Skip to main navigation menu Skip to main content Skip to site footer
FrancoAngeli Journals

Articles/Articoli

Vol. 15 No. 2 (2024): Artificial Intelligence in Schools and University Education: Risks and Opportunities

Artificial Intelligence in Higher Education: A Research Pathway with ChatGPT for Learning Design, Feedback, and Professional Development

DOI
https://doi.org/10.3280/ess2-2024oa18772
Submitted
novembre 1, 2024
Published
2025-01-31

Abstract

This paper explores a research pathway that leverages an AI-based conversational tool, ChatGPT - OpenAI, to enhance essential competencies in future teachers and educators, with a focus on self-reflection and feedback literacy. Conducted within two pedagogical courses, the activity involved peer feedback on didactic design tasks, fostering students’ agency and metacognitive reflection. By using ChatGPT as both a design and feedback agent, students evaluated its effectiveness, strengths, and limitations. Reflective questionnaires allowed them to assess the tool’s potential integration into their future professional practices, addressing the broader applicability of AI in educational contexts.

References

  1. 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.
  2. Bolter J.D. (2019). The Digital Plenitude. The Decline of the Elite Culture and the Rise of New Media. Cambridge, MA: TheMIT Press.
  3. Bonaiuti G., Calvani A., Menichetti L., and Vivanet G. (2017). Le tecnologie educative. Criteri per una scelta basata su evidenze. Roma: Carocci.
  4. Braun V., Clarke V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2): 77-101. DOI: 10.1191/1478088706qp063oa.
  5. Braun V., Clarke V. (2012). Thematic analysis. In H. Cooper P. M. Camic D. L. Long A. T. Panter D. Rindskopf and K. J. Sher (Eds.). APA Handbook of Research Methods in Psychology: Vol. 2. Research Designs (pp. 57-71). Washington, DC: American Psychological Association.
  6. Braun V., Clarke V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4): 589-597. DOI: 10.1080/2159676X.2019.1628806.
  7. Capolla L.M., Giannandrea L., Gratani F., Pentucci M. and Rossi P.G. (2024). Rethinking and formalizing initial teacher training on learning design for and in uncertainty. Frontiers in Education, 9, 1268936. DOI: 10.3389/feduc.2024.1268936.
  8. Carless D., Boud D. (2018). The development of student feedback literacy enabling uptake of feedback. Assessment and Evaluation in Higher Education, 43(8): 1315-1325.
  9. Coeckelbergh M. (2020). AI Ethics. Cambridge MA: The MIT Press.
  10. Deng Y., Liao L., Zheng Z., Yang G.H., Chua T. (2024). Towards human-centered proactive conversational agents. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022 (pp. 807-818). DOI: 10.1145/3626772.3657843.
  11. Elliott A. (2021). La cultura dell’intelligenza artificiale. Torino: Codice Edizioni.
  12. Følstad A., Araujo T., Law E.L.C., Brandtzaeg P.B., Papadopoulos S., Reis L., Baez M., Laban G., McAllister P., Ischen C., Wald R., Catania F., Meyer Von Wolff R., Hobert S. and Luger E. (2021). Future directions for chatbot research: An interdisciplinary research agenda. Computing, 103(12): 2915-2942. DOI: 10.1007/s00607-021-01016-7.
  13. Gratani F., Capolla L.M., Giannandrea L., Screpanti L. and Scaradozzi D. (2023). Facilitating feedback at university using AI-based techniques. In HELMeTO 2023-Book of Abstracts (pp. 157-159). Roma: STUDIUM.
  14. Gupta P., Ding B., Guan C. and Ding D. (2024). Generative AI: a systematic review using topic modelling techniques. Data and Information Management, 8(2), 100066. DOI: 10.1016/j.dim.2024.100066.
  15. Hwang G.J., Chang C.Y. (2021). A review of opportunities and challenges of chatbots in education. Interactive Learning Environments, 1-14. DOI: 10.1080/10494820.2021.1952615.
  16. Krippendorff K. (2018). Content analysis: An introduction to its methodology. London: Sage.
  17. Laici C. (2021). Il feedback come pratica trasformativa nella didattica universitaria. Milano: FrancoAngeli.
  18. Lee H., Phatale S., Mansoor H., Lu K.R., Mesnard T., Ferret J., Bishop C., Hall E., Carbune V. and Rastogi A. (2023). RLAIF: Scaling reinforcement learning from human feedback with AI feedback. In Proceedings of the 41st International Conference on Machine Learning (PMLR 235). Vienna: PMLR.
  19. Liao L, Yang G., Shah C. (2023). Proactive conversational agents in the post-ChatGPT world. SIGIR, 23: 23-27.
  20. McNamara D.S., Arner T., Butterfuss R., Fang Y., Watanabe M., Newton N., McCarthy K.S., Allen L.K. and Roscoe R.D. (2023). iSTART: Adaptive comprehension strategy training and stealth literacy assessment. International Journal of Human-Computer Interaction, 39(11): 2239-2252.
