AutoScore aims to simplify the free response grading pipeline faced by instructors by utilizing ML methodologies to predict whether or not a student's answer is deemed correct.
With a great amount of experience teaching and tutoring at the university level, we knew there was a lot to be desired in the grading experience for both students and instructors. We wished that there was a way students could receive feedback quickly and overworked instructors could focus their attention on more impactful things than grading. As a result, we decided to build a tool that would auto grade short answer response while allowing a high degree of accuracy and customization.
Given a student response, our program analyzes the similarity to teacher provided answers. Furthermore, it uses GPT to provide quick feedback for students.
We used ChromaDB to handle our vector database operations and GPT4 to provide feedback for students. For our front-end, we used Reflex as our full-stack solution.
- chroma
- gpt-4
- python
- reflex
- scikit-learn