MasterEDU

Inspiration

We did research on AI and how it was affecting education and thought there was an opportunity for students to benefit from instruction created from both their instructors and AI. A place where classical and modern educational strategies can intersect.

What it does

MasterEDU will be an all encompassing platform that will allow for teachers to post problems sets made by themselves, and curate supplemental practice problems, based on the results of the aforementioned problems sets, to help ensure the student is achieving mastery in that subject. This will ensure we have the necessary direct interaction between students and educators, but also that students that need extra help will be able to receive it.

How we built it

The first thing we did was research. As students ourselves, we were interested in how AI could affect the educational process in the future. We read many articles and found a place where we could make a difference and started making MasterEDU into a prototype. We started out with deciding on a stack, creating a site map, and making mockups on figmas. Then, we hit the ground running with a frontend and backend teams diving into the material.

Challenges we ran into

There were a couple of hiccups on the backend in properly meshing all of our technologies together. We are having some trouble properly connecting our backend with our MongoDB. These problems will be overcome with enough time to tinker.

Accomplishments that we're proud of

The progress we made in one weekend not only in prototyping but understanding the complex and changing landscape of how AI is and should be used in education.

What we learned

We learned about the modern education landscape and how much AI is shaking it up for better and for worse. We discovered how dynamic and adaptable lesson plans have to be in this ever changing world and how much the shrinking pool of teachers need tools and are safe, reliable, and actually have an impact on a students learning.

What's next for MasterEDU

Our next steps are to get sample data for the database so that we can start generating new problem sets and ensure that the questions are what we intended in scope and difficulty. Then, starting a user test with a small group of students and perhaps a teacher or two.