{"repo":"AmirhosseinHonardoust/Academic-Instability-Early-Warning-System","free":true,"listed":false,"github":"https://github.com/AmirhosseinHonardoust/Academic-Instability-Early-Warning-System","clone":"git clone https://github.com/AmirhosseinHonardoust/Academic-Instability-Early-Warning-System.git","description":"An interpretable early-warning engine that detects academic instability before grades collapse. Instead of predicting performance, it models pressure accumulation, buffer strength, and transition risk using attendance, engagement, and study load to explain fragility and identify high-leverage interventions.","language":"Python","stars":18,"topics":["academic-performance","ai-in-education","counterfactual-analysis","data-visualization","decision-support","early-warning-systems","education-analytics","equilibrium-modeling","ethical-ai","explainable-ai"],"license":"MIT","category":"analytics","readme_excerpt":"Academic Instability Early Warning System --- Grades are lagging indicators. Instability is the leading signal. The Academic Instability Early Warning System is an interpretable, force-based analytics engine designed to surface academic fragility before performance collapses . Rather than predicting grades or labeling students as “at risk,” this system models pressure accumulation, buffering capacity, and transition instability to expose early warning signals that are otherwise invisible in traditional educational analytics. At its core, this project reframes academic performance as a dynamic equilibrium , not a static outcome. --- Why This Project Exists Most educational analytics systems ask: “Will this student fail?” That question is asked too late . By the time grades collapse: pressure has already accumulated adaptation has already failed intervention becomes reactive instead of supportive This system asks a different, more useful question: “Is this student’s academic equilibrium becoming unstable, and why?” That shift in framing changes everything . --- From Prediction to Instability Detection Traditional approaches focus on outcomes : final grades pass/fail probabilities risk classification This system focuses on process : pressure buildup weakening buffers loss of recovery capacity Grades are treated as lagging indicators , useful for validation, but not for early action. Instability is treated as a leading signal . --- Dataset Student Performance Dataset Author: alii","default_branch":null,"files":null,"tree":[],"storefront":"/r/AmirhosseinHonardoust","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/AmirhosseinHonardoust/Academic-Instability-Early-Warning-System/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}