Generative AI in Mental Health Training: A Human Factors Approach to Active Learning and Pedagogical Innovation

This study examines the use of generative artificial intelligence (GenAI) as a simulation environment for mental health training. Drawing on a human factors and active learning perspective, this study explores how interactions between psychology students and AI-simulated patients may support the development of professional competencies, formative assessment, and reflective learning. An exploratory mixed-methods design was conducted with 40 final-year psychology students who completed simulated initial clinical interviews using ChatGPT. The simulation environment was iteratively designed through expert interviews and human factors principles. Interaction corpora were analyzed using natural language processing techniques, categorical analysis, and exploratory interaction metrics. Results describe the design of the simulation environment, the intervention categories that emerged during consultations, a set of linguistic, cognitive, and temporal indicators for interaction analysis, and students’ perceptions of the pedagogical value and limitations of the experience. Findings suggest that GenAI-based simulations can support competency-oriented training by generating rich interaction data for reflection, feedback, and curriculum development.