CET Automated Grading System with AI Predictive Analytics in PHP and MySQL

System Description

The Automated Grading System with Predictive AI is a dynamic PHP/MySQL web application initially designed for a College of Engineering and Technology (CET). It moves beyond traditional grading by incorporating a native Predictive AI function powered by Simple Linear Regression. By analyzing a student's historical grade data across various terms (Prelims, Midterms, Pre-Finals), the system forecasts their trajectory and predicts their upcoming final score.

The system is highly portable and secure, built with an auto-updating database schema architecture. It features a modern, fully responsive UI styled with Tailwind CSS, and utilizes Tom Select for smooth, searchable dropdowns. It includes a strict Role-Based Access Control (RBAC) system handling Administrators, Faculty Members, and Students, complete with secure deletion authorizations and comprehensive activity logging.

Features

Administrator Features:

System Dashboard: Overview of all enrolled students grouped by Year Level and Section.

User Management: Create, edit, and delete Admin, Faculty, and Student accounts.

Manage Subjects: Add course offerings with Program, Code, Name, School Year (dynamically auto-generated), and Semester.

Faculty Assignment: Assign specific subjects to specific faculty members.

Activity Logs Panel: Track all user logins, logouts, grade additions, and system updates with timestamps.

Secure Deletion: High-level actions (deleting users or subjects) require an active Admin Password to execute.

Student Profiling: Edit student ID numbers, names, year levels, and sections directly from the dashboard.

Faculty Features:

Add Grades: Record term grades (Prelim, Midterm, Pre-Final, Final).

Assigned Subjects Only: Faculty can only add grades for subjects specifically assigned to them by the Admin.

View Analytics: Access the AI predictive dashboard for any student to view their academic trajectory.

Student Features:

Self-Registration Portal: Students can create their own accounts and link them to their Student ID.

My Analytics Panel: A restricted dashboard where students can view their historical grades and AI-predicted upcoming grades.

Restricted Access: Students are securely blocked from accessing administrative settings, adding grades, or viewing other students' data.

General / System Features:

AI Grade Prediction: Uses a Simple Linear Regression algorithm to calculate performance trajectories (Improving, Declining, Neutral) and predict future term scores.

Searchable Dropdowns: Implements Tom Select for quick searching through hundreds of students or subjects in forms.

Auto-Database Configuration: The PHP script automatically alters/updates missing database columns upon launch.

Technologies Used

Backend: PHP 8+

Database: MySQL / MariaDB

Frontend Styling: Tailwind CSS (via CDN)

Icons: FontAwesome

JavaScript Plugins: Tom Select (for dynamic searchable dropdown options)

Installation Instructions

Download the source code zip file and extract it.

Turn on your local web server environment (e.g., XAMPP, WAMP, Laragon).

Open phpMyAdmin (usually http://localhost/phpmyadmin).

Create a new database named ai_grading_system.

Import the provided database.sql file into the newly created database.

Copy the index.php file into your local server's document root (e.g., htdocs or www folder). You can put it inside a folder like htdocs/grading_system/.

Open your web browser and navigate to the project URL (e.g., http://localhost/grading_system/index.php).

Default Login Credentials

Administrator Account:

Username: admin

Password: admin123

(Note: Faculty and Student accounts can be created within the Admin panel, or Students can use the Self-Registration link on the login page).

Snapshots

Admin Side - Subject Management

Admin Side - Student Analytics

Faculty Side - Dashboard

Student Side - Analytics

I hope this CET Automated Grading System with AI Predictive Analytics in PHP and MySQL Database will help you with what you are looking for.

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Screenshots

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