LeARn was conceived around a simple notion: what if we could use Google Cardboards to create a cheap, dynamic, and useful educational tool? Any student that ever attended a primary or secondary school will know how intensely boring a chemistry or anatomy lecture can be. As we dozed off in these very same classes in high school, our experience sowed the seeds for what would become LeARn. This app has the potential to disrupt the way students view lectures, literally.
What it does
LeARn allows users to interact with physics simulations, plot 3D graphs, view MRIs, and watch the molecular structure of a chemical compound float before their very eyes. The user can move and manipulate these projections via an online client, affecting factors like scale, rotation, and position. Most importantly, when, say, a teacher makes these changes, all other users viewing the same object will also see them take effect. This collaborative aspect is one of the key features of the application.
How we built it
LeARn is built using a panoply of technologies. Unity/C#/Vuforia is used for 3D rendering, physics, and stereoscopic projection, JS/Node.js/Express.js/Socket.io is what keeps our backend running smoothly, and HTML/CSS/Materialize comprises our frontend stack.
Challenges we ran into
LeARn was very difficult to build for a variety of reasons. Nobody on our team had worked in Unity before or even knew C#, so to call it a learning experience is an understatement. We used complex and highly detailed models, and optimising these such that they would render well on mobile presented a significant challenge in and of itself. We are truly pushing the boundaries of Google Cardboard technology, having to cut apart our Cardboards just to allow the app to function.
Accomplishments that we're proud of
Having gone into this hackathon with no experience in augmented reality or Unity, we are all immensely proud of how far we were able to take this app, and we're thrilled with the product thus far. The collaborative aspect of the app is particularly interesting, and certainly no small technical feat.
What we learned
As previously mentioned, we went into this hackathon with little to no experience in many of the technologies and languages we were working in. We know a great deal more now than we did, and although we are very much still learning, we feel we've come a long way.
What's next for LeARn
Although we're satisfied with the progress of LeARn thus far, there are a few more features/fixes we'd like to implement in the future. For one, we began to implement voice control via Houndify. Unfortunately, we didn't have time to bring that feature to fruition, but we would like to see this completed down the road. We'd also just like to devote more time to improving the user experience and visuals.