11.017.
  23. Haderer, B., Ciolacu, M. (2022). Education 4.0: Artificial Intelligence Assisted Task- and Time Planning System. Procedia Computer Science, 200, pp. 1328-1337. doi:10.1016/j.procs.2022.01.334.
  24. Harika, J. et al. (2022). A Review on Artificial Intelligence with Deep Human Reasoning. 2022 International Conference on Applied Artificial Intelligence and Computing (ICAAIC). IEEE, pp. 81-84. doi:10.1109/ICAAIC53929.2022.9793310.
  25. Harvard Business Review (2020). The Essential Clayton Christensen Articles. Available at: https://hbr.org/2020/01/the-essential-clayton-christensen-articles. 10 March 2023.
  26. Huang, M.-H., Rust, R.T. (2017). Technology-driven service strategy. Journal of the Academy of Marketing Science, 45(6), pp. 906-924. doi:10.1007/s11747-017-0545-6.
  27. Hwang, G.-J. et al. (2020). Vision, challenges, roles and research issues of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1, p. 100001. doi:10.1016/j.caeai.2020.100001.
  28. Kaplan, A., Haenlein, M. (2019). Siri, Siri, in my hand: Who's the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), pp. 15-25. doi:10.1016/j.bushor.2018.08.004.
  29. Koedinger, K.R., Corbett, A. (2006). Cognitive Tutors: Technology Brining Learning Science to the Classroom. In: K. Sawyer (Ed.), The Cambridge Handbook of Learning Sciences, January 2006, pp. 61-77. doi:10.1017/CBO9781107415324.004.
  30. Kotsiantis, S.B., Pierrakeas, C.J., Pintelas, P.E. (2003). Preventing Student Dropout in Distance Learning Using Machine Learning Techniques, pp. 267-274. doi:10.1007/978-3- 540-45226-3_37.
  31. Kumar, K., Thakur, G.S.M. (2012). Advanced Applications of Neural Networks and Artificial Intelligence: A Review. International Journal of Information Technology and Computer Science, 4(6), pp. 57-68. doi:10.5815/ijitcs.2012.06.08.
  32. Lacity, M.C. (2017) Robotic Process Automation and Risk Mitigation: The Definitive Guide. Ashford: SB Publishing.
  33. Laupichler, M.C. et al. (2022). Artificial intelligence literacy in higher and adult education: A scoping literature review. Computers and Education: Artificial Intelligence, 3, p. 100101. doi:10.1016/j.caeai.2022.100101.
  34. Lee, I., Shin, Y.J. (2020). Machine learning for enterprises: Applications, algorithm selection, and challenges. Business Horizons, 63(2), pp. 157-170. doi:10.1016/j.bushor. 2019.10.005.
  35. Lem, S. (2020) Summa Technologiae. Kraków: Wydawnictwo Literackie.
  36. Lindsay Tjepkema (2016). What is Artificial Intelligence (AI) Marketing? A Complete Guide. Available at: https://emarsys.com/learn/blog/artificial-intelligence-marketing- solutions/, 10 March 2023.
  37. Liu, Z., Wang, H., Wang, S. (2022). Cross-Domain Local Characteristic Enhanced Deepfake Video Detection, pp. 3412-3429. Available at: http://arxiv.org/abs/2211.03346.
  38. Loeckx, J. (2016). Blurring Boundaries in Education: Context and Impact of MOOCs. The International Review of Research in Open and Distributed Learning, 17(3). doi:10.19173/irrodl.v17i3.2395.
  39. Luckin, R. et al. (2022). Empowering educators to be AI-ready. Computers and Education: Artificial Intelligence, 3, p. 100076. doi:10.1016/j.caeai.2022.100076.
  40. Luckin, R., Holmes, W., Griffiths, Mark, Forcier, L.B. (2016). The Open University's repository of research publications and other research outputs. London: Pearson Education.
