Portfolio HF Researcher
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Transcript of Portfolio HF Researcher
![Page 1: Portfolio HF Researcher](https://reader030.fdocuments.us/reader030/viewer/2022021503/577cce051a28ab9e788d18a9/html5/thumbnails/1.jpg)
Welcome
Chiushun Dan(Dan)’s
Human Factors Research Portfolio
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Who am I
• I am a human factors/Usability researcher
• My research experiences are very diverse, ranging from human performance in cockpit to usability research of websites and consumer products
• I enjoy collaborating with visual/interactive designers, engineers, PMs
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My Research Philosophy-1
• I am as strong as my data
– Garbage in, garbage out
– Always plan studies carefully
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My Research Philosophy-2
• Triangulation of data collection
Qualitative & Quantitative
Self Report & BehaviorSubliminal & Conscious
Data
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My Research Philosophy-3
• Be part of the big picture
– Deliver evidence-based info to assist decision making
– Respect all teams’ concerns
– PERSIST but also COMPROMISE
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A brief history of mine
2007 2008 2009 2010 2011 2012 2013 Present
UndergraduateApplied Psyc
Ebay China, Online Trust Research
Master in Aviation Human Factors@ Florida
Tech
Master in HCI/PhD in Engineering Psyc@ Georgia Tech
Photo-grapher
Research Assistant @GT Human Factors and
Aging Lab
Coop@GE Appliances
Thesis: The effects of time of automation failures and expectation on trust in automation.
Thesis: Visual attention allocation in a multi-tasking environment
Achievements:Develop MultitaskingTest platform: STEP 1
Usability Review of remoteMower control room design
AchievementsEstablish readability test procedure2
Redesign GE service website3
Usability Test remote control Appliance App4
Define touch interface specs
Achievement:Modeling trust formation for Ebay users
Note: 1,2,3,4 are Clickable Shortcut in MS Powerpoint
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Research Example: Ebay China
• Background – EBay's business was
stagnant in China.
• Research questions:– What information do
online shoppers look for?
– How do they develop trust in sellers?
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Methods-Ebay
• Data Collection: Lab Experiment – Orthogonal Experimental Design
• Sampling– 60, Convenient sampling with screening criteria
• Measurements– Subjective report trust questionnaire (Likert-scale)
• Good reliability, Cronbach alpha>.80
– Structured Interview
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Thinking Process-Ebay
• Why Lab experiment (instead of other methods such as web-analytics, interview… )?1. Establish a quantitative model
2. Explore causal relationship
3. Test hypothesized designs
• Use orthogonal design– Large amount of treatment combinations(30+) of
independent variables
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Early Trust Development
Institution Based Trust(i.e., Buyer Protection)
HistoryRelation Based Trust (i.e.,Friendship)
Institution
Follow-up Trust Development
Purchase
Explanations:1. Sellers’ History(feedbacks) accounted for little variance initially.
2. Institution based trust(i.e., Paypal) is the key to the early development of trust.
3. Relation based (emotional trust) trust gradually develops, which is reinforced by seller-buyer interaction and transactions.
