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This study examines the impact of problem posing on students’ emotions during mathematical modeling tasks. Mathematical modeling involves posing and solving real-world problems using mathematical methods, enhancing students’ understanding and engagement. However, the emotional responses elicited during these tasks are not well studied. Emotions significantly influence student engagement and learning efficacy, with AI-based facial recognition offering a novel method for their analysis. This research investigates how emotional experiences influence the outcomes of problem-posing and modeling processes. The study aims to bridge the gap in the literature by integrating problem posing into modeling tasks, providing a holistic view of the modeling process, and employing advanced emotion analysis to assess student emotions.