  41. Martín-Núñez, J.L. et al. (2023). Does intrinsic motivation mediate perceived artificial intelligence (AI) learning and computational thinking of students during the COVID-19 pandemic? Computers and Education: Artificial Intelligence, 4, p. 100128. doi:10.1016/j.caeai.2023.100128.
  42. McCarthy, B., Chui, M., Bughin, J. (2017) A Survey of 3,000 Executives Reveals How Businesses Succeed with AI. Available at: https://hbr.org/2017/08/a-survey-of-3000- executives-reveals-how-businesses-succeed-with-ai, 10 March 2023.
  43. McCarthy, J. et al. (1955). A proposal for the Dartmouth summer research project on artificial intelligence. Available at: https://www-formal.stanford.edu/jmc/history/ dartmouth/dartmouth.html.
  44. McCarthy, J. (2007). What is artificial intelligence? Available at: https://www- formal.stanford.edu/jmc/whatisai.pdf.
  45. Micro-Credentials at SUNY (n.d.). Available at: https://system.suny.edu/academic- affairs/microcredentials/, 10 March 2023.
  46. Ng, D.T.K. et al. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, p. 100041. doi:10.1016/j.caeai.2021.100041.
  47. O'Shea, T., Self, J. (1983) Learning and Teaching with Computers: Artificial Intelligence in Education. Prentice-Hall.
  48. Ouyang, F., Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, p. 100020. doi:10.1016/ j.caeai.2021.100020.
  49. Pai, K.-C. et al. (2021). An application of Chinese dialogue-based intelligent tutoring system in remedial instruction for mathematics learning. Educational Psychology, 41(2), pp. 137-152. doi:10.1080/01443410.2020.1731427.
  50. Pelletier, K. et al. (2021). Horizon Report 2021, EDUCAUSE Review. Available at: https://www.educause.edu/horizon-report-teaching-and-learning-2021.
  51. Peres, R. et al. (2023). On ChatGPT and beyond: How generative artificial intelligence may affect research, teaching, and practice. International Journal of Research in Marketing, pp. 1-7. doi:10.1016/j.ijresmar.2023.03.001.
  52. Price, S., Flach, P.A. (2017). Computational support for academic peer review. Communications of the ACM, 60(3), pp. 70-79. doi:10.1145/2979672.
  53. Rahimi, F., Talebi Bezmin Abadi, A. (2023). ChatGPT and Publication Ethics. Archives of Medical Research, 54(3), pp. 272-274. doi:10.1016/j.arcmed.2023.03.004.
  54. Rai, A. (2020). Explainable AI: from black box to glass box. Journal of the Academy of Marketing Science, 48(1), pp. 137-141. doi:10.1007/s11747-019-00710-5.
  55. Rich, E., Knight, K. (1991) Artificial Intelligence. New York: Mcgraw Hill Higher Education.
  56. Rouhani, S. et al. (2016). The impact model of business intelligence on decision support and organizational benefits. Journal of Enterprise Information Management, 29(1), pp. 19-50. doi:10.1108/JEIM-12-2014-0126.
  57. Russel, S.J., Norvig, P. (2010). Artificial Intelligence. A Modern Approach. New Jersey: Pearson Education.
  58. Scott, P. (2000). Globalisation and Higher Education: Challenges for the 21st Century. Journal of Studies in International Education, 4(1), pp. 3-10. doi:10.1177/ 102831530000400102.
  59. Seldon, A., Abidoye, O. (2018). The Fourth Education Revolution Reconsidered: Will Artificial Intelligence Enrich or Diminish Humanity? London: Legend Press.
  60. Selwyn, N. (2016). Is Technology Good for Education? London: Polity.
  61. Solon, O. (2018). Google's robot assistant now makes eerily lifelike phone calls for you. Available at: https://www.theguardian.com/technology/2018/may/08/google-duplex- assistant-phone-calls-robot-human, 10 March 2023.
  62. Southworth, J. et al. (2023). Developing a model for AI Across the curriculum: Transforming the higher education landscape via innovation in AI literacy. Computers and Education: Artificial Intelligence, 4, p. 100127. doi:10.1016/j.caeai.2023.100127.
