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

AI and Feedback. Assessing written tasks in Higher Education through human and artificial agent interaction

DOI
https://doi.org/10.3280/ess2-2024oa18951
Submitted
dicembre 4, 2024
Published
2025-01-31

Abstract

Automated feedback, made possible by advanced technological tools such as artificial intelligence, represents an emerging frontier to overcome some of the traditional challenges related to the customisation and scalability of the assessment process, especially in large classes. In Italy, despite growing interest at European level, the adoption of digitally supported assessment remains limited and presents numerous challenges. These critical issues underline the urgency of promoting the professional development of teachers through training courses aimed at integrating automated feedback into teaching practice, in order to enhance the transformative potential of these tools. It is in this context that PRIN “AI&F” has emerged, which aims to define a methodology for using an open-source machine learning framework to support teachers in providing high quality feedback to large groups of students, generating interactive and transformative pathways in an ecosystem logic. The paper presents current research progress and outlines future development perspectives.

References

  1. Bearman M., Tai J., Dawson P., Boud D., and Ajjawi R. (2024). Sviluppo del giudizio valutativo per un'epoca di intelligenza artificiale generativa. Assessment & Evaluation in Higher Education, 49(6): 893-905. DOI: 10.1080/02602938.2024.2335321.
  2. Boud D., Ajjawi R., Dawson P., and Tai J. (2018). Developing evaluative judgement in higher education. London: Routledge.
  3. Braun V. e Clarke V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2): 77-101.
  4. Devlin J., Chang M.-W., Lee K., and Toutanova K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv, 1810.04805. DOI: 10.48550/arXiv.1810.04805.
  5. Doria B., Foschi L.C., Slaviero G., Zaggia C., and Grion V. (in press). Feedback e feedback automatizzato: Pratiche e percezioni dei docenti universitari. Research Trends in Humanities: Education & Philosophy.
  6. Doria B., Picasso F. (2024). Alternative Assessment and Technology Enhanced Assessment practices: Research to inform Faculty Development processes. QWERTY-Interdisciplinary Journal of Technology, Culture and Education, 19(1): 52-71.
  7. Doria B., Grion V., and Paccagnella O. (2023). Pratiche valutative nelle università italiane: Una ricerca esplorativa a livello nazionale. Italian Journal of Educational Research, 30: 129-143.
  8. Doria B., Grion V., and Zaggia C. (2024). How to train university professors in assessment? A systematic literature review. Form@re - Open Journal per la forma-zione in rete, 24(2): 14-30.
  9. Facer K., Selwyn N. (2021). Digital technology and the futures of education – To-wards ‘non-stupid’ optimism. Educational Philosophy and Theory, 53(3): 233-244.
  10. Fiorentino M.G., Montone A., and Ricciardiello G. (2024). The Feedback in a Formative Assessment Path: Development of Communicative Skills in a Workshop Online. In: International Conference on Higher Education Learning Methodologies and Technologies Online (pp. 250-261). Cham: Springer Nature Switzerland. DOI: 10.1007/978-3-031-67351-1.
  11. Giannandrea L. (2019). Valutazione, feedback, tecnologie. In: Rivoltella P.C. and Rossi P.G., a cura di, Tecnologie per l’educazione (pp. 69-81). Milano: Pearson.
  12. Giannandrea L., Ferrari S., and Laici C. (2024). Tecnologie per la riflessione e l’autovalutazione. E-portfolio, feedback, open badge. In: Rivoltella P.C. and Rossi P.G., a cura di, (nuova edizione), Tecnologie per l’educazione (pp. 189-199). Milano: Pearson.
  13. Grion V., Cesareni D. (2016). Multiplicity, fluidity, dialogue and sharing: Keywords to understand the complex dynamics between human learning and technology. QWERTY-Interdisciplinary Journal of Technology, Culture and Education, 11(1): 5-10.
  14. Grion V., Serbati A. (2019). Valutazione sostenibile e feedback nei contesti universitari. Prospettive emergenti, ricerche e pratiche. Lecce: PensaMultimedia.
  15. Grion V., Serbati A., Doria V., and Nicol D. (2021). Rethinking assessment and feed-back practices in higher education: A review of recent literature. Innovations in Education and Teaching International, 58(4): 405-416.
  16. 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.
