The role of artificial intelligence in digital education

Rosak-Szyrocka, Joanna

doi:10.29119/1641-3466.2024.195.29

Artykuł - szczegóły

Tytuł artykułu

The role of artificial intelligence in digital education

Autorzy

Rosak-Szyrocka Joanna

Treść / Zawartość

Pełne teksty:

Pobierz

Identyfikatory

DOI

10.29119/1641-3466.2024.195.29

Warianty tytułu

Języki publikacji

Abstrakty

Purpose: The article presents a bibliometric analysis of studies in the artificial intelligence field, with the principal source of scientific articles selected being the academic platform Scopus. Design/methodology/approach: The content of 3365 open access research articles has been taken into consideration from 2019 and 2024 years. The search documents related to “artifical intelligence” “in” “education” issue in title, abstract and keywords. The analysis was performed using the VosWiever program. Findings: The study showed that AI assesses students' skills and requirements using machine learning, and then utilizes the findings of that analysis to develop and disseminate personalized or tailored information that improves learning via increased retention and uptake. AI improves learning for students by providing them with possibilities for experiential or hands-on learning, particularly when paired with other technologies like virtual reality, 3-D, gaming, and simulation. Research limitations/implications: The first limitation of the study is a result of the papers and reviews that were selected that deal with artificial intelligence. Since a broad variety of scientific fields are included in the field of artificial intelligence, findings may vary if publications from other domains are completely taken into account. Consequently, one should use extreme caution when extrapolating the study's conclusions to the vast domain of artificial intelligence. Another limitation is the research timeline (2019-2024); future results may vary since we anticipate that new topics, concepts, and techniques will emerge in the expanding field of artificial intelligence, which will significantly change the outcomes of our study. Finally, since the study's data came from Scopus, it's possible that this research is impacted by some of Scopus's restrictions. Practical implications: The manuscript can be a guide for universities on what students need for AI as well as how to improve the didactic process. Originality/value: Manuscript fills the gap in the analysis of what is the main role of AI in the education area from the student life-cycle and university effectiveness.

Słowa kluczowe

digitalization education artifical intelligence Wosviewer analysis

cyfryzacja edukacja sztuczna inteligencja analiza Wosviewer

Wydawca

Wydawnictwo Politechniki Śląskiej

Czasopismo

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

Rocznik

2024

Tom

z. 195

Strony

477--499

Opis fizyczny

Bibliogr. 81 poz.

