EduAnalysis - Student Performance Feedback Report Generator

A Flask-based web application that processes student test performance data, generates personalized feedback using Google Gemini API, creates visualizations, and produces comprehensive PDF reports with actionable insights.

Features

• Automated Data Processing: Parses JSON test data to extract comprehensive performance metrics
• AI-Powered Feedback: Generates personalized feedback using Google Gemini API
• Dynamic Visualizations: Creates interactive charts using Plotly for performance analysis
• PDF Report Generation: Produces structured reports with ReportLab integration
• Web Interface: User-friendly Flask application for file upload and report generation

Tech Stack

• Backend: Flask, Python
• AI Integration: Google Gemini API (gemini-1.5-flash)
• Data Visualization: Plotly, Pandas
• PDF Generation: ReportLab
• File Processing: JSON parsing with comprehensive data extraction

Report Structure

The generated PDF report includes:

1. Introduction & Overview: Personalized motivational message with performance highlights
2. Performance Analysis:
   • Overall performance metrics
   • Subject-wise breakdown
   • Chapter-wise analysis
   • Difficulty-level insights
   • Concept-wise performance
3. Time Management Analysis: Time vs accuracy correlation insights
4. Actionable Recommendations: Data-driven suggestions for improvement
5. Visual Analytics: Comprehensive charts and graphs on separate pages

Installation

Prerequisites

• Python 3.8+
• Google Gemini API key

Setup

1. Clone the repository

   git clone <repository-url>
   cd student-performance-analyzer

2. Create virtual environment

   python -m venv venv
   source venv/bin/activate  # Windows: venv\Scripts\activate

3. Install dependencies

   pip install -r requirements.txt

4. Configure environment variables

   # Create .env file
   echo "GOOGLE_API_KEY=your-google-api-key" > .env

5. Install system dependencies (for chart rendering)

   # Ubuntu/Debian
   sudo apt-get install libcairo2 libpango1.0-0 libgdk-pixbuf2.0-0
   
   # macOS
   brew install cairo pango

Usage

1. Start the application

   python app.py

2. Access the web interface

   • Navigate to http://localhost:5000
   • Upload JSON test data file
   • Preview generated statistics
   • Download comprehensive PDF report

API Integration

Google Gemini API

The application leverages Google's Gemini 1.5 Flash model for generating contextual, personalized feedback. The AI analyzes performance patterns and provides:

• Personalized introductions highlighting strengths and improvement areas
• Detailed performance breakdowns across multiple dimensions
• Time management insights and recommendations
• Actionable, data-driven suggestions for academic improvement

Dependencies

Flask==2.3.2 
google-generativeai==0.7.2 
matplotlib==3.7.1 
reportlab==4.2.2
markdown==3.4.3
python-dotenv>=1.0.1
pandas==2.2.2 
plotly==5.24.0
kaleido==0.2.1
gunicorn==22.0.0

Configuration

Environment Variables

GOOGLE_API_KEY=your-google-gemini-api-key
SECRET_KEY=your-secret-key-for-dev

API Key Setup

1. Visit Google Cloud Console
2. Enable the Gemini API
3. Create credentials and obtain your API key
4. Add the key to your .env file

Data Format

The application expects JSON input with the following structure:

• Overall performance metrics
• Subject-wise breakdown
• Individual question details with chapters, difficulty levels, and concepts
• Time tracking data

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Please ensure your code follows PEP 8 style guidelines and includes appropriate documentation.

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Thank you for using Student Performance Feedback Report Generator!

Hoping this tool helps educators and students gain valuable insights into academic performance.