The project aimed to strengthen the capacity of participating schools to adopt data-informed and personalised approaches to teaching and learning. More specifically, it sought to digitalise and administer a validated questionnaire on learning strategies in order to obtain a structured and comparable dataset across Italian and Hungarian schools. The project also aimed to develop an initial AI-assisted system capable of analysing students’ responses and generating individualised reports for each learner, offering teachers evidence-based insights into study habits, cognitive preferences and areas requiring support. A further objective was to enhance teachers’ digital and analytical competences, enabling them to interpret the reports and reflect on how learning variability affects classroom dynamics. The project also intended to reinforce cross-country collaboration on innovative educational practices and to provide schools with a model for integrating research-based tools into their internal quality processes. Overall, the project aimed to lay the groundwork for more personalised, inclusive and effective learning environments supported by digital and AI-driven methodologies.
We applied for this project because the participating schools and organisations had identified a clear need to modernise their educational practices and strengthen their capacity to address increasingly diverse learning profiles. Before the project, teachers lacked structured tools to analyse students’ study habits and learning styles, and schools had limited digital systems to support data-informed teaching. Moreover, both Italian and Hungarian partners expressed the need to enhance digital readiness and adopt evidence-based methods for personalising instruction, in line with Erasmus+ priorities on innovation and digital transformation in school education. The project addressed these needs by introducing a structured, research-based questionnaire, by supporting teachers in understanding learning variability, and by implementing digital and AI-assisted tools to interpret educational data. Partners also sought to reinforce their capacity to integrate adaptive methods into classroom practice, improve students’ engagement, and promote more inclusive and tailored pedagogical approaches.