Twórcy

autor

Rosak-Szyrocka Joanna

Joanna.rosak-szyrocka@wz.pcz.pl

Czestochowa University of Technology

https://orcid.org/0000-0002-5548-6787

Bibliografia

1. Abduljabbar, R., Dia, H., Liyanage, S., Bagloee, S.A., (2019). Applications of Artificial Intelligence in Transport: An Overview. Sustainability, vol. 11, no. 1, p. 189.
2. Abulibdeh, A., Zaidan, E., Abulibdeh, R. (2024). Navigating the confluence of artificial intelligence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical dimensions. 0959-6526, vol. 437, p. 140527. Available from: https://www.sciencedirect.com/science/article/pii/s0959652623046851.
3. Adiguzel, T., Kaya, M.H., Cansu, F.K. (2023). Revolutionizing education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology, vol. 15, no. 3, ep429.
4. Ahmad, S.F., Alam, M.M., Rahmat, M.K., Mubarik, M.S., Hyder, S.I. (2022). Academic and Administrative Role of Artificial Intelligence in Education. Sustainability, vol. 14, no. 3, p. 1101.
5. Alam, A. (2021). Possibilities and Apprehensions in the Landscape of Artificial Intelligence in Education. 2021 International Conference on Computational Intelligence and Computing Applications (ICCICA), IEEE.
6. Alam, A. (2021-2021). Possibilities and Apprehensions in the Landscape of Artificial Intelligence in Education. 2021 International Conference on Computational Intelligence and Computing Applications (ICCICA), IEEE, pp. 1-8.
7. Alpaydin, E. (2021). Machine learning, revised and updated edition. New York: MIT Press.
8. Aoun, J.E. (2017). Robot-Proof. Available from: https://cir.nii.ac.jp/crid/ 1360855570699080064.
9. Artificial intelligence in society (2019).
10. Bahadir, E. (2016). Using Neural Network and Logistic Regression Analysis to Predict Prospective Mathematics Teachers' Academic Success upon Entering Graduate Education. Educational Sciences: Theory and Practice, vol. 16, no. 3, pp. 943-964. Available from: https://eric.ed.gov/?id=ej1115064.
11. Baker, R.S., D'Mello, S.K., Rodrigo, M.T., Graesser, A.C. (2010). Better to be frustrated than bored: The incidence, persistence, and impact of learners’ cognitive–affective states during interactions with three different computer-based learning environments. International Journal of Human-Computer Studies, vol. 68, no. 4, pp. 223-241. Available from: https://www.sciencedirect.com/science/article/pii/s1071581909001797?casa_token= m9ltvkbhezeaaaaa:tedjfavjmitmzxbj8qoeryrrkf7jjm2u4ftn9h8odrp9r-jb-p-ezwrmyunmhfqvpotrvtw9.
12. Bakhov, I., Opolska, N., Bogus, M., Anishchenko, V., Biryukova, Y. (2021). Emergency Distance Education in the Conditions of COVID-19 Pandemic: Experience of Ukrainian Universities. Education Sciences, vol. 11, no. 7, p. 364. Available from: https://www.mdpi.com/2227-7102/11/7/364.
13. Bates, L., Hayes, H. (2017). Using the Student Lifecycle Approach to Enhance Employability: An Example from Criminology and Criminal Justice. Asia-Pacific Journal of Cooperative Education, vol. 18, no. 2, pp. 141-151. Available from: https://eric.ed.gov/?id=ej1151139.
14. Bholat, D., Susskind, D. (2021). The assessment: artificial intelligence and financial services. Oxford Review of Economic Policy, vol. 37, no. 3, pp. 417-434.
15. Bhutoria, A. (2022). Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model. 2666-920X, vol. 3, p. 100068. Available from: https://www.sciencedirect.com/science/article/pii/ s2666920x22000236.
16. Chan, C.K.Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, vol. 20, no. 1, pp. 1-25. Available from: https://link.springer.com/ article/10.1186/s41239-023-00408-3.
17. Chen, L., Chen, P., Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, vol. 8, pp. 75264-75278.
