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

Journal title EDUCATION SCIENCES AND SOCIETY
Author/s Laura Carlotta Foschi, Beatrice Doria, Chiara Laici, Francesca Gratani, Laura Screpanti, Michele Giuliano Michele Giuliano, Pier Giuseppe Rossi, Lorella Giannandrea, Valentina Grion, Antonella Montone
Publishing Year 2025 Issue 2024/2
Language Italian Pages 15 P. 142-156 File size 0 KB
DOI 10.3280/ess2-2024oa18951
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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.

Keywords: ; feedback; artificial intelligence; higher education; BERT model; LLM

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Laura Carlotta Foschi, Beatrice Doria, Chiara Laici, Francesca Gratani, Laura Screpanti, Michele Giuliano Michele Giuliano, Pier Giuseppe Rossi, Lorella Giannandrea, Valentina Grion, Antonella Montone, AI e Feedback. Interazione tra agenti umani e artificiali per valutare prove scritte in ambito universitario in "EDUCATION SCIENCES AND SOCIETY" 2/2024, pp 142-156, DOI: 10.3280/ess2-2024oa18951