Designed and developed a data-driven college recommendations model for high school students.
College applicants, especially from first generation families, often don't have a lot of exposure to US colleges. A lot of students have heard of the top places but are not aware of the full spectrum of colleges they could apply to. This results in them applying to only high reach or ill fitting places.
where2apply combines data from a number of verified sources (IPEDS, CollegeBoard, Cappex) to create a data-driven college recommendations engine. Students can enter their profile details (SAT scores, GPA) and college preferences (Class Size, Location, Area Type) to match a balanced list of colleges.
The recommendations model runs at the backend and generates a list of colleges for the user based on their input parameters and preferences. However, these parameters needed to be collected from the user in an intuitive and seamless way. If the form felt too cumbersome, it would detract a lot of users from actually using the tool.
This was my main emphasis while designing the app: focus on a clean experience for the user where each input entry was as quick as possible. To do so, I closely inspected every question in the form and asked a focus group of high school students to choose the most obvious way they would answer it from a given set of options.
Cool Matte Black
#333333
Jade Blue
#6484F5
Code Green
#4FEB97
I wanted the color scheme to emphasize the clean focus of the app. Therefore, I chose a cool matte black as the website's primary color. To complement the plain nature of the primary color, I chose jade blue and code green as my secondary colors. These colors would be used scarcely in the app (mostly for buttons and other CTAs) but their vibrant nature would work well against the standard black backdrop.
Avenir
I wanted the font to be consistent with the minimalist nature of the app. That's why I chose Avenir, a popular Sans-Serif font with straight edges.
The app is now live and has been used by over 1000 students already. If you want to try out the app for yourself, click here.
For a user-centered tool like this recommendations engine, the key objective is to make people use the app with as few complaints as possible. Oftentimes, one can get too involved with creating flair and forget that the most imperative thing is to create simplicity for the user. This importance of targeting the user-base is what I learned from my research for this project as well as the designs I created for the various input types.