Students look forward to completing projects with peers but that dream is gets crushed by the various work ethics and work styles of people on the team. Conflicts not only take away productive time but also prevents through collaboration.
This can be prevented by ensuring optimized groupings. Zing is a mobile and web platform that helps professors group students in a way that enhances collaboration and productivity by ensuring that background, gender, ethnicity as well as custom criteria are matched.
Creating inclusive groups is a complex process that professors often overlook due its tedious nature,. Instead, they rely on self assignment which can lead to disfunction, lack of contribution, and underperformance.
To ensure the balanced groups professors have to collect detailed data and sort through it while matching various criteria. Critical details can be missed and of course in classes with 100+ students human error is inevitable. In those cases, due to inherent gender, race, or intellectual biases many students get discouraged from maximizing their learning opportunity. So the question is
"How might we ensure all students in a group are able to collaborate at their highest potential regardless of their background?"
It is important to note that within our product this problem applies to a niche group of people. So the first step in solving the problem is to understand how these users interact with the current product and what their pain points are. The big questions I will be asking are:
1. What are the common characteristics in the users?
2. What is the user flow in the existing product?
3. What are the pain points in the current user flow?
The administrator's main responsibilities are to schedule rides and dispatch drivers, so they want to quickly notice problems with rides, find its the root cause, and come up with a solution.
As the lead designer, I undertook the entire end to end design process from ideation to MVP handoff to develop the student survey and group organization platform.
I conducted user research to discover the problem, synthesized findings to define priorities, and iterated on designs through user testing to develop solutions and deliver the one stop shop for all grouping needs.
It is important to note that within our product this problem applies to a niche group of people. So the first step in solving the problem is to understand how these users interact with the current product and what their pain points are. The big questions I will be asking are:
1. What are the common characteristics in the users?
2. What is the user flow in the existing product?
3. What are the pain points in the current user flow?
The administrator's main responsibilities are to schedule rides and dispatch drivers, so they want to quickly notice problems with rides, find its the root cause, and come up with a solution.
Behaviors
Frustrations
Goals
From insights I started exploring various interactions. Resolving the most time consuming pain point - browsing existing data, meant implementing an analytics feature that organizes the complex data set and makes it easy to pin point a specific group of data. After user testing, the interval picker and summary dashboard especially appealed to the administrator because it helped filter the unnecessary data and visualize the necessary data.
The analytics feature only solved part of the problem because there was no precise ride feedback system that allowed for solving today's problems in a timely manner. So, I implemented a live status feature that would provide up to date information on today's rides and highlight any anomalies.
To ensure that the platform is accessible and to reduce complexity I wanted to use soft primary colors with enough contrast to be easily visible. I also implemented distinct icons for easy status recognition.
The administrator Mindy wants to find and solve any problems with rides. Let's visualize her journey.
Before Mindy starts to recognize any problems, she needs to go to today's schedule.
Schedule Navigation
Mindy then needs to delve a little deeper into the problem rides to see the exact issue.
Live Status
Mindy wants to understand the root cause of the problems, so she uses the analytics feature. The data is filtered yearly and monthly or by using an interval picker. The aggregate is then shown in the dashboard.
Analytics Feature
Mindy remembers to check for changes to existing schedules to see whether that is the real cause instead.
Notifications
Besides working on navigation, analytics, live status, and notifications, I was also partially responsible for the admin access interaction.
