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In this study, we proposed a group formation method that focuses on the diversity of emotions estimated from speech and facial expressions, with the aim of improving learning outcomes in collaborative learning. By optimally combining learner characteristics using a genetic algorithm, we achieved the activation of dialogue and the promotion of deep understanding. This achievement was recognized, and Ms. Haruka Tada received the Student Presentation Encouragement Award at the Cloud Network Robot Research Meeting.