18. Chen, X., Xie, H., Di Zou, Hwang, G.-J. (2020). Application and theory gaps during the rise of Artificial Intelligence in Education, 2666-920X, vol. 1, p. 100002. Available from: https://www.sciencedirect.com/science/article/pii/s2666920x20300023.
19. Chmyr, V., Bhinder, N. (2023). AI in the Higher Military Institutions: Challenges and Perspectives for Military Engineering Training. Rupkatha Journal on Interdisciplinary Studies in Humanities, vol. 15, no. 4.
20. Cope, B., Kalantzis, M., Searsmith, D. (2021). Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies. Educational Philosophy and Theory, vol. 53, no. 12, pp. 1229-1245.
21. Da Tan, Y., Cheah, C.W. (2021). Developing a gamified AI-enabled online learning application to improve students’ perception of university physics, 2666-920X, vol. 2, p. 100032. Available from: https://www.sciencedirect.com/science/article/pii/ s2666920x21000266.
22. Danylchenko-Cherniak, O. (2023). Creative and collaborative learning during Russian-Ukrainian war period: philological aspects. Philological Treatises, vol. 15, no. 1, pp. 51-61. Available from: http://tractatus.sumdu.edu.ua/index.php/journal/article/view/1069.
23. Du Boulay, B. (2016). Artificial Intelligence as an Effective Classroom Assistant. IEEE Intelligent Systems, vol. 31, no. 6, pp. 76-81.
24. Educ-AI-tion rebooted? Exploring the future of artificial intelligence in schools and colleges (2019).
25. Eggmann, F., Weiger, R., Zitzmann, N.U., Blatz, M.B. (2023). Implications of large language models such as ChatGPT for dental medicine. Journal of esthetic and restorative dentistry: official publication of the American Academy of Esthetic Dentistry … [et al.], vol. 35, no. 7, pp. 1098-1102.
26. Firat, M. (2023). Integrating AI Applications into Learning Management Systems to Enhance e-Learning. Instructional Technology and Lifelong Learning, vol. 4, no. 1, pp. 1-14. Available from: https://dergipark.org.tr/en/pub/itall/article/1244453.
27. Garg, T. (2020). Artificial Intelligence in Medical Education. The American Journal of Medicine, vol. 133, no. 2, e68.
28. Gligorea, I., Cioca, M., Oancea, R., Gorski, A.-T., Gorski, H., Tudorache, P. (2023). Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review. Education Sciences, vol. 13, no. 12, p. 1216. Available from: https://www.mdpi.com/2227-7102/13/12/1216.
29. Gruševá, E., Blašková, V. (2022). Education as a factor influencing the economic growth of the V4 countries. Review of Applied Socio-Economic Research, vol. 24, no. 2, pp. 58-69. Available from: https://www.reaser.eu/ojs/ojs-3.1.2-1/index.php/reaser/article/view/139.
30. Halagatti, M., Gadag, S., Mahantshetti, S., Hiremath, C.V., Tharkude, D., Banakar, V. (eds.). Smart Analytics, Artificial Intelligence and Sustainable Performance Management in a Global Digitalised Economy. Emerald Publishing Limited; iUniverse.
31. Hinojo-Lucena, F.-J., Aznar-Díaz, I., Cáceres-Reche, M.-P., Romero-Rodríguez, J.-M. (2019). Artificial Intelligence in Higher Education: A Bibliometric Study on its Impact in the Scientific Literature. Education Sciences, vol. 9, no. 1, p. 51. Available from: https://www.mdpi.com/2227-7102/9/1/51.
32. Holmes, J., Moraes, O.R., Rickards, L., Steele, W., Hotker, M., Richardson, A. (2022). Online learning and teaching for the SDGs – exploring emerging university strategies. International Journal of Sustainability in Higher Education, vol. 23, no. 3, pp. 503-521.
33. Holmes, W., Anastopoulou, S., Schaumburg, H., Mavrikis, M. (2018). Technology-enhanced Personalised Learning: Untangling the Evidence. Stuttgart: Robert Bosch Stiftung GmbH. Available from: https://oro.open.ac.uk/56692/.
34. Holmes, W., Bialik, M., Fadel, C. (2019). Artificial intelligence in education. Promises and implications for teaching and learning. Boston, MA: Center for Curriculum Redesign.