  21. Nicol D. (2020). The power of internal feedback: exploiting natural comparison processes. Assessment & Evaluation in Higher Education, 46(5): 756-778. DOI: 10.1080/02602938.2020.1823314.
  22. Nicol D., S. McCallum (2022). Making Internal Feedback Explicit: Exploiting the Multiple Comparisons That Occur during Peer Review. Assessment & Evaluation in Higher Education 47(3): 424-443. DOI: 10.1080/02602938.2 021.1924620.
  23. Nieminen J.H., Carless D. (2023). Feedback literacy: A critical review of an emerging concept. Higher Education, 85(6): 1381-1400. DOI: 10.1007/s10734-022-00895-9.
  24. Packin N. G., Lev-Aretz Y. (2018). Learning algorithms and discrimination. In W. Barfield, U. Pagallo (eds.). Handbook on the law of artificial intelligence (pp. 88-113). Cheltenham MA: Edward Elgar Publishing.
  25. Panciroli C., Rivoltella P.C. (2023). Pedagogia algoritimica. Per una riflessione educativa sull’Intelligenza Artificiale. Brescia: Scholè.
  26. Pang T.Y., Kootsookos A., Cheng C. (2024). Artificial intelligence use in feedback: a qualitative analysis. Journal of University Teaching and Learning Practice, 21(6): 1-18. DOI: 10.53761/40wmcj98.
  27. Pentucci M., Laici C. (2023). Peer feedback and peer review in higher education: mirroring and transformative practices in active learning processes. In EDULEARN23 Proceedings (pp. 790-799). Siviglia (ES): IATED.
  28. Pentucci M., Rossi P.G., Capolla L. (2023). Designing regulation in action to manage the unforeseen in teaching-learning contexts. In EDULEARN23 Proceedings (pp. 1151-1158). IATED.
  29. Pentucci M., Sarra A., Laici C. (2023). Feedback to align teacher and student in a digital learning ecosystem. Education Sciences & Society, 14(1): 242-260. Milano: FrancoAngeli.
  30. Pentucci M. (2018). I formati pedagogici nelle pratiche degli insegnanti. Milano: FrancoAngeli.
  31. Perera P., Lankathilaka M. (2023). AI in higher education: A literature review of chatgpt and guidelines for responsible implementation. International Journal of Research and Innovation in Social Science, 7(6); 306-314. DOI: 10.1080/10494820.2021.1952615.
  32. Prananta A.W., Megahati S., Susanto N. and Raule J.H. (2023). Transforming education and learning through ChatGPT: A systematic literature review. Jurnal Penelitian Pendidikan IPA, 9(11): 1031-1037. DOI: 10.29303/jppipa.v9i11.5468.
  33. Reiss M.J. (2021). The Use of Al in Education: Practicalities and Ethical Considerations. London Review of Education, 19(1), 1.
  34. Rivoltella P.C., Rossi P.G. (2019). Il corpo e la macchina. Tecnologia, cultura, educazione. Brescia: Scholé.
  35. Rossi P.G., Pentucci M. (2021). Progettazione come azione simulata. Didattica dei processi e degli eco-sistemi. Milano: FrancoAngeli.
  36. Rossi P.G., Pentucci M., Fedeli L., Giannandrea L. and Pennazio V. (2018). Dal feedback informativo al feedback generativo. Education Sciences and Society, 9(2): 83-107.
  37. Tam A.C.F. (2024). Interacting with ChatGPT for internal feedback and factors affecting feedback quality. Assessment & Evaluation in Higher Education, 1-17. DOI: 10.1080/02602938.2024.2374485.
  38. Sansone N., Bortolotti I., Fabbri M. (2021). Il peer-assessment nella formazione insegnanti: accorgimenti e ricadute. Education Sciences & Society, 2: 444-460.
  39. Sansone N., Fabbri M., Bortolotti I. (2023). Reflective practices in teacher education for and through technologies. Formazione & insegnamento, 21(1): 239-246. DOI: 10.7346/-fei-XXI-01-23_29.
  40. van Velzen J.H. (2015). Are students intentionally using self-reflection to improve how they learn? Conceptualising self-induced self-reflective thinking. Reflective Practice, 16(4): 522-533. DOI: 10.1080/14623943.2015.1064378.
  41. Walter Y. (2024). Embracing the future of artificial intelligence in the classroom: The relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education, 21(1), 15. DOI: 10.1186/s41239-024-00448-3.
  42. Wan T., Chen Z. (2024). Exploring generative AI assisted feedback writing for students’ written responses to a physics conceptual question with prompt engineering and few-shot learning. Physical Review Physics Education Research, 20(1), 010152.
  43. Williamson B., Macgilchrist F., Potter J. (2023). Re-examining AI, automation and datafication in education. Learning, Media and Technology, 48(1): 1-5.
  44. Winstone N., Carless D. (2019). Designing Effective Feedback Processes in Higher Education: A Learning-Focused Approach (1st ed.). London: Routledge. DOI: 10.4324/9781351115940.

Metrics

Metrics Loading ...

Most read articles by the same author(s)