Exploring Artificial Intelligence Tutor Adaptability to Harness Epistemic Curiosity and Promote Learning in Applied Mathematics and Life Sciences

This study investigates the impact of an Artificial Intelligence (AI) tutor teammate on student engagement driven by curiosity and the effectiveness of learning during Interactive Molecular Dynamics (IMD) tasks on the Visual Molecular Dynamics platform. It examines how the AI’s behaviors in triggering curiosity and responding to student inquiries affect the frequency and complexity of questions students initiate. Using Cross Recurrence Quantification Analysis (CRQA), the study examined structural alignment in coordination and its connection to communication behaviors. Teams that performed well showed superior task completion, a deeper understanding of the material, and heightened engagement. Advanced questions were linked to the AI’s ability to trigger curiosity, indicating increased engagement and cognitive complexity. The CRQA metrics also highlighted dynamic synchronization in the interactions between students and the AI tutor teammate, emphasizing the importance of structured yet adaptable engagement to foster curiosity.