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

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Database Schema

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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.

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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.

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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.

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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.

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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)

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How to use

Prerequisites

• PHP 8.2.12
• Composer
• MySQL
• web server (Apache/Nginx)

or you can just install XAMPP and Compoaer

Instal Laravel

composer global require laravel/installer

Install project

git clone https://github.com/khaledkamr/Muster.git

configurations

• Copy the .env.example file to create a .env file:

  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:

  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:

  php artisan migrate

• Run database seeders:

  php artisan db:seed

Run the Application

• Run laravel server

  php artisan serve

  This will start the server, typically at http://localhost:8000.

• Run flask APIs

  python python_scripts/APIs/model_endpoints.py

  This will start the server, typically at http://127.0.0.1:5000.