COGNITIVE STRESS MONITORING AND LEARNING SUPPORT SYSTEM FOR STUDENTS

Abstract

Students' concentration, memory, reasoning and overall assessment are adversely impacted by stress. Traditional evaluation systems are mainly centered on grades and fail to take stress into account when assessing learning outcomes. The present study proposes the Cognitive Stress Monitoring and Learning Support System for Students which combines cognitive assessment and stress analysis for providing a more comprehensive evaluation of student performance. The system assesses student performance in five cognitive areas and measures the time taken to respond and includes physiological data like heart rate and heart rate variability (HRV). The system identifies weak areas, stress-prone tasks using a Random Forest classifier for stress and performance analysis, it can generate personalized study and stress-management suggestions via the FLAN-T5 Large Transformer model. The proposed system provides a systemic strategy to enhance student well-being and academic development.