AI Course Insights

AI Course Insights helps students optimize learning with data-driven feedback to improve performance. Students can feed the website their courses, assignments, and exams for personalized advice.

Comment

Inspiration

We wanted to learn how to effectively integrate the Gemini API into a full-stack application. Our goal was to create a platform that uses data-driven insights to help students optimize their learning and coursework. By leveraging the power of Gemini's text analysis capabilities, we set out to build a solution that improves student performance through intelligent feedback.

What it does

AI Course Insights allows users to add their classes and associate assignments with each one. Once users upload their assignments, we utilize the Gemini API to generate detailed, data-driven insights from the documents. These insights help students analyze their past work, understand where improvements are needed, and receive recommendations on how to better prepare for future exams. This feedback aims to enhance academic performance by offering personalized guidance based on real data.

How we built it

Our tech stack includes MongoDB, Express.js, React, and Node.js (MERN), which we used to create a responsive, dynamic platform for users. MongoDB helps manage class data, while Express and Node.js provide the backend infrastructure to handle API requests and user interactions. React is used for building the front-end interface, ensuring a smooth user experience. We used Git for version control, enabling seamless collaboration and code management throughout the development process.

Challenges we ran into

We encountered several challenges during the development process, especially with version control when managing our codebase through Git. Another major hurdle was working with the Gemini API. Specifically, we struggled with prompting the API in a way that it could process uploaded documents and extract useful insights. The API had certain limitations regarding document formats and the accuracy of text extraction, which required us to adjust our approach multiple times to ensure reliable data inputs.

Accomplishments that we're proud of

We are particularly proud of our ability to learn and apply prompt engineering to effectively use the Gemini API. Despite the challenges, we were able to implement a functional system that extracts useful insights from students' assignments, which is a major milestone for us. Additionally, we were able to integrate all components of the tech stack into a cohesive platform.

What we learned

We learned how to effectively prompt the Gemini API and integrate it into our application to generate insights. Through this project, we gained valuable experience in using AI-driven solutions for practical, real-world applications in education. Additionally, we enhanced our full-stack development skills and deepened our understanding of managing complex integrations between backend and frontend systems.

What's next for AI Course Insights

Moving forward, we plan to improve the Gemini API's text recognition accuracy to ensure that all documents are interpreted correctly. We will also focus on refining our prompt engineering to extract more precise and actionable insights. A key feature we are adding is the ability for users to upload notes, enabling the Gemini API to suggest personalized study plans based on the content. This will help users further improve their academic performance by providing structured guidance on what to study next.

Share this project:

Updates