Study goals
To evaluate the effectiveness of a tool integrating artificial intelligence and neuroscience in measuring students’ experience in short-term courses, considering emotional and behavioral indicators to support pedagogical and institutional decisions in corporate education processes.
Relevance / originality
This study proposes integrating artificial intelligence and neuroscience into educational experience management, replacing exclusively subjective methods. The proposal addresses gaps in short-term course measurement, enabling more precise and useful information for pedagogical and administrative improvements.
Methodology / approach
Qualitative research with exploratory and exploratory-descriptive strategy. Primary data collected through semi-structured interviews with manager, coordinators, and instructors, analyzed using content analysis and interpretative text analysis. Convenience sampling included diverse perspectives from course operation and management.
Main results
Implementation of a system integrating artificial intelligence and neuroscience to measure educational experience. The solution will enable real-time monitoring, reporting, pedagogical adjustments, strengthened partnerships, and adaptation to different courses, increasing effectiveness and institutional impact.
Theoretical / methodological contributions
Advances the joint application of artificial intelligence and neuroscience in education. Develops an approach to integrate emotional and behavioral data into course evaluation, offering methodological references for studies in educational innovation and corporate learning management.
Social / management contributions
Strengthens institutional capacity to personalize courses and enhance student experience. Generates actionable data for managers, instructors, and client companies, increasing corporate training effectiveness and competitiveness in the professional education market.