Acadex
Our project is a University Exam Planner and Academic Management System that automates key academic processes like attendance, course management, timetable scheduling, and student risk prediction. It uses a Spring Boot backend, React frontend, MySQL database, and integrates a Machine Learning model (Logistic Regression via Flask) to predict student performance risk. The system improves efficiency, reduces manual work, and provides intelligent insights for better academic planning.
Our project is a full-stack academic management system designed to streamline university operations and enhance decision-making using both traditional backend logic and machine learning.
🧩 Core Modules:
User Management: Role-based access (Admin, Faculty, Student) using JWT authentication.
Attendance System: Faculty can mark attendance based on timetable and subjects.
Course & Subject Management: Courses, topics, and faculty assignments are handled dynamically.
Timetable Management:
Manual scheduling
Auto-generation using optimization logic (conflict-free scheduling)
Exam & Assignment Tracking: Helps monitor student performance.
🤖 Machine Learning Integration:
We implemented an ML-based Student Risk Prediction System:
Model used: Logistic Regression
Built using Python + Flask + scikit-learn
Predicts whether a student is:
LOW risk
MEDIUM risk
HIGH risk
Features used:
Attendance
Exam scores
Assignment scores
Failures
Study time
The Spring Boot backend calls the ML API and shows predictions in the UI, with fallback logic if ML fails.
⚙️ Tech Stack:
Frontend: React (Vite) + Tailwind CSS
Backend: Spring Boot (REST APIs, Security, JPA)
Database: MySQL
ML Service: Python Flask
Tools: Maven, Node.js
🚀 Key Highlights:
Full end-to-end system (frontend + backend + ML)
Real-time API integration between Java and Python
Smart automation (timetable + risk prediction)
Scalable and modular architecture