Expert Agents for Social and Emotional Learning: An Agentic Graph Retrieval Augmented Generation Approach

The positive impact of Social and Emotional Learning (SEL) activities in schools is widely recognized in various sectors, including mental health, social relationships, and academic performance of students. This impact can be efficiently realized and catalyzed based on the development of tools that help teachers to effectively and consistently apply SEL in classrooms. Such tools can leverage emerging Artificial Intelligence (AI) technologies, including Generative AI (GenAI) and Agentic AI, and Knowledge Graphs to enable their ease of adoption and use by teachers and provide accurate and context-aware guidance. In this perspective, this manuscript presents an Agentic Graph Retrieval-Augmented Generation (RAG) approach to support educators to apply methodologies for SEL. The approach is materialized through an agent, called MySELAgent, which synthesizes information and provides recommendations around SEL, taking advantage of GenAI and following an Agentic AI approach. MySELAgent is interoperable with third-party psychometric tools, enabling assessment and monitoring of the social and emotional competencies of students. It is able to suggest evidence-based targeted SEL activities and create holistic SEL intervention programs in the form of learning pathways, which are based on teachers’ pReferences and students’ emotional needs. A detailed evaluation of the implemented techniques is presented, analyzing the performance and effectiveness of MySELAgent on retrieving information and creating accurate responses based on the use of different Large Language Models (LLMs).