I started a nonprofit at UC Davis that aims to teach robotics virtually. A lot of students don't have access to robotics curriculum, especially in rural and other underserved communities. This platform we developed today will adapt curriculum based on a current student’s skill level, allowing to reinforce concepts that students’ may not completely understand. Specifically, we will build an adaptive learning algorithm to assess student’s progress and modify the pace and content of the materials presented. This work will build on the literature on Intelligent Tutoring Systems (ITS) [Corbett 1997]. We will use computer-generated algorithms to identify individual learner ‘needs’ and present content based on the recorded data. Our proposal is to adapt this type of technology to the STEM fields.

What it does

It is a learning platform that incorporates Bayesian Learning and Artificial Intelligence in order to predict a student's currents

How I built it

I build backend on python and frontend with react.js.

Challenges I ran into

I ran into time challenges in terms of not finishing the entire project.

Accomplishments that I'm proud of

Finishing a working server

What I learned

Bayesian Learning, Node.js, React.js, Teaching beginners and children about javascript

What's next for natcar-platform

Build this out with the additions from UC Davis, TI, Intel, and CITRIS

For our domain name, because our team member Daniel Kim is currently unemployed and have no job prospects, we decided on the name

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