Artificial intelligence mediated socioemotional support emotional co-regulation and self-regulated learning in higher education

Abstract

Abstract Artificial intelligence (AI)–based conversational systems are increasingly incorporated into student support strategies in higher education, particularly in response to rising levels of psychological distress and limited counseling resources. These systems are often used to provide immediate guidance and emotional support in situations of academic stress and anxiety. This perspective examines how AI-mediated socioemotional support shapes emotional regulation processes and its implications for self-regulated learning. Drawing on major models of self-regulated learning, including perspectives on emotional regulation and co-regulation, and on current evidence regarding AI-based support in educational contexts, the paper conceptualizes these interactions as forms of emotional co-regulation that assist students in managing distress in the short term. However, their recurrent use may also influence how emotional regulation is carried out in academic life. The paper proposes a conceptual framework showing how AI-mediated socioemotional support may contribute either to the internalization of regulatory strategies or to the delegation of regulatory processes, with implications for emotional autonomy and self-regulated learning. The analysis suggests that, while AI may serve as a complementary resource, its integration should not displace the interpersonal processes through which students develop emotional regulation and engage meaningfully with university life; instead, it requires institutional conditions that ensure responsible and bounded use.