https://github.com/khaledkamr/muster
A web-based platform designed to centralize and visualize academic data (attendance, grades, assignments) with dashboards for professors, students, and parents. with AI-driven insights including predictive analytics, clustering, and course recommendations.
https://github.com/khaledkamr/muster
blade bootstrap css javascript laravel11 mysql php
Last synced: 2 months ago
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A web-based platform designed to centralize and visualize academic data (attendance, grades, assignments) with dashboards for professors, students, and parents. with AI-driven insights including predictive analytics, clustering, and course recommendations.
- Host: GitHub
- URL: https://github.com/khaledkamr/muster
- Owner: khaledkamr
- Created: 2025-03-02T22:00:43.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-08-09T14:57:19.000Z (11 months ago)
- Last Synced: 2025-08-09T16:32:16.041Z (11 months ago)
- Topics: blade, bootstrap, css, javascript, laravel11, mysql, php
- Language: Blade
- Homepage:
- Size: 12.9 MB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Muster: University Dashboard System with AI-Driven Analytics
## Overview
**Muster** is a web-based university dashboard developed as a graduation project at **Misr University for Science and Technology**. It enhances educational decision-making by integrating academic data with AI-powered insights through customized interfaces for **professors**, **admins**, **students**, and **parents**.
The system provides visualizations and predictive analytics on grades, attendance, assignments, and course data, leveraging cutting-edge AI techniques such as:
- **Logistic Regression**: Predicts student dropout risk
- **LSTM-based RNN**: Forecasts future GPA
- **K-Means Clustering**: Categorizes student performance
- **Content-Based Filtering**: Recommends personalized courses
---
## Database Schema
---
## Professor Interface
Professors can manage courses, track students performance, and act on predictive insights with dashboards tailored to academic engagement:
- **Students Dashboard**: view all students and cluster them as groups based on their performance.
- **Exams Dashboard**: view all assessments with detailed statistics.
- **Grades Dashboard**:
- Searchable tables for all the students with all types of assessments.
- Classify students (***on track*** or ***at risk***) and send feedbacks.
- **Attendance Dashboard**:
- view all the attendances over the weeks with the session type.
- charts to visualize the weekly attendance trend and attendance distribution.
- **Assignments Dashboard**: Track student submissions and scores.
- **Student & Course Metrics**: view all the academic statistics for one student in specific course.
---
## Admin Interface
Admins can manage courses and users with full CRUD operations. They can also view analytics on courses, users, and professor feedbacks.
- **Courses Dashboards**:
- manage CRUD operations on courses.
- charts to visualize courses analytics.
- **Users Dashboard**:
- manage CRUD operations on users
- charts to visualize users analytics (professors, students).
- **Feedbacks Dashboard**:
- track professors feedback about students.
- track students feedback about professors.
- track students feedback about courses content.
---
## Student Interface
Students receive a personalized dashboard to monitor academic progress and receive AI-backed recommendations:
- **Courses Dashboard**:
- view all current semester courses with overview and progress.
- courses total grades chart to visualize difference performance between courses.
- GPA and CGPA prediction for the current semester based on performance.
- **Course Recommendations**: AI-based elective courses suggestions tailored to strengths and progress.
- **Grade Summary**:
- show grades statistics for selected semester.
- charts to visualize grades distribution and GPA trend over semesters.
- **Assignment Tracker**:
- view assignments status and upcoming assignments.
- Completion charts and score trends.
- **Attendance Record**:
- Weekly and overall attendance visualizations with attendance rate.
- show attendance details and rate for each course.
- **Course Details**: view all the academic statistics for each course.
---
## Parent Interface
Parents are offered an intuitive dashboard to stay engaged with their child’s academic journey:
- **Child Dashboards**: Dashboard for each child if having more than one.
- **Courses Dashboard**: current semester courses with overview and progress.
- **Grade Summary**: show grades statistics for selected semester.
- **Assignment Completion**: See pending/submitted assignments and deadlines.
- **Class Attendance Rate**: Charts showing attendance performance and rate.
- **Professors Feedbacks**: Review professors feedbacks about student.
---
## Technical Details
### Technologies
- PHP Laravel (core logic)
- Flask API (AI model integration)
- MySQL (data storage)
- JavaScript + Bootstrap (responsive UI)
- Chart.js (interactive charts)
- Python with `scikit-learn` and `TensorFlow`
- Logistic Regression (Dropout prediction)
- K-means Clustering (Performance segmentation)
- Content-Based Filtering (Course suggestions)
- LSTM RNN (GPA forecasting)
---
## How to use
### Prerequisites
- PHP 8.2.12
- Composer
- MySQL
- web server (Apache/Nginx)
or you can just install XAMPP and Compoaer
### Instal Laravel
```bash
composer global require laravel/installer
```
### Install project
```bash
git clone https://github.com/khaledkamr/Muster.git
```
### configurations
- Copy the `.env.example` file to create a `.env` file:
```bash
cp .env.example .env
```
- Edit the `.env` file to configure your environment settings, such as:
- Database connection.
- App URL (`APP_URL`) and other settings as required.
- Generate an application key:
```bash
php artisan key:generate
```
### Set Up the Database
- Create a database in your database management system.
- Update the `.env` file with your database credentials.
- Run migrations to set up the database schema:
```bash
php artisan migrate
```
- Run database seeders:
```bash
php artisan db:seed
```
### Run the Application
- Run laravel server
```bash
php artisan serve
```
This will start the server, typically at `http://localhost:8000`.
- Run flask APIs
```bash
python python_scripts/APIs/model_endpoints.py
```
This will start the server, typically at `http://127.0.0.1:5000`.