Emotional Responses to AI Tutors in Young Learners: A Sociocultural Perspective on Trust, Motivation, and Frustration

This study explores EFL young learners’ emotional responses to AI tutors through the lens of Vygotsky’s Sociocultural Theory, focusing on how trust, motivation, and frustration emerge in mediated learning environments. Framing AI-tutors, as quasi-social agents, the research examines how they mediate between students and learning context, particularly in relation to the Zone of Proximal Development (ZPD). The study involves Grade 5 and Grade 6 pupils in a bilingual Italian school in Rome. Using questionnaires and qualitative analysis of student interactions with AI-powered tutors on the SchoolAI platform, the study investigates how learners perceive AI support, and whether these perceptions reflect effective scaffolding within their ZPD. Emotional responses are interpreted as signals of alignment between AI support and learners’ developmental readiness: motivation and trust suggest effective scaffolding, while frustration may point to mismatched support. The findings contribute to our understanding of how AI can serve as a culturally shaped, emotionally responsive tool in education, mimicking aspects of human scaffolding. The study emphasizes that emotions are not peripheral to learning, but central to cognitive development, especially when mediated by AI in socially and developmentally meaningful ways.