
Microsoft Uni
Education, Wearables, User Research

PROJECT TYPE
Academic project with Microsoft User Experience Team
RESPONSIBILITY
Interaction Design, Visual Design, Prototyping
DELIVERABLES
Research Deck
Design Deck
Motion Study
TOOLS & METHODS
Sketch 3,Principle, Interviews, Competitive Analysis, Focus Groups, Elito Chart
TEAM & DURATION
Daisy Yi Wang, Matt,
2 Weeks
THE CHALLENGE
How can an intelligent digital assistant support the needs of students in 2020?
Siri, GoogleNow, Facebook M, Alexa, Cortana, Luka and myriad other speech or text activated assistants have all started the conversation about what intelligence is and does in system design. As Microsoft has always been caring about the realm of education, how can we utilize this new piece of technology to help students support their needs?

OUR SOLUTION
We proposed Microsoft Uni, utilizing data collected with an Intelligent Digital Assistant to facilitate education among students and instructors.
We approached the problem by researching on both Intelligent Digital Assistant and education, holding interviews and focus groups with users.

ASKING QUESTIONS
What is an Intelligent Digital Assitant?
What it is capable of doing? What are the areas it has been succeed in? We conducted a Competitive Analysis between Cortana, Siri, Google Now, Facebook M, Alexa and Luka. This allowed us to understand the pro’s and con’s of the various iterations of these assistants. It also provided us a basis for understanding their future potential.
We also conducted Expert Interview with the User Research Team at Microsoft, to get more details about an IDA.
KEY FINDINGS


UNDERSTAND THE CONTEXT
When and Where to Use?
To understand the contexts in which a digital assistant might function, we observed various locations on campus. We found that there is a functional breakdown of the different spaces:
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Collabrative
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Recreational
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Transitional
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Individual
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Instructional
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Dining
KEY FINDINGS
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Any built environment implies a set of functional and behavioral uses.
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In general, students abide by those implications and feel uncomfortable outside of them.
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An intelligent digital assistant (IDA) should be able to understand the relationship between environment and behavior.
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An IDA should interact within the behavioral norms established by a built environment.

UNDERSTAND THE USER
What do they value?
What are they struggling with?
To help us better understand user needs and design considerations we interviewed a PHD in education technology, and a law student, as well as conducted Focus Groups round the topics of Student Experience, Intelligent Assistance, and Learning Spaces. Our participants were three students from different disciplines, ages and expertise. We focused specifically on their values and struggles.
KEY FINDINGS
Students value:
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Engaging, collaborative, no one left out in class
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Whiteboards allow us to draw/ write freely.
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Use phone to take photos for notes on whiteboard is convenient.
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Think aloud can help me solve problems.
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Knowledgeable and well-prepared professors are highly valued.
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Equality among teachers and students.
They struggule with:
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Voice-based digital assistant can be awkward sometimes.
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Organizing and prioritizing things to do is a pain.
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Focusing on grades takes away the learning aspect.
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Campus digital services can get confusing when not putting together well.
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Too many unrelated and disruptive emails.
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Too many digital devices can be distracting in class.
![]() Ideation | ![]() Focus Groups | ![]() Affinity Diagram |
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CONCEPTS SKETCHES
Ideation And Research, at The Same Time
One thing we kept doing along with our research is that we sketched ideas, as many as we can. Knowing that we could never get "enough research" to do our design, brainstorming early ideas help us better frame the problem, narrow down our design scope. We grouped together similar ideas, and started to see patterns, which provoked us to think about:

Individual vs Togetherness
What does it mean to provide intelligent assistance to a single student? A class? A house? A room? A seminar? How should an intelligent assistant navigate and respond to the nuances of these relationships?

Devices
What devices come into play in a students' life and in what context(s) are they used? Shared? How does intelligent assistance respond (or not respond) to these contexts?

Interactions
What are the core interactions an intelligent digital assistant needs to support? Voice-based? Text-based? How does the using context affect the interactions?

Risks
What are the risks (ethical, personal, socio-cultural) associated with providing intelligent assistance?

DATA ANALYSIS
Making Sensen from Massive Data.
We have collected lots of research data, as well as sketched out many many ideas. We were struggling with how to utilize these information to direct our design? We tried using Elito Chart to synthesize data, which helped us figure out our design directions.

01 Elito Chart Process

02 Elito Chart Sample
