- Challenge: How can we help Georgia Tech students to efficiently locate spaces for a variety of purposes, according to their personal preferences?
- My Role: UX researcher
- Duration: August 2016 – December 2016
- Expert Interviews
- Field study
- Contextual Inquiry
- Affinity Map
- Persona Development
- Design Sprint
- Low Fidelity Mockups
- User Testing Plan
- Pen & Paper
You have some homework to complete today and you decide to pop into the biggest, central building on campus: Clough Undergraduate Learning Commons (CULC). You spy an empty seat at a table with a group of 3 students excitedly discussing something. You leave to find a quieter place but the spot you found has no plug point. Filled with regret, you go back to the previous table but someone else has taken the seat! After spending 15 minutes combing through CULC’s shared spaces supposedly filled with 2100 seats, group study rooms and glass atriums, you settle for a spot ON THE FLOOR near a plug point. Great.
02 USER RESEARCH
Exploring the problem & identifying user needs
OUR RESEARCH QUESTIONS
In order to scope down the project, we brainstormed several research questions that would guide our approach without preemptively cutting off potential problems in the topic area.
- How do users search and decide on a space? (what are their goals, what criteria do they consider, how do those criteria influence the process)
- What difficulties do users face in the search process?
- What is the sociotechnical context of finding and using a space?
Step 1: Expert Interviews
We spoke to experts from facilities management, and human resources about the search process. This got us up to speed on how spaces relate to one another, student behavior within those spaces, physical constraints, and some handy resources available (e.g. online room reservation).
Step 2: Observational Field Study
5 unobtrusive observations were conducted across CULC. We observed 2 key search styles: roaming through the building VS grabbing the first available spot. There were some interesting interactions within the shared spaces but too many possible explanations despite immersing ourselves in the task context.
Step 3: Contextual Inquiry
To clarify assumptions from the field study and investigate student attitudes directly, we interviewed 13 students in CULC as they were completing a task – searching for a suitable space. We asked semi-structured questions such as “what were your goals coming to CULC?” & “what difficulties did you face?”
Step 4: Survey
With more knowledge about the types of purposes, search processes, behaviors & attitudes, I made a survey to investigate personal preferences based on type of activity involved, level of familiarity with person, and personality traits. A total of 23 responses were received.
Copious amounts of qualitative data from the field studies and interviews were affinity mapped using a deductive approach. Broader categories and trends started to surface and we started to identify factors that influenced users’ search process.
Using descriptive analytics, the quantitative survey data also shed light on users’ personal preferences and how that could change during AND after the search, depending on activity. I grouped together similar findings from this analysis and the affinity map, and extracted contrasting ones to create the key insights below.
Search for Space - More Than Just Time
- ” I tell strangers yes they can have the seat but I actually don’t want them sticking around glancing at my screen”
A significant number of users expressed a desire for privacy while trying to be unselfish. They understand that it’s difficult to find an empty spot so they’ll share the space but they lose control of the space.
- “I find a quiet spot to work but I chat with the person next to me when I’m bored and need inspiration”
Users’ goals and preferences can change after they have found a spot and settled into it. This can also affect other users sharing that space, for better or for worse.
04 PERSONA DEVELOPMENT
Using our research data, we identified key attributes of our users such as extrovert/introvert, decisiveness, convenience etc. These attributes were grouped into clusters to begin forming clear characters. 2 distinct characters emerged and we added details to make the personas more believable.
This process helped us to foster empathy for the specific users we were designing for, while breaking away from the attempt to design for everyone. The 2 personas eventually served as the north star for future design decisions.
05 DESIGN PHASE
Our process from ideation to proof of concept
Moving on to ideation, we went through a couple rounds of converging and diverging. Ideas that did not target the personas or fulfill user needs were discarded. The remaining ideas were prioritized using a feasibility-impact grid.
Based on the prioritization grid, we prototyped the top 3 ideas using pen and paper. The 3 design ideas include: a ubiquitous cube that indicates availability and preferences using color, a kiosk interface that addressed the overall problem, and an AR map app that would guide the user real-time.
Design Critique & Decisions
We presented our prototypes to our classmates- also HCI enthusiasts and UXers – and obtained feedback from them. They voted on our ideas using green (like), blue (unsure) and red (dislike) stickers.
Based on the overwhelming amount of green “like” stickers for our cube idea, we decided to bring it forward to a higher fidelity. The designers on the team took on the role of programming the raspberry pi and laser cutting materials while I served as the user needs advocate in the rest of the design phase.
Users select a color (green, yellow or red) to reflect their desired level of interaction and availability of seats in that particular space. The device lights up according to the color button pressed.
- Red: no empty spots in the space.
- Yellow: space is partially filled. A limited number of strangers are welcomed as long as they do not disturb the user. This is suitable for use cases where the user is doing individual work and needs to focus but is still open to sharing the space.
- Green: seats available; open to interaction.
Users are also given the ability to post a message that would define the characteristics of the space they have color coded. They can thus communicate personal preferences to other users searching for a space. Socialight thus creates a safer environment for introverts without reducing socializing opportunities for extroverts.
Our prototype essentially reflects personal preferences while capturing space availability. At one glance, users can locate suitable spaces and and identify criteria that drive their search process. We hope that our prototype not only facilitates a more effective way of finding spaces based on a variety of needs and goals, but also reduces the misfits that arise from sharing spaces.
As part of the iterative design process, our next step was to test our prototype on users.
Our agreed goals were to:
- investigate how differing levels of extraversion could influence use of the prototype
- evaluate users’ attitudes towards the process of interaction between the user, the SociaLight, and other users
- identify problems and reiterations needed (e.g. did the meaning of the colors match users’ expectations?)
Based on these goals, I created a usability study. The full script that I wrote can be found here.
Qualitative research is incredibly rewarding
Don’t get me wrong, quantitative methods are fun too. They answer how much and how many questions very effectively but it is done indirectly. Qualitative research lets me observe users directly, question my assumptions, and think deeper about what they say VS what they do. It was incredibly fun understanding unique searching behaviors then bringing it to the team to impact design.
There is a missing link between data and actionable insight
An essential part of any UX process is analyzing the research data so that you can use it. However, actionable insight is more than just key trends found in the data. Data is raw, unprocessed stuff. Even after aggregating and processing, it just becomes information. Insights can only be generated by analyzing the information and drawing conclusions. Going through the data rigorously helped me realize that actionable insights are a leveled-up version of insights – they’re insights that can be acted upon and makes you rethink something. It’s novel, relevant, specific and contextual.
Define the right tasks
It’s one thing to talk about making representative tasks but another thing to write them. User tasks should be realistic, actionable and non-leading to be effective. Tasks scenarios are also important – it sets the stage for action and context for why the user needs to “do X”.
It was frustrating rewriting tasks but it gets better and better after each redraft. One useful approach I eventually found was to turn user goals into task scenarios was to phrase a task using “who”, “when”, “where” and “what”, and asking the users “how” .
I’m not a graphic designer
This project helped me realized that while I like designing, my talents do not lie there. I struggled with visualizing tiny details and planning shots for a video. User research came much more easily and naturally to me. Critical and analytical thinking (that would lead one to think out of the box) was like second nature, perhaps due to my psychology background. Since that’s what I’m good at and also passionate about, I might as well pursue that direction and learn enough design skills to be able to execute research insights.