From emotion regulation to academic success: A self‐determination theory‐based emotional agent‐mediated approach

Abstract Emotion regulation has been recognized as a key factor affecting students' academic success. However, in conventional school settings, it is challenging to foster students' emotion regulation owing to the involvement of complex factors that might influence students' conscious and unconscious behaviours. To address this issue, a self‐determination theory (SDT)‐based emotional agent framework was proposed, and an emotional agent (EmoAgent), capable of proactively detecting students' emotional states and providing emotional regulation strategies to individual students in addition to the provision of conventional learning supports, was implemented. To assess the effectiveness of the proposed approach, an 8‐week quasi‐experiment was designed with 173 sixth graders from four classes taking the Information Technology course in a primary school. Two classes (87 students) comprised the experimental group (EG) which used the SDT‐based emotional agent‐mediated (SDT‐EA) approach, while the other two classes (86 students) comprised the control group (CG) which learned with the SDT‐based conventional agent (STD‐CA), which is capable of providing learning supports but without considering emotional factors. The experimental results showed that (1) the SDT‐EA approach significantly outperformed the SDT‐CA approach in academic achievement; (2) the SDT‐EA approach engaged students in positive emotional experiences, whereas the SDT‐CA approach exposed students to more negative emotional experiences; (3) negative emotion was significantly negatively associated with academic achievement, moderated by the SDT‐EA approach. Practitioner notes What is already known about this topic? Within self‐determination theory, if the three psychological needs of autonomy, competence and relatedness are met, students’ intrinsic motivation is activated and in turn their academic emotion is regulated, which shapes their well‐being, engagement and academic success. GenAI–human collaboration can facilitate students’ self‐determined and personalized learning. Most pedagogical agents tend to assist with personalized cognitive support rather than with emotion regulation or emotional support. What does this paper add? Merging affective computing technology with GenAI, this study constructed an emotional agent with emotion sensing, recognition, feedback and regulation, providing emotional and cognitive supports. Using process mining techniques, this study found that the emotional agent facilitated students’ emotion regulation from negative to positive. The emotional agent moderated the effect of negative emotions on academic success. The emotional agent can significantly promote academic achievement. Implications for practice and/or policy The study findings imply that the SDT‐based emotional agent‐mediated approach shows promise for strengthening students’ self‐regulated learning. The study offers a viable model for integrating socio‐emotional learning with subject‐matter instruction. The SDT‐based emotional agent can be embedded in regular instruction to instantiate a self‐determined learning paradigm.