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SmartScore

SmartScore is an innovative software developed by our team, which secured an impressive 4th position out of 64 competing teams in a Texas A&M artificial intelligence and machine learning focused hackathon. The team, comprised of Adam Chawdhury, Johnnie Chen, Julio Dondisch, and Dakota Pound, collaborated to create a powerful tool that automates the grading process for free response questions in math and physics exams.

Features

  • Handwritten Text Recognition (OCR): SmartScore utilizes Optical Character Recognition to convert handwritten responses into LaTeX format, ensuring accurate interpretation of students' answers.

  • Automatic Grading: The software automates the grading process, enabling efficient evaluation of free response questions in math and physics exams.

  • Database Management: SmartScore manages classes and stores students' answers in a SQLite database, providing a structured and organized way to access and review the data.

  • Python Implementation: Developed using Python, SmartScore leverages the language's versatility and robust libraries to create a reliable and efficient grading system.

How It Works

  1. Input: The software takes free response answers from students, whether handwritten or typed.

  2. OCR Processing: Handwritten responses are processed using OCR, converting them into LaTeX for accurate interpretation.

  3. Grading Algorithm: SmartScore employs a sophisticated grading algorithm to evaluate the correctness and quality of the answers.

  4. Database Storage: Student information, class details, and graded responses are stored in a SQLite database, facilitating easy access and analysis.

Contributors

License

This project is licensed under the MIT License - see the LICENSE file for details.