Pitch, demo and usage
Same as embedded video above.
Link to video: https://youtu.be/9jpGdw4brwY
Link to video: https://youtu.be/dQq2AUojiQ0
Our app can be viewed here, and you can log in with:
Email: email@example.com Password: password
We experimented with a Node Express backend but ultimately decided to focus on using a mock database interface in the frontend to focus our efforts on user functionality.
As the world slowly emerges from what was COVID-19, many stresses in the education system have come to light.
- Teachers are overwhelmed by the workload demanded by COVID-19.
- Students are struggling to stay engaged in a virtual classroom.
- The education system makes children compete with one another.
To solve this we built Brain.Chain, a classroom management tool that gamifies collaboration to encourage peer-led learning from a young age.
What it does
We provide classrooms with a web-application where:
- Students are rewarded for actions that lead to the greater good of their class or community.
- Non-ranked gamification incentivises students to do better, but not for the purpose of "competition".
- User-friendly tools and data visualisation to assist teachers in teaching, decision-making, and classroom management.
The product is ideal for students to keep up-to-date on homework or for classrooms working remotely.
One particular focus of the tool is the formation of study groups that are well-balanced with both students that tend to struggle or excel with classwork. This enables us to leverage existing talent and room for growth such that students will lift eachother's communal knowledge, and help take some onus off teachers struggling to stay afloat.
How we built it
We utilised a containerised frontend development environment using Docker and Typescript React, and deployed the app through Netlify.
Challenges we ran into
One of the main challenges was figuring out a way to deal with user data. Originally we wanted to make use of the Google Classrooms Restful API as the main backend, but that was deemed too complicated and lacking of all the features we needed. We then tried implementing a simple Express API but we were running out of time and progress was slow. In the end we opted for data stored and manipulated on the front end. This gave us the ability to showcase the main features of the app without having to deal with persistent storage.
We had similar problems with login. Originally we wanted to use Google login but time constraints meant we had to go with a locally stored solution.
Accomplishments that we're proud of
We're proud of the idea, we think it's innovative and it really holds promise for a new way of communal learning.
We're proud of the fact that we were all able to come together and learn so much in a short amount of time.
We're happy with all the pages, but especially happy with the fact that we were able to implement most of the features in the 'Squads' page, including multiple tasks and functional question and answer features.
What we learned
We have learnt that the need for collaboration, along with the need for reliable technology, is crucially important and cannot be taken for granted. In order for progress to be made smoothly and consistently, it is important that everyone is not just effective at what they do, but also if they are able to collaborate with others so that everyone is on the same page.
What's next for Brain.Chain
There are many exciting new directions that the brain.chain app can take, after the initial development stage. Updating the machine learning model, in addition to the interface, allows for a smoother operation of the app.