Neural networks at the service of education: challenges of the new era of educational transformation
Keywords:
neural networks, chatbots, artificial intelligence, education personalization of learning, ways of developing neural networks
Abstract
The article is devoted to the current topic of using neural networks and chatbots in education. It analyzes various functions of neural networks, such as personalization of learning, automation of task checking, creation of adaptive educational materials, as well as the capabilities of chatbots to support and motivate students.
The paper highlights the importance of using artificial intelligence (AI) in education, noting its potential to improve learning quality, accessibility and efficiency. The authors cite the pros and cons of introducing chatbots and neural networks into the educational process, citing the results of a survey and interviews with participants in the educational process (students and teachers).
Methodology included theoretical analysis of the state of development of the problem, such scientometric databases and repositories of scientific texts as: Researchgate, GoogleScholar and Scopus databases were used. Teachers (School of Psychology and School of Foreign Languages) and students (School of Psychology and School of Foreign Languages) of V. N. Karazin Kharkiv National University participated in the empirical part of the study. Data were collected using a Google form and interviews with participants in the educational process. The practical aspect of the study involved the use of two questionnaires created with Google Forms. One of them was designed for students, while the other one was tailored for teachers from V. N. Karazin Kharkiv National University and other higher education institutions. Both questionnaires comprised 12 and 11 open- and close-ended questions respectively. Also, the teacher respondents were asked 7 open questions, two of which were of a general organizational nature.
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References
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2. AlAfnan, M. A., Dishari, S., Jovic, M., & Lomidze, K. (2023). Chatgpt as an educational tool: Opportunities, challenges, and recommendations for communication, business writing, and composition courses. Journal of Artificial Intelligence and Technology, 3(2), 60-68.
3. Borenstein, J., & Howard, A. (2021). Emerging challenges in AI and the need for AI ethics education. AI and Ethics, 1, 61-65.
4. Chan, C. K. Y., & Tsi, L. H. (2023). The AI Revolution in Education: Will AI Replace or Assist Teachers in Higher Education? arXiv preprint arXiv:2305.01185.
5. Cotton, D. R., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 1-12.
6. Dai, W., Lin, J., Jin, H., Li, T., Tsai, Y. S., Gašević, D., & Chen, G. (2023, July). Can large language models provide feedback to students? A case study on ChatGPT. In 2023 IEEE International Conference on Advanced Learning Technologies (ICALT) (pp. 323-325). IEEE.
7. Divekar, R. R., Drozdal, J., Zhou, Y., Song, Z., Allen, D., Rouhani, R., ... & Su, H. (2018, June). Interaction challenges in AI equipped environments built to teach foreign languages through dialogue and task-completion. In Proceedings of the 2018 Designing Interactive Systems Conference (pp. 597-609).
8. Google Trends. Google Trends. Available online: https://www.google.com/trends (accessed on 08 March 2024).
9. Griol, D., Molina, J. M., & Callejas, Z. (2017). Incorporating android conversational agents in m‐learning apps. Expert systems, 34(4), e12156.
10. Hwang, G. J., & Chang, C. Y. (2023). A review of opportunities and challenges of chatbots in education. Interactive Learning Environments, 31(7), 4099-4112.
11. Junining, E., Alif, S., & Setiarini, N. (2020). Automatic speech recognition in computer-assisted language learning for individual learning in speaking. JEES (Journal of English Educators Society), 5(2), 219-223.
12. Kaklauskas, A. (2015). Student progress assessment with the help of an intelligent pupil analysis system. Biometric and Intelligent Decision Making Support, 81, 175-193.
13. Kamalov, F., Santandreu Calonge, D., & Gurrib, I. (2023). New era of artificial intelligence in education: Towards a sustainable multifaceted revolution. Sustainability, 15(16), 12451.
14. Khanh, Q. V., Chehri, A., Quy, N. M., Han, N. D., & Ban, N. T. (2023). Innovative Trends in the 6G Era: A Comprehensive Survey of Architecture, Applications, Technologies, and Challenges. IEEE Access.
