collaboRATE

Want to find a study mate? Let collaboRATE come to the rescue!

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Inspiration

The Covid-19 pandemic has taken a toll on students’ motivation and mental health. Reduced social interaction has taken away a key component essential for brain health. Never has the learning experience been constrained to an individual level, where students are constrained to their study spaces, alone. Before the pandemic started, one in five college students experienced one or more diagnosable mental disorders worldwide. The fact that the COVID-19 pandemic affects collegiate mental health underscores the urgent need to understand these challenges and concerns to inform the development of courses of action and public health messaging that can better support college students in this crisis.

Our team recognizes the importance of connecting students to facilitate collaboration in learning. collaboRate is a website where college students can easily match with study buddies across the globe while tracking their progress through their user profiles. We envision the global connections made through this app taking us one step closer to mitigating the social deprivation mental health induced disorders.

What it does

collabRATE is an user-friendly website that allows students to create their own profiles, track their study progress, and most importantly, connect with like-minded individuals. The website is designed to be data driven whereby we collect users preferences on study methods including subjects of interest, language, learning styles, meeting frequency, time zones, age in a secure manner(ensuring users’ data privacy according to a predefined agreement), and we utilize machine learning algorithms such as k-means clustering algorithm to group users that could be possible matches. The website has five main pages: the welcome page, the sign up page, the leaderboard, the ‘find your match’ page and the Matches page, each of which would be described below:

  1. Welcome Page: This is the main landing page of our website that displays our brand name and logo, provides a brief description of how to use the website and gives the options to register or to sign in. This page also includes a description of the team members.
  2. Register Now: This page is a typical sign up page that collects basic information needed to differentiate users. It asks for the User’s name, email, age, and password.
  3. The Leaderboard: This page shows teams score. It is a method to keep teams accountable. The teams will be scored based on achievement of predefined goals they set on the website. The scores will be evaluated weekly with an option to track monthly goals.
  4. “Find your Match”: This page collects information necessary to connect people like timezones, geographical locations, age, learning styles, meeting frequencies, subjects of interest.
  5. The Matches page: This page resembles Tinder and other matchmaking app pages. It gives a list of potential matches and shows the match percentage ( measure of similarity). The user can swipe to select matches.

How we built it

We used the problem first approach to design our solution whereby we invested a lot of time in defining the problem before diving into the solution. We started by making a long list of problems we were interested in solving. Then we discussed each problem and came up with a consensus based on feasibility, impact and joint passion in the project. We used collaborative softwares to draw our first draft of our website using arrows to show links and boxes to show pages as shown below:

Finally, we used HTML, CSS, JavaScript, MySQL and PHP for the website (collabRATE) development.

Challenges we ran into

Adjusting each other’s time zone was our biggest challenge. It was also hard to collaborate virtually with WiFi issues.

Accomplishments that we're proud of

Despite other team mate’s different time zones we could manage to successfully develop our website. Throughout working on this project we shared each other’s expertise and learnt team management, time management. Made new friends. Despite having different academic backgrounds in computer science, electrical engineering, biomedical engineering and data science, we managed to utilize each other’s expertise and successfully launched our application.

What we learned

HTML, JavaScript, and CSS Visual Studio Code Working together and delegating.

What's next for collaboRATE

Designing a team logo Our website recommends student study buddies based on location. In the future as new users register on our website we are going to build a recommender system using machine learning algorithms in python that would suggest study buddies to a student based on their age, major, hobbies, location, university etc.

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