This dataset tracks student academic behaviors across categories including study hours, online course enrollment, and sleep patterns. It maps these behavioral inputs against final exam performance to facilitate educational outcome analysis.
Use Cases
- Train a linear regression model to estimate exam scores using the study hours and sleep habits features.
- Perform a feature importance analysis to determine if online courses or study hours have a higher correlation with exam performance.
- Cluster students into performance groups based on their reported learning habits and sleep patterns.
Strengths
- Quantifies study hours as a variable for correlation analysis.
- Includes data on online course participation to measure digital learning impact.
- Captures sleep habit information to evaluate the role of rest in exam performance.