  17. Laici C. (2021). Il feedback come pratica trasformativa nella didattica universitaria. Milano: FrancoAngeli.
  18. Laici C., Pentucci M. (2023). Developing university students’ feedback literacy through peer feedback activities. Education Sciences & Society - Open Access, 14(1). DOI: 10.3280/ess1-2023oa15925.
  19. Lipnevich A.A., Panadero E. (2021). A Review of Feedback Models and Theories: Descriptions, Definitions, and Conclusions. Frontiers in Education, 6, 720195. DOI: 10.3389/feduc.2021.720195.
  20. Nicol D. (2010). From monologue to dialogue: Improving written feedback processes in mass higher education. Assessment & Evaluation in Higher Education, 35(5): 501-517.
  21. Nicol D. (2018). Unlocking generative feedback via peer reviewing. In: Grion V. and Serbati A., a cura di, Assessment of learning or assessment for learning? Towards a culture of sustainable assessment in HE (pp. 73-85). Lecce: Pensa MultiMedia.
  22. Nicol D. (2021). Guiding learning by activating students’ inner feedback. Times Higher Education. https://www.timeshighereducation.com/campus/guide-learning-activating-students-inner-feedback.
  23. Nicol D.J., Macfarlane-Dick D. (2006). Formative assessment and self-regulated learning: A model and seven principles of good feedback practice. Studies in Higher Education, 31(2): 199-218.
  24. Nieminen J.H., Carless D. (2023). Feedback literacy: una revisione critica di un concetto emergente. High Education, 85: 1381-1400. DOI: 10.1007/s10734-022-00895-9.
  25. Panadero E., Lipnevich A.A. (2022). A review of feedback models and typologies: Towards an integrative model of feedback elements. Educational Research Review, 35, 100416.
  26. Panadero E., Fraile J., Fernández Ruiz J., Castilla-Estévez D., and Ruiz M.A. (2019). Spanish university assessment practices: Examination tradition with diversity by faculty. Assessment & Evaluation in Higher Education, 44(3): 379-397.
  27. Panciroli C., Rivoltella P.C. (2023). Pedagogia algoritimica. Per una riflessione educativa sull’Intelligenza Artificiale. Brescia: Scholè.
  28. Picasso F., Doria B., Grion V., Venuti P., and Serbati A. (2023). What technology-enhanced assessment and feedback practices do Italian academics declare in their syllabi? Analysis and reflections to support academic development. In: Fulantelli G., Burgos D., Casalino G., Cimitile M., Lo Bosco G., and Taibi D., a cura di, Higher education learning methodologies and technologies online (pp. 267-279). Cham: Springer.
  29. Price M., Handley K., Millar J., and O’Donovan B. (2010). Feedback: All that effort, but what is the effect? Assessment & Evaluation in Higher Education, 35(3): 277-289.
  30. Raffaghelli J.E., Ghislandi P., Sancassani S., Canal L., Micciolo R., Balossi B., and Zani M. (2018). Integrating MOOCs in physics preliminary undergraduate education: beyond large size lectures. Educational Media International, 1-16. DOI: 10.1080/09523987.2018.1547544.
  31. Raffaghelli J.E. (2024). Post Digital Scholarship. Professionalità accademica e trasformazione digitale in università. Didattiche, Tecnologie e Media Education. Frontiere per la Sostenibilità, 1: 1-460.
  32. Ranieri M., Raffaghelli J.E., and Bruni I. (2021). Game-based student response system: Revisiting its potentials and criticalities in large-size classes. Active Learning in Higher Education, 22(2): 129-142. DOI: 10.1177/1469787418812667.
  33. Redecker C., Punie Y. (2017). European framework for the digital competence of educators: DigCompEdu. Lussemburgo: Publications Office of the European Union.
  34. 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.
  35. Sadler R. (2010). Beyond feedback: developing student capability in complex appraisal. Assessment & Evaluation in Higher Education, 35(5): 535-550.
  36. Steiss J., Tate T., Graham S., Cruz J., Hebert M., Wang J., Moon Y., Tseng W., Warschauer M., and Olson C.B. (2024). Comparing the quality of human and ChatGPT feedback of students’ writing. Learning and Instruction, 91, 101894.
  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. Tonelli D., Grion V., and Serbati A. (2018). L’efficace interazione fra valutazione e tecnologie: Evidenze da una rassegna sistematica della letteratura. Italian Journal of Educational Technology, 26(3): 6-23.
  39. Winstone N., Carless D. (2019). Designing Effective Feedback Processes in Higher Education: A Learning-Focused Approach (1st ed.). Routledge. DOI: 10.4324/9781351115940.

Metrics

Metrics Loading ...