Exploring the Application of Generative AI Agents to Higher Education: A Case Study of "Preschool Educational Psychology"

This paper presents a case study on the design, implementation, and evaluation of generative artificial intelligence (AI) agents for personalized teaching in higher education, focusing on the Preschool Educational Psychology course. By integrating generative AI technologies with pedagogical frameworks, we developed an AI agent system comprising two dimensions: a Learning Theory Agent (LTA) and a Research Advancement Agent (RAA). This system addresses challenges in student-centered learning and instructor-led pedagogy through structured knowledge integration, automated workflows, and data-driven analysis, enabling personalized learning pathways, real-time feedback, and adaptive teaching strategies. Semi-structured interviews with students and course instructors highlighted AI’s educational benefits: structured knowledge support, innovative analytics, and efficient information integration. Limitations included theoretical gaps, rigid interaction patterns, and cognitive rigidity risks. Future work should emphasize collaborative synergy between AI-driven efficiency and human educators’ strengths in emotional intelligence and individualized mentoring, aiming to establish a sustainable model for AI-enhanced higher education.