35. Hwang, G.-J., Xie, H., Wah, B.W., Gašević, D. (2020). Vision, challenges, roles and research issues of Artificial Intelligence in Education, 2666-920X, vol. 1, p. 100001. Available from: https://www.sciencedirect.com/science/article/pii/s2666920x20300011.
36. Ivanashko, O., Kozak, A., Knysh, T., Honchar, K. (2024). The Role of Artificial Intelligence in Shaping the Future of Education: Opportunities and Challenges. Futurity Education, vol. 4, no. 1, pp. 126-146. Available from: https://futurity-education.com/index.php/fed/article/view/262.
37. Kamalov, F., Santandreu Calonge, D., Gurrib, I. (2023). New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution. Sustainability, vol. 15, no. 16, p. 12451. Available from: https://www.mdpi.com/2071-1050/15/16/12451.
38. Kamruzzaman, M.M., Alanazi, S., Alruwaili, M., Alshammari, N., Elaiwat, S., Abu-Zanona, M., Innab, N., Mohammad Elzaghmouri, B., Ahmed Alanazi, B. (2023). AI- and IoT-Assisted Sustainable Education Systems during Pandemics, such as COVID-19, for Smart Cities. Sustainability, vol. 15, no. 10, p. 8354. Available from: https://www.mdpi.com/2071-1050/15/10/8354.
39. Lin, C.-C., Huang, A.Y.Q., Lu, O.H.T. (2023). Artificial intelligence in intelligent tutoring systems toward sustainable education: a systematic review. Smart Learning Environments, vol. 10, no. 1, pp. 1-22. Available from: https://link.springer.com/article/10.1186/s40561-023-00260-y.
40. Loeckx, J. (2016). Blurring Boundaries in Education: Context and Impact of MOOCs. International Review of Research in Open and Distributed Learning, vol. 17, no. 3, pp. 92-121.
41. Luckin, R. (2017). Towards artificial intelligence-based assessment systems. Nature Human Behaviour, vol. 1, no. 3.
42. Luckin, R., Holmes, W. (2016). Intelligence Unleashed: An argument for AI in Education. London, UK. Available from: https://discovery.ucl.ac.uk/id/eprint/1475756/.
43. Mackenzie, A. (2017). Machine learners. Archaeology of a data practice. Cambridge (Estados Unidos), London: The MIT Press.
44. Mao, J., Chen, B., Liu, J.C. (2024). Generative Artificial Intelligence in Education and Its Implications for Assessment. TechTrends, vol. 68, no. 1, pp. 58-66. Available from: https://idp.springer.com/authorize/casa?redirect_uri=https://link.springer.com/article/10.1007/s11528-023-00911-4&casa_token=epamwg5wxewaaaaa:md-z9asr-bo8b5s63ffvnyf2vjggv31ysr8wqhv10svnywe25xz12uelxddgdsesziytsyqhjpuf6ic.
45. Mhlanga, D. (2023). Open AI in Education, the Responsible and Ethical Use of ChatGPT Towards Lifelong Learning. FinTech and Artificial Intelligence for Sustainable Development, pp. 387-409. Available from: https://link.springer.com/chapter/10.1007/978-3-031-37776-1_17.
46. Navajas, A., Echarri, I., Gandía, L.M., Pozuelo, J., Cascarosa, E. (2024). Life Cycle Assessment in Higher Education: Design and Implementation of a Teaching Sequence Activity. Sustainability, vol. 16, no. 4, p. 1614. Available from: https://www.mdpi.com/2071-1050/16/4/1614.
47. Navarro-Espinosa, J.A., Vaquero-Abellán, M., Perea-Moreno, A.-J., Pedrós-Pérez, G., Del Martínez-Jiménez, M.P., Aparicio-Martínez, P. (2022). Gamification as a Promoting Tool of Motivation for Creating Sustainable Higher Education Institutions. International Journal of Environmental Research and Public Health, vol. 19, no. 5, p. 2599. Available from: https://www.mdpi.com/1660-4601/19/5/2599.
48. OECD Education Working Papers (2024).
49. OECD skills outlook 2019: Thriving in a digital world (2019). Available from: https://www.voced.edu.au/content/ngv:82995.
50. Ouyang, F., Jiao, P. (2021). Artificial intelligence in education: The three paradigms, 2666-920X, vol. 2, p. 100020. Available from: https://www.sciencedirect.com/science/ article/pii/s2666920x2100014x.
