University Student Performance & Habits Dataset

Giving access to university student metrics from the Asia region focused on predicting Cumulative Grade Point Average (CGPA). It incorporates behavioral data including attendance, study habits, and lifestyle factors, though specific record counts and authorship dates are not documented in the source metadata.

Use Cases

• Predicting CGPA outcomes using attendance and study habit features
• Analyzing the correlation between lifestyle factors and academic success
• Feature engineering using categorical habit data to identify key performance indicators

Strengths

• Includes lifestyle data as predictors for academic performance
• Focuses specifically on the Asia geographic region
• Combines categorical and text-based features for multi-modal modeling

Limitations

• Lack of documented metadata regarding sample size and specific feature definitions
• Potential for self-reporting bias if data was gathered via student surveys
• Unknown temporal relevance due to missing update and collection timestamps

Provenance

Geography

Asia