This project implements a machine learning model for text analysis and feedback, focusing on student assignments. The system reads PDF files, processes the text, matches keywords against a given solution, provides grading, and generates constructive feedback. Additionally, it includes a dashboard for visualizing student performance and analysis results with dashboard.
- Text Extraction 📄: Reads and extracts text from PDF files.
- Text Processing 🛠️: Tokenizes, lemmatizes, and removes stopwords from the text.
- Keyword Matching 🔍: Compares student text with solution keywords and calculates match scores.
- Grading and Feedback 🎓: Assigns grades based on keyword usage and text coherence, providing specific feedback for improvement.
- Dashboard 📊: Visualizes performance metrics and feedback using interactive graphs.
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Clone the Repository
git clone https://github.com/avadheshgithub/Automated-Grading-System.git cd student-text-analysis -
Set Up Virtual Environment
python -m venv venv source venv/bin/activate # On Windows, use `venv\Scripts\activate`
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Install Dependencies
pip install -r requirements.txt
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Extract Text from PDFs
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Preprocess Text
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Calculate Match Score
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Generate Feedback
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Run Dashboard
Feel free to fork this project and contribute by creating pull requests. For major changes, please open an issue first to discuss what you would like to change.