Online Trust Development Model-Ebay
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Wrap-up: Ebay China
• Recommendations:– For Chinese buyers, history of sellers yields little trust
• Stop creating complicated metrics of seller’s history
• No need to highlight reputation data
– Institution, buyer protection, is overwhelmingly important .• Paypal must be implemented quickly and successfully
– Should allow communications between sellers and buyers• Stop blocking communication between buyers and sellers
• Encourage buyers-sellers interaction to boost trust
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Research Example:Redesign of GE Service Website
• High drop-off rate when scheduling service online (shown right)
• Objectives: Improve online scheduling completion rate– Reduce call center workload
– Improve dispatch efficiency
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Thinking Process-GE service website
• Four methods were used to collect usability data:
SubjectiveData
ObjectiveData
Qualitative Data
Quantitative Data
3. Interview
2. Eye tracking
1. Web-analytics 4. Questionnaire
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Methods: GE Service Website
• 3 Steps Approach:
Step-2: Eye-tracking/interviewLook into pages that identify In step-1 with internal participants
Step-1: Web-analyticsIdentify specific pain-pointin current design
Step-3: Usability testEvaluate original and redesigned Webpage with external participants
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Results 1-GE Service Website
Improvements:1. Reduce visual clutter by deleting meaningless image and inappropriate information
2. Linear scan pattern• Rationales: Eye-tracking data shown a scattered scanpath
3. Provide phone no. across the whole scheduling process
Original Redesigned
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Results 2-GE Service Website
Original
Improvements:1. Show availability in a Calendar instead of Radio buttons and Drop-down Menu
• Rationale: Web analytics data suggest a high drop-out rate when selecting date and time
2. Provide fee information upfront• Rationale: Fee is shown as soon as the product info is entered
Redesigned
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Results 3-GE Service Website
Original
Improvements:1. Users do not need to provide any information regarding the problem
• Rationale: Relieve users from technical terms and actions.
Redesigned
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Wrap-up: GE Service Website
• A wide variety of data collection methods was used to solve usability problems.
• System usability score(SUS) improved by 25 points.
• Completion rate significantly improved.
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Research Example: Establish Readability Test Procedures
• Background
• Cost• Tooling• Time• …
• Modern• Sleek• Aha• …
• Profit• Usability• Safety
Engineers want:Current 7- Segments Display
Designers want:Dot Matrix Display
Product Manager want:(Decision Maker)
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Background-2: Readability
• Users want:
– Displays should be visible across a room at a glance
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Thinking process- Goal of Usability Research
• We want (usability team):
– Facilitate data-driven decision making
• Not to simply offer a result of Winner/Loser
• A test method that benefits similar studies in future
– Take considerations for all scenarios/Users
• Close-up view Vs. Distal view
• Numbers, Letters(Both UPPER and lowercase)
• Users with different visual acuity
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Research Design
• Materials:
– Inspired by the visual acuity test, I create a series of revised “eye charts”
– Instead of testing eyes, they test readability
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Why resemble visual acuity test
• Standard test procedure– Quick– Inexpensive
• Comprehensible Results– 20/20 Vs. Image size on retina
• Quantitative in nature– High granularity – Comparable between tests
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Research Design
• Within subjects design, 9 conditions
– Fully randomized eye chart, no learning/carryover
– Maximize test stats power
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Research Design
• Measurements/Metrics
– Maximum legiblility rating (e.g., 20/20,20/40)
– Comfortable legibility rating
• “At which line you are still able to read effortlessly and comfortably at a glance?”
– Subjective preference(ranking order)
• Dots Vs. 7 Segments Vs. Solid(LCD)
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Results
• The Dot matrix requires XX%1 larger size to achieve equivalent readability of 7 segs.
Or
• 7 segs can provide X2 feet more visible range for people with 20/20 vision
Note: 1,2 Non-disclosure data
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Wrap-up: Establish Readability Test Procedures
• A detailed, quantitative, and easy to understand result for all teams.
• A new testing methods for evaluating display and typography
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Research example- Usability review of GE Brillion App
• Brief: GE Brillion app allows users to control appliances with smart phone
• What I did?• Define info architecture
• Heuristic evaluation
• 1-on-1 verbal protocol test
• Manage external consulting service
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Research Example-Persona: A couple of Millennium Generation
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Research Example: STEP for John Deere
• STEP: Simultaneous Task Environment Platform (Youtube Demo)
– A test platform contains basic cognitive tasks that are essential for machine operators.
• What I did?
– Identify related tasks
– Prototype
– Debug
– Manage development
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• Due to non disclosure agreement, some materials are selectively presented.
• Feel free to contact me @
– Mobile: 321-474-9633
to discuss projects in more details
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