  63. Spector, J.M., Polson, M.C., Muraida, D.J. (1993) Automating Instructional Design: Concepts and Issues. Englewood Cliffs: Educational Technology Pubns.
  64. Su, J., Zhong, Y., Ng, D.T.K. (2022). A meta-review of literature on educational approaches for teaching AI at the K-12 levels in the Asia-Pacific region. Computers and Education: Artificial Intelligence, 3, p. 100065. doi:10.1016/j.caeai.2022.100065.
  65. Sułkowski, Ł., Kaczorowska-Spychalska, D. (2021). Determinants of the adoption of AI wearables - practical implications for marketing. Human Technology, 17(3), pp. 294-320. doi:10.14254/1795-6889.2021.17-3.6.
  66. Swanson, E.B. (1988). Information System Implementation: Bridging the Gap Between Design and Utilization. Computer Science [Preprint].
  67. Tan, S.C., Lee, A.V.Y., Lee, M. (2022). A systematic review of artificial intelligence techniques for collaborative learning over the past two decades. Computers and Education: Artificial Intelligence, 3, p. 100097. doi:10.1016/j.caeai.2022.100097.
  68. The International Artificial Intelligence in Education Society (n.d.). Available at: https://iaied.org/about, 10 March 2023.
  69. Thomaz, A.L., Breazeal, C. (2008). Teachable robots: Understanding human teaching behavior to build more effective robot learners. Artificial Intelligence, 172(6-7), pp. 716-737. doi:10.1016/j.artint.2007.09.009.
  70. Tolan, S. et al. (2019). Why Machine Learning May Lead to Unfairness. Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law. New York, NY, USA: ACM, pp. 83-92. doi:10.1145/3322640.3326705.
  71. Tuomi, I. (2018) The Impact of Artificial Intelligence on Learning, Teaching, and Education. Luxembourg: Publications Office of the European Union. doi:10.2760/12297.
  72. Turing, A.M. (1950). Computing Machinery and Intelligence. Mind, 59(236), pp. 433-460. Available at: http://www.jstor.org/stable/2251299.
  73. Della Ventura, M. (2017). Creating Inspiring Learning Environments by means of Digital Technologies: A Case Study of the Effectiveness of WhatsApp in Music Education. EAI Endorsed Transactions on e-Learning, 4(14), p. 152906. doi:10.4108/eai.26-7- 2017.152906.
  74. Verma, S. et al. (2021). Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Information Management Data Insights, 1(1), p. 100002. doi:10.1016/j.jjimei.2020.100002.
  75. Wiener, N. (1950). Cybernetics: or the Control and Communication in the Animal and the Machine. Cambridge: The MIT Press.
  76. Wirth, N. (2018). Hello marketing, what can artificial intelligence help you with? International Journal of Market Research, 60(5), pp. 435-438. doi:10.1177/ 1470785318776841.
  77. Xiao, M., Yi, H. (2021). Building an efficient artificial intelligence model for personalized training in colleges and universities. Computer Applications in Engineering Education, 29(2), pp. 350-358. doi:10.1002/cae.22235.
  78. Yavuz, M. (2022). Digital Transformation and Productivity in Higher Education.
  79. Zawacki-Richter, O. et al. (2019). Systematic review of research on artificial intelligence applications in higher education - where are the educators? International Journal of Educational Technology in Higher Education, 16(1), p. 39. doi:10.1186/s41239-019-0171-0.
  80. Zhai, X. et al. (2021). A Review of Artificial Intelligence (AI) in Education from 2010 to 2020. Complexity. N. Cai (ed.), pp. 1-18. doi:10.1155/2021/8812542.
Cytowane przez
Pokaż
ISSN
1641-3466
Język
eng
URI / DOI
http://dx.doi.org/10.29119/1641-3466.2023.172.13
Udostępnij na Facebooku Udostępnij na Twitterze Udostępnij na Google+ Udostępnij na Pinterest Udostępnij na LinkedIn Wyślij znajomemu