The impact of Generative Artificial Intelligence (GenAI) on education: A review of the potential, the risks and the role of immersive technologies

Journal title EDUCATION SCIENCES AND SOCIETY
Author/s Martina Rossi, Michele Ciletti, Lucia Melchiorre, Giusi Antonia Toto
Publishing Year 2025 Issue 2024/2
Language English Pages 16 P. 400-415 File size 0 KB
DOI 10.3280/ess2-2024oa18464
DOI is like a bar code for intellectual property: to have more infomation click here

View article Download Open Access article

FrancoAngeli is member of Publishers International Linking Association, Inc (PILA), a not-for-profit association which run the CrossRef service enabling links to and from online scholarly content.

Generative Artificial Intelligence (GenAI) is revolutionising teaching practices, offering new opportunities to personalise learning and improve the interaction between students and content. This paper aims to explore the uses of GenAI and immersive technologies in teaching practices, with a specific focus on Italian schools and universities. A review of the literature and state of the art was conducted, through the analysis of existing projects and case studies, in order to investigate how these joint technologies can enhance learning and address complex teaching challenges. Although the projects reviewed show a wide range of innovative applications that exploit GenAI and immersive technologies to enhance learning experiences, develop critical thinking and problem-solving skills, several challenges emerged in terms of accessibility and scalability of the tools.

Keywords: ; Generative Artificial Intelligence; Immersive Technologies; Virtual Reality; Educational Innovation