51. Venkateswaran, P.S., Ayasrah, F.T.M., Nomula, V.K., Paramasivan, P., Anand, P., Bogeshwaran, K. Applications of Artificial Intelligence Tools in Higher Education. In: Data-Driven Decision Making for Long-Term Business Success (pp. 124-136), IGI Global. Available from: https://www.igi-global.com/chapter/applications-of-artificial-intelligence-tools-in-higher-education/335567.
52. Pantelimon, F.-V., Bologa, R., Toma, A., Posedaru, B.-S. (2021). The Evolution of AI-Driven Educational Systems during the COVID-19 Pandemic. Sustainability, vol. 13, no. 23, p. 13501. Available from: https://www.mdpi.com/2071-1050/13/23/13501.
53. Perez, S., Massey-Allard, J., Butler, D., Ives, J., Bonn, D., Yee, N., Roll, I. (2017). Identifying Productive Inquiry in Virtual Labs Using Sequence Mining. Artificial intelligence in education. 18th international conference, aied. Springer, pp. 287-298. Available from: https://link.springer.com/chapter/10.1007/978-3-319-61425-0_24.
54. Rahmani, A.M., Azhir, E., Ali, S., Mohammadi, M., Ahmed, O.H., Yassin Ghafour, M., Hasan Ahmed, S., Hosseinzadeh, M. (2021). Artificial intelligence approaches and mechanisms for big data analytics: a systematic study. PeerJ Computer Science, vol. 7, e488. Available from: https://peerj.com/articles/cs-488/.
55. Regulating artificial intelligence in finance: Putting the human in the loop. Sydney Law Review.
56. Roopal Shrivastava (2023). Role of Artificial Intelligence in Future of Education. International Journal of Professional Business Review, vol. 8, no. 1, p. 2. Available from: https://dialnet.unirioja.es/servlet/articulo?codigo=8789502.
57. Rosak-Szyrocka, J. (2024). The Era of Digitalization in Education where do Universities 4.0 Go? Management Systems in Production Engineering, vol. 32, no. 1, pp. 54-66.
58. Rosak-Szyrocka, J., Apostu, S.A., Ali Turi, J., Tanveer, A. (2022a). University 4.0 Sustainable Development in the Way of Society 5.0. Sustainability, vol. 14, no. 23, p. 16043. Available from: https://www.mdpi.com/2071-1050/14/23/16043.
59. Rosak-Szyrocka, J., Zywiolek, J., Zaborski, A., Chowdhury, S., Hu, Y.-C. (2022b). Digitalization of Higher Education Around the Globe During Covid-19. IEEE Access, vol. 10, pp. 59782-59791.
60. Rosak-Szyrocka, J., Żywiołek, J., Nayyar, A., Naved, M. (2024). The role of sustainability & artificial intelligence in education improvement. Boca Raton, FL: CRC Press.
61. Ruiz-Rojas, L.I., Acosta-Vargas, P., De-Moreta-Llovet, J., Gonzalez-Rodriguez, M. (2023). Empowering Education with Generative Artificial Intelligence Tools: Approach with an Instructional Design Matrix. Sustainability, vol. 15, no. 15, p. 11524. Available from: https://www.mdpi.com/2071-1050/15/15/11524.
62. Salmon, G. (2008). E-moderating. The key to teaching and learning online. London/NewYork: Routledge Falmer.
63. Santos, G., Magalhaes, M.D., Carvalho, S., Pinto, R.J., Felix, M.J., Rosak-Szyrocka, J. (2022). Digital transformation and global inequality. International Journal for Quality Research, vol. 16, no. 4, pp. 1297-1314.
64. Sanusi, I.T., Olaleye, S.A., Agbo, F.J., Chiu, T.K. (2022). The role of learners competencies in artificial intelligence education, 2666-920X, vol. 3, p. 100098. Available from: https://www.sciencedirect.com/science/article/pii/s2666920x22000534.
65. Seldon, A., Abidoye, O. (2018). The fourth education revolution. Will artificial intelligenceliberate or infantilise humanity. Buckingham: The University of Buckingham Press.
66. Student lifecycle, transition and orientation (2012).
