ARTIFICIAL INTELLIGENCE AND SOCIAL-EMOTIONAL LEARNING AS TOOLS FOR PREVENTING ANTISOCIAL BEHAVIOR IN SCHOOLS

Abstract

This study examines the role of artificial intelligence (AI) and social-emotional learning (SEL) in preventing antisocial behavior among school students within contemporary educational environments. The research analyzes the pedagogical, psychological, and social factors contributing to the development of antisocial behaviors, including aggression, cyberbullying, social isolation, disruptive conduct, and internet addiction. Particular attention is given to the integration of AI-powered educational technologies for early identification of behavioral risks, continuous monitoring of students' learning activities, and personalized pedagogical support. The study further explores how SEL competencies—such as self-awareness, self-regulation, empathy, responsible decision-making, and relationship skills—contribute to reducing behavioral problems and fostering positive school climates. Based on a comprehensive review of contemporary literature and pedagogical approaches, the paper proposes an integrated framework combining AI-driven analytics with SELbased interventions to enhance preventive practices in schools. The findings suggest that the effective integration of artificial intelligence, social-emotional learning, and collaborative efforts among teachers, parents, and school psychologists can significantly reduce the incidence of antisocial behavior while promoting students' well-being, digital citizenship, and positive social development. The proposed framework provides practical recommendations for educational policymakers and practitioners seeking to establish safer, more inclusive, and learner-centered digital learning environments