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  Student Risk Early Warning System

Inspiration

Educational institutions lose thousands of students every year not because of lack of ability, but because early warning signs such as stress, absenteeism, financial hardship, and disengagement go unnoticed. We wanted to build a data-driven, AI-enabled early warning system that detects these signals early so educators can act before it is too late.

What it does

Student Risk Early Warning System uses AI-driven risk scoring and Tableau analytics to analyze academic performance, attendance, behavioral patterns, and engagement data. The dashboards identify high-risk students, visualize contributing risk factors, and recommend intervention levels so educators can prioritize support and prevent dropouts.

How we built it

We created a structured dataset of student performance and 12 key risk indicators and connected it to Tableau. Using Tableau’s interactive visual analytics, we built dashboards showing risk levels, attendance trends, stress indicators, and intervention needs. An AI-based risk model converts raw data into dropout probability and actionable insights in real time.

Challenges we ran into

One of the main challenges was designing a risk model that reflects real-world student problems, not just grades. We had to carefully balance academic, behavioral, emotional, and socio-economic factors to create a fair, explainable, and trustworthy AI risk score.

Accomplishments that we're proud of

We successfully built a working AI-powered analytics system that identifies high-risk students and clearly explains why they are at risk. The Tableau dashboards transform complex data into clear, decision-ready insights that enable early and effective intervention.

What we learned

We learned that data, AI, and visualization together are far more powerful than charts alone. When multiple risk indicators are combined into a single, intuitive Tableau view, educators can move from guesswork to evidence-based, proactive action.

What’s next for Student Risk Early Warning System

Next, we plan to integrate real-time data from learning platforms and student information systems, expand the AI-based risk prediction models, and add RAG-based intelligent recommendations so schools can deliver personalized, automated support for every student.

Built With

• ai
• data-analytics
• data-visualization
• predictive
• tableau