AI and Feedback with Socrative: Evidence from a Middle School

Abstract

The adoption of artificial intelligence (AI)–based platforms is reshaping approaches to personalization, formative assessment, and inclusion in Italian schools. This quasi-experimental study, conducted over 12 weeks in a middle school, compared two Grade 7 classes (seconda media; N = 46). The experimental group integrated Socrative into all Italian language lessons, while the control group followed traditional methods. Quantitative data (Student Engagement Scale; reading comprehension test) and qualitative data (interviews, focus groups, in-class observations) were collected. A 2 × 2 repeated-measures ANOVA showed a significant increase in overall engagement in the experimental group, accompanied by gains in text comprehension. Thematic analysis revealed three emergent domains: student agency, playful (game-based) motivation, and perceived inclusion. The findings reinforce literature on immediate feedback, learning analytics, and Universal Design for Learning (UDL), suggesting that AI can serve as a lever for equity and self-regulation when supported by robust pedagogical design.