Orderliness predicts academic performance: behavioural analysis on campus lifestyle

Area of Science:

• Educational Data Mining
• Behavioral Science
• Higher Education

Background:

• Personalized education requires understanding student behavior and academic performance.
• Previous studies relied on surveys; unobtrusive digital data offer new insights into student lifestyles.
• Smart card data provide large-scale, objective behavioral records.

Purpose of the Study:

• To investigate the relationship between student behavioral patterns and academic performance using smart card data.
• To introduce and validate 'orderliness' as a novel metric for campus daily life regularity.
• To assess the predictive power of orderliness and diligence on academic performance (GPA).

Main Methods:

• Collected smart card behavioral records from 18,960 undergraduate students.
• Developed an entropy-based metric ('orderliness') using shower and meal timestamps.
• Analyzed correlations between orderliness, diligence, and Grade Point Average (GPA).

Main Results:

• Academic performance (GPA) is significantly correlated with orderliness.
• Orderliness is a significant predictor of GPA, improving prediction accuracy.
• The study demonstrates the utility of unobtrusive digital data in educational research.

Conclusions:

• Orderliness, a measure of daily routine regularity, is a key factor in student academic success.
• Education administrators can use these findings to understand performance drivers and implement targeted interventions.
• Leveraging digital footprints offers a quantitative approach to supporting student well-being and academic achievement.