The EssayEvalPro is a system designed specifically for teachers to assist them in evaluating essays submitted by their students. The system leverages Natural Language Processing (NLP) techniques to provide a comprehensive analysis of each essay, including plagiarism detection, relevancy assessment, and grammar error identification.
- Plagiarism Detection: The system compares the submitted essay with a database of existing essays to determine the extent of similarity and identify potential instances of plagiarism.
- Relevancy Calculation: By utilizing NLP techniques, the system calculates the relevancy of the essay based on its title, allowing teachers to assess how well the content aligns with the chosen topic.
- Grammar Mistake Analysis: The system employs NLP capabilities to analyze the essay and highlight any grammar mistakes or errors, helping students improve their writing skills.
- Score Generation: After evaluating the essay for plagiarism, relevancy, and grammar mistakes, the system generates a score that reflects the overall quality and originality of the submitted work.
- Plagiarism Detection: When an essay is submitted, the system compares it against the existing essays in its database using NLP techniques. It calculates the degree of similarity and identifies any instances of potential plagiarism.
- Relevancy Calculation: The system then uses NLP methods to evaluate the relevancy of the essay by analyzing the title and its alignment with the content. This analysis helps teachers assess the coherence and suitability of the essay's topic.
- Grammar Mistake Analysis: Next, the system employs NLP tools to identify and highlight grammar mistakes and errors within the essay, providing valuable feedback to students for improvement.
- Score Generation: Based on the results obtained from the plagiarism detection, relevancy calculation, and grammar mistake analysis, the system generates a comprehensive score that reflects the quality and originality of the essay. This score assists teachers in objectively assessing and providing feedback to the students.
Note: This project is only tested on python 3.8
To set up the EssayEvalPro System, follow these steps:
- Clone the repository:
git clone https://github.com/MaazLab/EssayEvalPro.git
- Install the necessary dependencies:
pip install -r requirements.txt
- figure the system:
- Provide access to the existing essay database or configure a new database.
- Adjust any settings or parameters as per your requirements.
- Run the system:
python app.py
Contributions to the Essay Relevance and Plagiarism Detection System are welcome. To contribute, follow these steps:
- Fork the repository.
- Create a new branch for your feature or bug fix.
- Make the necessary changes and commit them.
- Push your changes to your forked repository.
- Submit a pull request, describing your changes in detail. Please ensure that your contributions align with the project's coding standards and guidelines.
If you have any questions, suggestions, or feedback regarding the Essay Relevance and Plagiarism Detection System, please feel free to reach out to us at [maaz.rafique.75@gmail.com]
Happy evaluating!