Automated student assignment evaluation using NLP — reduces manual grading effort and provides data-driven insights for educators.
git clone <repository_url>
pip install -r requirements.txt
streamlit run main.py| Metric | Details |
|---|---|
| Sentiment | Polarity, subjectivity, positive/negative scoring |
| Language Complexity | Fog index, sentence length, complex word % |
| Structure | Word count, paragraph organisation, coherence |
| Plagiarism | Algorithmic similarity scoring |
| Hypothesis Testing | Zero-shot classification via HuggingFace |
Log in to the admin panel → view assignment summaries → click any assignment for a full breakdown. Navigate to Student-wise Report for per-student metrics. All results are stored in SQLite and visualised as bar charts and scatter plots.
Python 3 · Streamlit · NLTK · HuggingFace Transformers · SQLite
Licensed under MIT.