15. Kreydun, N., Nalyvaiko, O., Ivanenko, L., Zotova, L., Nevoienna, O., Iavorovska, L., Kharchenko, A., & Sevostianov, P. (2022). The Quality of Education in the Conditions of Forced Distance Learning Caused by COVID-19. Revista Romaneasca Pentru Educatie Multidimensionala, 14(4), 423-448. https://doi.org/10.18662/rrem/14.4/649
16. Lodge, J. M., Thompson, K., & Corrin, L. (2023). Mapping out a research agenda for generative artificial intelligence in tertiary education. Australasian Journal of Educational Technology, 39(1), 1-8.
17. Lv, D. (2023, November). Research on International Chinese Education Informatization based on artificial intelligence Technology. In 2023 8th International Conference on Modern Management and Education Technology (MMET 2023) (pp. 367-373). Atlantis Press.
18. Malmström, H., Stöhr, C., & Ou, A. W. (2023). Chatbots and other AI for learning: A survey of use and views among university students in Sweden. Chalmers Studies in Communication and Learning in Higher Education, 1(10.17196).
19. Nalyvaiko, O. & Maliutina, A. (2021). Use of chat bots in the educational process of a higher education institution. Scientific Notes of the Pedagogical Department, (48), 117-122. https://doi.org/10.26565/2074-8167-2021-48-14
20. Nalyvaiko, O. O. (2023). Prospects of using neural networks in higher education of Ukraine. Information Technologies and Learning Tools, 97(5), 1-17. https://doi.org/10.33407/itlt.v97i5.5322
21. Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B. P. T. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies, 28(4), 4221-4241.
22. Nicolescu, L., & Tudorache, M. T. (2022). Human-computer interaction in customer service: the experience with AI chatbots—a systematic literature review. Electronics, 11(10), 1579.
23. Nwana, H. S. (1990). Intelligent tutoring systems: an overview. Artificial Intelligence Review, 4(4), 251-277.
24. Okonkwo, C. W., & Ade-Ibijola, A. (2021). Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2, 100033.
25. Pérez, J., Cerezo, E., Serón, F. J., & Rodríguez, L. F. (2016). A cognitive-affective architecture for ECAs. Biologically Inspired Cognitive Architectures, 18, 33-40.
26. Schiff, D. (2022). Education for AI, not AI for education: The role of education and ethics in national AI policy strategies. International Journal of Artificial Intelligence in Education, 32(3), 527-563.
27. Stokel-Walker, C. (2022). AI bot ChatGPT writes smart essays-should academics worry?. Nature.
28. Terzopoulos, G., & Satratzemi, M. (2019, September). Voice assistants and artificial intelligence in education. In Proceedings of the 9th Balkan Conference on Informatics (pp. 1-6).
29. United Nations Educational, Scientific and Cultural Organization. (2021). Recommendations on the Ethics of Artificial Intelligence. Available online: https://unesdoc.unesco.org/ark:/48223/pf0000380455 (accessed on 10 March 2024).
30. Villegas-Ch, W., Arias-Navarrete, A., & Palacios-Pacheco, X. (2020). Proposal of an Architecture for the Integration of a Chatbot with Artificial Intelligence in a Smart Campus for the Improvement of Learning. Sustainability, 12(4), 1500.
31. Wahle, J. P., Ruas, T., Foltýnek, T., Meuschke, N., & Gipp, B. (2022, February). Identifying machine-paraphrased plagiarism. In International Conference on Information (pp. 393-413). Cham: Springer International Publishing.
32. Winkler, R. & Söllner, M. (2018). Unleashing the Potential of Chatbots in Education: A State-Of-The-Art Analysis. In: Academy of Management Annual Meeting (AOM). Chicago, USA.
33. Zhang S. (2022). The Cognitive Transformation of Japanese Language Education by Artificial Intelligence Technology in the Wireless Network Environment. Computational intelligence and neuroscience, 2022, 7886369. https://doi.org/10.1155/2022/7886369
Published
2024-08-26
Cited
How to Cite
Oleksii Nalyvaiko, Kateryna Malysh, Yana Prykhodko, & Sofiia Chaban. (2024). Neural networks at the service of education: challenges of the new era of educational transformation. Scientific Notes of the Pedagogical Department, (54). Retrieved from https://periodicals.karazin.ua/pedagogy/article/view/24253
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