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.
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.
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7
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Language
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License
MIT
Category
Last pushed
Jan 27, 2026
Commits (30d)
0
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