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While traditional mock trials are foundational to legal education, the rise of generative AI offers novel pedagogical approaches. This study investigates an AI-powered multi-agent system as a new method for developing students’ core legal and cognitive skills. We compared the effects of multi-agent practice with the traditional self-directed group practice on law students' learning outcomes. Using a crossover experimental design, 30 undergraduate law students participated in both conditions. Quantitative and qualitative data were collected and analysed to assess learning satisfaction, mock trial abilities, and cognitive development. Findings revealed that while overall satisfaction levels were comparable, multi-agent practice significantly enhanced students’ problem-solving skills, critical thinking, creativity, and perspective-taking. Qualitative analysis attributed this effectiveness to the system's structured feedback, variety of roles, and immersive scenariosThis study provides evidence that AI-powered multi-agent practice is a potent tool for legal education, particularly for cultivating higher-order cognitive skills. In addition the findings pointed a blended approach that integrating multi-agent systems into legal curricula to complement traditional methods and better prepare students for complex legal practice.
Shi et al. (Wed,) studied this question.