  1. Accoto C. (2017). Il mondo dato. Cinque brevi lezioni di filosofia digitale. Milano: Egea.
  2. Accoto C. (2019). Il mondo ex machina. Cinque brevi lezioni di filosofia dell’automazione. Milano: Egea.
  3. Bahdanau D. (2014). Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv, 1409.0473.
  4. Bahroun Z., Anane C., Ahmed V., and Zacca A. (2023). Transforming education: A comprehensive review of generative artificial intelligence in educational settings through bibliometric and content analysis. Sustainability, 15(17), 12983.
  5. Baidoo-Anu D., Ansah L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1): 52-62.
  6. Bellman R. E. (1978). An Introduction to Artificial Intelligence: Can Computers Think?. Boyd & Fraser Publishing Company.
  7. Bozkir E., Özdel S., Lau K. H. C., Wang M., Gao H., and Kasneci E. (2024, July). Embedding large language models into extended reality: Opportunities and challenges for inclusion, engagement, and privacy. In Proceedings of the 6th ACM Conference on Conversational User Interfaces (pp. 1-7).
  8. Buccini F. (2024). Come l’intelligenza artificiale sta cambiando l’educazione Uno studio esplorativo. Research Trends In Humanities Education & Philosophy, (11): 75-89.
  9. Elliott D., Soifer E. (2022). AI technologies, privacy, and security. Frontiers in Artificial Intelligence, 5, 826737.
  10. Epley N, Waytz A, and Cacioppo J.T. (2007). On seeing human: a three-factor theory of anthropomorphism. Psychol Rev., Oct, 114(4): 864-86. DOI: 10.1037/0033-295X.114.4.864
  11. Gao Y., Xiong Y., Gao X., Jia K., Pan J., Bi Y., ... and Wang H. (2023). Retrieval-augmented generation for large language models: A survey. arXiv preprint arXiv, 2312.10997.
  12. Geraci R. M. (2011). There and Back Again: Transhumanist Evangelism in Science Fiction and Popular Science. Implicit Religion, 14(2): 141-172. DOI: 10.1558/imre.v14i2.141
  13. Goldstein J. A., Sastry G., Musser M., Di Resta R., Gentzel M., and Sedova K. (2023). Generative language models and automated influence operations: Emerging threats and potential mitigations. arXiv preprint arXiv, 2301.04246.
  14. Grassini S. (2023). Shaping the future of education: exploring the potential and consequences of AI and ChatGPT in educational settings. Education Sciences, 13(7), 692.
  15. Guidotti R., Monreale A., Ruggieri S., Turini F., Giannotti F., and Pedreschi D. (2018). A survey of methods for explaining black box models. ACM computing surveys (CSUR), 51(5): 1-42.
  16. Harry A., Sayudin S. (2023). Role of AI in Education. Interdiciplinary Journal and Hummanity (INJURITY), 2(3): 260-268.
  17. Hassabis D., Kumaran D., Summerfield C., and Botvinick M. (2017). Neuroscience-Inspired Artificial Intelligence. Neuron., Jul 19, 95(2): 245-258. DOI: 10.1016/j.neuron.2017.06.011
  18. Jaouadi A., Maaradji A. (2024). ICT & Generative Artificial Intelligence Powered Hybrid Model for Future Education. Cadmus, 5(3).
  19. Kurzweil R. (1990). The Age of Intelligent Machines. MIT Press.
  20. Mao J., Chen B., and Liu J. C. (2024). Generative artificial intelligence in education and its implications for assessment. TechTrends, 68(1): 58-66.
  21. McDonald N., Johri A., Ali A., and Hingle A. (2024). Generative artificial intelligence in higher education: Evidence from an analysis of institutional policies and guidelines. arXiv preprint arXiv, 2402.01659.
  22. Montenegro-Rueda M., Fernández-Cerero J., Fernández-Batanero J. M., and López-Meneses E. (2023). Impact of the implementation of ChatGPT in education: A systematic review. Computers, 12(8), 153.
  23. Natale S., Ballatore A. (2020). Imagining the thinking machine: Technological myths and the rise of artificial intelligence. Convergence, 26(1): 3-18. DOI: 10.1177/1354856517715164
  24. Maslej N., Fattorini L., Brynjolfsson E., Etchemendy J., Ligett K., Lyons T., Manyika J., Ngo H., Niebles J. C., Parl V., Shoham Y., Wald R., Clark J., and Perrault R., “The AI Index 2023 Annual Report,” AI Index Steering Committee, Institute for Human-Centered AI, Stanford University, Stanford, CA, April 2023.
  25. Noy S., Zhang W. (2023). Experimental evidence on the productivity effects of generative artificial intelligence. Science, 381: 187-192.
  26. Panciroli C., & Macauda A. (2018). Educazione al patrimonio e realtà aumentata: quali prospettive. Giornale italiano della ricerca educativa, 11(20): 47-62.
  27. Peconio G., Ciletti M., Rossi M., and Toto G. A. (2024). Artificial Intelligence And Emotions: An exploratory survey on the perception of AI Technologies between support teachers in training. Italian Journal of Health Education, Sport and Inclusive Didactics, 8(3).
  28. Rivoltella P.C. (2020). Nuovi alfabeti. Educazione e culture nella società post-mediale. Scholé-Morcelliana, 124: 5-220.
  29. Rossi M., Ciletti M., Scarinci A., and Toto G. A. (2023). Apprendere attraverso il metaverso e la realtà immersiva: nuove prospettive inclusive. IUL Research, 4(7): 165-177.
  30. Russell S. J., Norvig P. (2016). Artificial intelligence: a modern approach. Pearson.
  31. Russell S. J., Norvig P. (2003), Artificial Intelligence: A Modern Approach (2nd ed.), Upper Saddle River, New Jersey: Prentice Hall.
  32. Sekeroglu B., Dimililer K., and Tuncal K. (2019). Artificial Intelligence in Education: application in student performance evaluation. Dilemas Contemporáneos: Educación, Política y Valores, 7(1).
  33. Smutny P., Babiuch M., and Foltynek P. (2019, May). A review of the virtual reality applications in education and training. In 2019 20th International Carpathian Control Conference (ICCC) (pp. 1-4). IEEE.
  34. Stampfl R., Geyer B., Deissl-O’Meara M., and Ivkić I. (2024). Revolutionising Role-Playing Games with ChatGPT. arXiv preprint arXiv, 2407.02048.
  35. Sze V., Chen Y.-H., Yang T.-J., and Emer J. (2017). Efficient Processing of Deep Neural Networks: A Tutorial and Survey. arXiv, 1703.09039.
  36. Touvron H., Lavril T., Izacard G., Martinet X., Lachaux M., Lacroix T., Rozière B., Goyal N., Hambro E., Azhar F., Rodriguez A., Joulin A., Grave E., and Lample G. (2023). LLaMA: Open and Efficient Foundation Language Models. ArXiv, abs/2302.13971.
  37. Turing A. (1950). Computing Machinery and Intelligence. Mind, LIX (236): 433-460, DOI: 10.1093/mind/LIX.236.433, ISSN 0026-4423
  38. Vaswani A. (2017). Attention is all you need. Advances in Neural Information Processing Systems.
  39. Weizenbaum J. (1976). Computer Power and Human Reason: From Judgment to Calculation. New York: W. H. Freeman and Company.
  40. Wolf M. J., Miller K., and Grodzinsky F. S. (2017). Why we should have seen that coming: comments on Microsoft’s tay “experiment,” and wider implications. Acm Sigcas Computers and Society, 47(3): 54-64.
  41. Wu C. J., Raghavendra R., Gupta U., Acun B., Ardalani N., Maeng K., ... and Hazelwood K. (2022). Sustainable ai: Environmental implications, challenges and opportunities. Proceedings of Machine Learning and Systems, 4: 795-813.
  42. Yin K., Neubig G. (2022). Interpreting language models with contrastive explanations. arXiv preprint arXiv, 2202.10419.
  43. Yu H., Guo Y. (2023). Generative artificial intelligence empowers educational reform: current status, issues, and prospects. Frontiers in Education, 8, 1183162.

Martina Rossi, Michele Ciletti, Lucia Melchiorre, Giusi Antonia Toto, The impact of Generative Artificial Intelligence (GenAI) on education: A review of the potential, the risks and the role of immersive technologies in "EDUCATION SCIENCES AND SOCIETY" 2/2024, pp 400-415, DOI: 10.3280/ess2-2024oa18464