This paper presents a formative assessment toolkit for blended learning (BL) in higher education, developed within the PRIN project named Active Online Assessment in Higher Education and funded by the Italian Ministry of University and Research. Involving research teams from the Universities of Florence and Padua, the project aims to develop and validate an online assessment framework that enhances learning outcomes through advanced technological environments. The toolkit was designed to assist faculty, addressing the need for tailor made support when integrating pedagogical innovations within formative assessment practices. It incorporates machine-led assessment alongside self, teacher, and peer-assessment methods, leveraging generative AI for personalized feedback. Structured around three BL models - transmissive, active, and collaborative assessment - the toolkit is currently being validated in BL courses. Initial results highlight its potential but also underscore the need for additional faculty training and structured guidance for effective implementation.

A toolkit for formative assessment in blended learning settings: integrating AI to support faculty in higher education / C. Baiata, O. Trevisan, E. Gabbi, D. Luzzi, M. De Rossi, M. Ranieri. - ELETTRONICO. - (2025), pp. 6962-6968. ( EDULEARN2025).

A toolkit for formative assessment in blended learning settings: integrating AI to support faculty in higher education

C. Baiata;E. Gabbi;D. Luzzi;M. Ranieri
2025

Abstract

This paper presents a formative assessment toolkit for blended learning (BL) in higher education, developed within the PRIN project named Active Online Assessment in Higher Education and funded by the Italian Ministry of University and Research. Involving research teams from the Universities of Florence and Padua, the project aims to develop and validate an online assessment framework that enhances learning outcomes through advanced technological environments. The toolkit was designed to assist faculty, addressing the need for tailor made support when integrating pedagogical innovations within formative assessment practices. It incorporates machine-led assessment alongside self, teacher, and peer-assessment methods, leveraging generative AI for personalized feedback. Structured around three BL models - transmissive, active, and collaborative assessment - the toolkit is currently being validated in BL courses. Initial results highlight its potential but also underscore the need for additional faculty training and structured guidance for effective implementation.
2025
Proceedings of EDULEARN25 Conference
EDULEARN2025
C. Baiata, O. Trevisan, E. Gabbi, D. Luzzi, M. De Rossi, M. Ranieri
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1430415
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