Mentigo: An Intelligent Agent for Mentoring Students in the Creative Problem Solving Process

Creative Problem-Solving (CPS) promotes creative and critical thinking while enhancing real-world problem-solving skills, making it essential for middle school education.However, providing personalized mentorship in CPS projects at scale is challenging due to resource constraints and diverse student needs.To address this, we developed Mentigo, an AI-driven mentor agent designed to guide middle school students through the CPS process.Using a dataset of real classroom interactions, we encoded CPS task stages, adaptive guidance strategies, and personalized feedback mechanisms to inform Mentigo's dynamic mentoring framework powered by large language models (LLMs).A comparative experiment with 12 students and evaluations from five expert educators demonstrated improved student engagement, creativity, and task performance.Our findings highlight design implications for using LLM-based AI mentors to enhance CPS learning in educational environments.