learner.ai | Devpost

Inspiration

Our goal was to create an app that would enhance students' learning experiences and would enable professors to adjust the teaching content based on the students' knowledge.

What it does

Learner.ai is a mobile app designed for both students and instructors, where instructors can create questionnaires to identify areas in which students may be struggling. These surveys enable students to evaluate their skills needed for the course and they are accessible via a unique code. Using AI, the app then summarizes the responses and assist the professors in creating a customized study plan to support their students and help them succeed.

How we built it

Learner.ai was programmed using Python Flask as a backend, and React Native for frontend. Learner.ai's backend uses MongoDB to store the survey data and students' responses. With React Native, we developed a user-friendly mobile app enabling the effortless creation of surveys and the collection of students' information.

Challenges we ran into

Throughout the stages of development we faced many challenges. Not all of us knew how to use React Native, making the implementation of ChatGPT very difficult. Additionally, since none of us have ever worked with ChatGPT api, we had to learn everything from Open API docs, slowing down the whole process. Lastly, implementing the backend posed another significant challenge since we have never worked with a NoSQL database.

Accomplishments that we're proud of

We are incredibly proud of several accomplishments in this project. Firstly, we successfully developed a functional mobile application that empowers classroom learning experiences. We are also proud of being able to effectively collaborate as a team and assign each other tasks that fit our skill sets.

What we learned

Throughout the development of Learner.ai we gained valuable insights into various aspects of app development. We deepened our understanding of React Native, which allowed us to create an intuitive user interface. Moreover, we learned how to utilize various components of a complex application, including backend NoSQL databases and ChatGPT api.

What's next for learner.ai

In the future we would like to further expand learner.ai's features by implementing authentication measures to secure users' data. We also plan to implement new features that would allow the AI to categorize the survey results based on the students' majors.