67. Suresh Babu, S., Dhakshina Moorthy, A. (2024). Application of artificial intelligence in adaptation of gamification in education: A literature review. Computer Applications in Engineering Education, vol. 32, no. 1, e22683.
68. Techniques and applications of Machine Learning and Artificial Intelligence in education: a systematic review (2024). Available from: https://www.redalyc.org/journal/3314/ 331475280025/331475280025.pdf.
69. The Role of Artificial Intelligence in the Development of Digital Era Educational Progress (2024). Available from: https://edujavare.com/index.php/jai/article/view/297.
70. The usage of Poka-Yoka in Industry 4.0 conditions (2024). Scientific Papers of Silesian University of Technology Organization and Management Series, no. 191.
71. Vincent-Lancrin, S., González-Sancho, C., Bouckaert, M., Luca, F. de, Fernández-Barrerra, M., Jacotin, G., Urgel, J., Vidal, Q. (2019). Creativity and critical thinking in everyday teaching and learning. OECD. Available from: https://www.oecd-ilibrary.org/education/fostering-students-creativity-and-critical-thinking_10f841e0-en.
72. Vries, A. de, Bliznyuk, N., Pinedo, P. (2023). Invited Review: Examples and opportunities for artificial intelligence (AI) in dairy farms, 2590-2865, vol. 39, no. 1, pp. 14-22. Available from: https://www.sciencedirect.com/science/article/pii/s2590286523000022.
73. Williamson, B., Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, vol. 45, no. 3, pp. 223-235. Available from: https://www.tandfonline.com/doi/full/10.1080/17439884.2020.1798995.
74. Wolniak, R. (2023). Industry 5.0 – characteristic, main principles, advantages and disadvantages. Scientific Papers of Silesian University of Technology. Organization and Management Series, no. 170, pp. 663-678.
75. Wu, J., Wang, X., Dang, Y., Lv, Z. (2022). Digital twins and artificial intelligence in transportation infrastructure: Classification, application, and future research directions. Computers and Electrical Engineering, vol. 101, p. 107983. Available from: https://www.sciencedirect.com/science/article/pii/s0045790622002488?casa_token=ipwfb0u8zzkaaaaa:xfaz99nxcdw2i93linrvdrgniqsnggzs8rgj_jokrswby2zdn3f9rjzd9f08lgpncamqsizd.
76. Yordanova, Z. (2020). Gamification as a Tool for Supporting Artificial Intelligence Development – State of Art. Applied Technologies. First International Conference, ICAT 2019, Quito, Ecuador, December 3-5, 2019, proceedings (pp. 313-324). M. Botto-Tobar (ed.). Cham: Springer. Available from: https://link.springer.com/chapter/10.1007/978-3-030-42517-3_24.
77. Yousuf, M., Wahid, A. (2021). The role of Artificial Intelligence in Education: Current Trends and Future Prospects. 2021 International Conference on Information Science and Communications Technologies (ICISCT), IEEE.
78. Yu, K.-H., Beam, A.L., Kohane, I.S. (2018). Artificial intelligence in healthcare. Nature biomedical engineering, vol. 2, no. 10, pp. 719-731.
79. Zawacki-Richter, O., Marín, V.I., Bond, M., Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, vol. 16, no. 1, pp. 1-27. Available from: https://link.springer.com/article/10.1186/s41239-019-0171-0.
80. Zhai, X., Chu, X., Chai, C.S., Jong, M.S.Y., Istenic, A., Spector, M., Liu, J.-B., Yuan, J., Li, Y. (2021). A Review of Artificial Intelligence (AI) in Education from 2010 to 2020. Complexity, vol. 2021, pp. 1-18. Available from: https://www.hindawi.com/ journals/complexity/2021/8812542/.
81. Zhang, J., Quoquab, F., Mohammad, J. (2024). Plastic and sustainability: a bibliometric analysis using VOSviewer and CiteSpace. Arab Gulf Journal of Scientific Research, vol. 42, no. 1, pp. 44-67. Available from: https://www.emerald.com/insight/content/ doi/10.1108/agjsr-10-2022-0225/full/pdf.

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-60b404c0-03e1-43cb-a14a-535b6138e365