mdzaheerjk/Academic-Risk-Engagement-Prediction-System

This project predicts student academic outcomes using demographic, academic, and behavioral data. It applies ML classification and probabilistic modeling with preprocessing, feature importance analysis, and evaluation to identify at-risk students and support data-driven decisions.

25
/ 100
Experimental

This system helps educators and administrators identify students who are at risk of poor academic outcomes and disengagement. By inputting student demographic information, past academic records, and behavioral data, it generates predictions about student performance and engagement levels. The insights can then be used by school counselors, academic advisors, and institutional leaders to make informed decisions and provide targeted support.

Use this if you need to proactively identify students who might struggle academically or disengage, allowing for early intervention and support.

Not ideal if you're looking for a system that provides real-time tutoring recommendations or direct student-facing interventions.

education-management student-retention academic-advising institutional-planning student-support-services
No Package No Dependents
Maintenance 10 / 25
Adoption 4 / 25
Maturity 11 / 25
Community 0 / 25

How are scores calculated?

Stars

7

Forks

Language

License

MIT

Last pushed

Jan 27, 2026

Commits (30d)

0

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