Automatic System for Case-Based Collaborative Learning: Visual Design and Formation of Work Groups by Personality Affinity

This project aims to enhance the effectiveness of the DentaLAV educational platform, used for collaborative learning based on clinical dental cases, by addressing the limitation of its current random student assignment system. The research focuses on the influence of personality on academic performance and engagement in web-based learning environments. The main objective is to develop a transdisciplinary study integrating engineering, psychology, and graphic design to create an artificial intelligence algorithm that forms collaborative learning groups based on personality affinities identified through psychological metrics. The methodology involves continuous IT development of the platform, the creation and refinement of an optimized graphical interface, and the implementation of rigorous psychological evaluations. Pilot assessments and full academic cycles will be conducted to validate the usability, applicability, and impact of the new group formation system, ultimately optimizing collaboration and student engagement in solving clinical cases.<br/><br/><b>Goal</b>: <br/>To develop and evaluate an educational platform for peer interaction in case-based learning, focusing on creating an artificial intelligence algorithm for forming learning groups based on personality affinities.<br/><br/><b>Research lines</b>: <br/>Educational entertainment (Edutainment)