Characterization of the stress level of university students using data mining algorithms
Journal: Frontiers in Research Metrics and Analytics
Year: 2025

There is concern about the levels of stress faced by college students and their effects on mental health and academic performance. This study aimed to characterize academic stress levels in college students, using data mining algorithms to classify and predict risk patterns. Data were collected from 287 students using the SISCO Academic Stress Inventory, and classification algorithms and association rules were applied using WEKA software. The results revealed that 75.3% of the students experienc