Create a platform where Machine Learning, Data Science, and Artificial Intelligence Students can seamlessly connect with companies to source portfolio and capstone projects.
This was a 3-week capstone project as part of my 3 month UX Design Bootcamp at General Assembly. I worked on a team with two other UX Design students to help our client, BizdevIQ build a platform where Machine Learning, Data Science, and Artificial Intelligence students can seamlessly connect with companies to source portfolio and capstone projects. The tools we used were figma, miro, and adobe illustrator.
In our research we discovered that Machine Learning, Data Science, and Artificial Intelligence students have a difficult time finding real, good data sets for projects. They also desired more opportunities for "real world" feedback on their work outside of class.
Because of our 3-week timeline for the project, we focused on the needs of students as our primary persona, and did not delve as deeply as we would have liked into the needs, behaviors, and pain points of companies hiring the students.
My team held 7 user interviews, focusing on Masters Level Data Science, Machine Learning, and Artificial Intelligence students.
From the user interviews, we grouped the data points from our user interviews using affinity mapping into 12 areas of insight.
We chose four key insights to drive our design process because these insights came up the most in our user interviews.
From there we were able to develop a user persona to embody BizdevIQ's primary user's needs, behaviors, goals, and pain points. My team also created a user journey map to better illustrate and understand where the opportunities lay for BizdevIQ to help Sofia.
My team held a series of 7 design studios where we sketched out low fidelity wireframes for the main pages that we would include in the prototype to address Sofia's problem in this design sprint.
The main pages we focused on were those that we identified in our Feature Prioritization, and they included: a Sign-in Page, the Project Search Page, the Project Brief Page, the Mentor Search Page, and the Mentor Profile Page.
For one of our design studios, we had the opportunity to involve the CEO of BizdevIQ. Knowing that we had limited time with him, we selected the most complex and industry specific page to ideate with him.
We held the design studio with him over zoom, and walked out if it with a much better idea of what Sofia would expect to see when she looked at a project brief page on Bizdev's site.
Based off of the insights gathered in our User Interviews, combined with what we learned through sketching with our client, we built out a mid-fidelity prototype and tested it with potential users.
The focus of this round of usability testing was to check for the functionality of our design before taking it up to a higher fidelity. We tested with 5 users, based on the Norman Nielsen Group’s recommendation of only needing 5 users to test on.
We gave our users the following scenario and tasks:
You are pursuing a Masters Degree in DS/ML or AI. For your entire program you have been assigned to a team for all group projects. You and your team have to accomplish a project of your choice, and it is up to you to choose the data that you will work with for the project.
You and your team have joined BizDevIQ, a platform which allows ML, DS and AI graduate students to connect with companies, who have data projects for students to work on for their school projects.
Log in to your BizDevIQ account. Find a project for your team and ask to join that project.
Your program is focused on Predictive Analytics, find a mentor who specialize in your area of interest and ask to meet them.
5 out of 5 of our users successfully completed both tasks that we gave them. That said, 2 out of 5 users ignored or did not see the filter function on our results page, so we made sure to try and make the filtering function more visible in the hi-fidelity mock up.
After a successful round of usability testing our mid-fi prototype, my team built out a hi-fidelity version of the prototype and did a second round of usability testing, where we honed in on the content.
For this round of user testing, we did it all remotely via zoom and screen sharing. We aimed to test with users who were not available when we were holding user interviews. The information we gained doing our hi-fidelity user testing with these target users was invaluable, and left us with clear next steps and recommendations to offer to our client for how to proceed with further refining the website for students.
Based on our usability testing, my team discovered 3 major content specific issues that we reported to our client, they were:
Two weeks into our social distancing, and at the end of our 3 week sprint, my team presented to our client the results of our work. Although we would have preferred to present in person, my team deftly presented our slide deck to our client, and afterwards we had an hour-long conversation where our client asked us our recommendations and further insights into what we discovered. All in all, our team delivered a high quality product on time and despite the seeming issues that could have come up due to switching to remote work because of COVID-19.
Based on our presentation and research, our client took our feedback and implemented it 6 months after our final presentation. The resulting design incorporated many of the recommendations we offered, and took the design a step further to take into account the needs of the other target users, mainly companies, who might use the product.
Below is a video of the new website.
For the full case study, please view it here.