EduGenius
EduGenius is an innovative AI-powered tutoring platform developed by us who are three undergraduates at the Department of Computer Science and Engineering, University of Moratuwa, as our Semester 5 project.
The platform addresses challenges in modern education by offering personalized and efficient tutoring for O/Level students in mathematics. Leveraging advanced technologies such as LangChain and pre-processed mathematics marking schemes stored in a vector database, EduGenius generates tailored tutoring materials and provides instant, real-time feedback and grading. This approach enhances the learning experience, empowering students with a more interactive and supportive learning environment.
Let’s dive into a quick tour of the EduGenius platform
Features
- User Registration & Login: Users can register and log in using their email addresses. Password recovery is also supported.
- Math Problem Solving: Students can select math problems, submit their answers via images or canvas input, and receive immediate feedback.
- Hints & Tips: If students get stuck, they can request hints from the system.
- Feedback & Scoring: EduGenius provides feedback on students’ answers and scores them based on correctness.
- Question Clarification: Students can ask questions related to the problems and get clarifications from the system.
- User Feedback: Users can provide feedback on their tutoring experience.
- Past Session Review: Users can review their past tutoring sessions and check the marks obtained.
- Math Solving Tool: Integrated with Wolfram Alpha’s API for step-by-step math problem solutions.
- Admin Features: Admins can manage content, user accounts, and generate reports.
Refer the documentation for the technical details of the project.
Installation
- Clone the repository:
Clone the repository to your local machine using the following command:
git clone https://github.com/Irash-Perera/EduGenius.git - Install the dependencies:
Navigate to the project directory and install the required dependencies using the following command:
pip install -r requirements.txt - Run the application:
Run the application using the following command:
streamlit run app.py
Contributors
