The COVID-19 pandemic has evidenced a need for tools and methodologies to support students' autonomous learning and the formative assessment practices in distance education contexts, especially for students from challenging backgrounds. This paper proposes a conceptualization of Interactive Feedback (IF) for Mathematics, which is a step-by-step interactive process that guides the learner in the resolution of a task after one or more autonomous tentative. This conceptualization is grounded on theories and models of automatic assessment, formative assessment, and feedback. We discuss the effectiveness of the IF for engaging students from low socio-economic contexts in closing the gap between current and reference performance through a didactic experimentation involving 299 Italian students in grade 8. Using quantitative analyses on data from the automatic assessment, we compared the results of the first and last attempts in activities with and without IF, based on algorithmic parameters so that the task changes at every attempt. We found that IF was more effective than other kinds of activities to engage learners in actions aimed at improving their results, and the effects are stronger in low socio-economic contexts.