Students’ feedback process using automated post-submission reports in their modeling process

Abstract This study explores how students use automated elaborated feedback, specifically post-submission reports generated by a digital Formative Assessment (FA) platform, as a means to foster students’ engagement and enhance Mathematical Modeling Competencies (MMC). While the potential of technology to provide automated assessment is well established, this qualitative study provides empirical insight into the dynamic relationship between technology, metacognition, and the core processes of mathematical modeling. Our main finding is that the automated report enriches the structure and flow of the modeling cycle, transforming it from a linear sequence into a flexible, iterative process driven by student reflection. We found that the report functions as a catalyst for continuous reflection, prompting students to iteratively re-enter previous modeling phases, in ways that reflect specific MMC, and highlighting the potential role of automated feedback in supporting self-regulated learning in digital environments.