Transcript
SLIDETYPE
Xiao “Nikita”XiongMS Human Computer Interaction
April 25, 2013
A Universal Design Text-input Systems for Touch Screen Devices
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PROBLEM STATEMENTUbiquitous computing has surrounded us with lots of touchscreen devices, however....
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PROBLEM STATEMENTCurrent touch screen text-input does not accommodate people with vision, cognition, and dexterity impairments
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PREVIOUS RESEARCH
Figure 1: Nolook
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PERSONA AND USE CASE
Tom
-24 years old blind male. He is not very experienced with computer. He used a help dog. He went to a voting machine try to write in a candidate name but found out that the poll worker couldn’t set up the write machine for him
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DESIGN GOAL
One Text-input System for All Universal Design Approach
Equitable Use
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DESIGN APPROACHAccommodates range of preferences and abilities that interact with text-input (Flexibility in Use)
- Cognition- Simple and Intuitive Use- Tolerance for Error- Vision- Perceptible Information- Dexterity- Low Physical Effort- Size and Space for Approach and Use
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ITERATIVE DESIGN PROCESSSKETCHES
V2
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ITERATIVE DESIGN PROCESSWIREFRAMES
V1 V2 V3V2
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VISUAL MOCKUPS
SpinnerType
SlideType
V2
ITERATIVE DESIGN PROCESS
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V2
ITERATIVE DESIGN PROCESSLOW-FIDELITY PROTOTYPE
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V2
ITERATIVE DESIGN PROCESSHI-FIDELITY PROTOTYPE
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SOLUTION: SLIDETYPEMultimodal Inputs and Outputs
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SOLUTION: SLIDETYPE
Live Demo
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DESIGN FEATURES: SLIDER
- Utilize edge and corner for better navigation
- Use alphabetical order to lower cognitive load
- Provide instant audio for feed-forward
- Provide flexibility in use by sliding or tapping
- Single row to help faster visual search (Norman&Fisher,1982)
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DESIGN FEATURES: ARROWS AND ZOOMED BOX
- Use large font for better visibility
- Use bi-directional arrows for go forward/backward one letter
- Flexibility in use. It also reduce strokes when use with dual input devices such as sip-n-puff devices
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USER STUDYPARTICIPANTS14 Adults (8 female 6 male):
• 8 vision disabilities(3 totally blind, 5 low vision) • 3 mild cognitive disabilities. • 3 dexterity disabilities
• 24-64 years old
• 4 Master’s degree or higher• 3 Bachelor’s degree or higher, • 4 had Some college or Associate’s degree• 1 G.E.D.• 2 High school
• Self report touchscreen experience range 1-10 with a mean of 5.3
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USER STUDYMETHODS
Pre-test interview:• Background• Computer and touchscreen experiences
Test (think out loud):• 1. Type in “John Smith”• 2. Delete and input a new name
Post-test interview• Rate preferences and provide qualitative feedback
Duration: 20-30min
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USER STUDYTWO PROTOTYPES
SlideType V1:6 participants
User needs to hit enter to input;Space is inside the alphabet
SlideType V2:8 participants
User tap or slide on the slide barto input;Space is at the bottom right corner.
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USER STUDY 1RESULTS
Audio feedback and large letter size Bi-directional arrows: precise control, predictable manner (a low vision user)
Double action process is repetitive (2 participants with dexterity impairments)
1/6 fail to input text initially thinking they could directly tap2/6 fail to input space cause they can’t see the space button
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USER STUDY 2RESULTS
- 8/8 participants completed the task of typing and editing- Participants rate average 3.875 / 5 (4 easy, 5 very easy)- 3 participants with mild cognitive impairment finish the task with no instruction
One totally blind user who is very experienced with touchscreen had lots of error inputs since he wants to touch anywhere on the screen to input text
“This is easier than using keyboard”- 37 years old male participant who is totally blind“ I like everything about it. The letter size is very nice. That's easy to see”- 24 years old male participant who have complete spin injury
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USER STUDYFINDINGS- Participants find the introduction too long
- Participants would like to have audio feedback for the current letter they are deleting
- From observation, participants actually have a higher errorrate using SlideType V2
- More choices of color & contrast needs to be provided since people with low vision percept information differently
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FUTURE WORKBased on participants’ feedback
• Modifications of instructions• Modifications of audio feedback for correcting typo• Modifications of slide gesture detection • Modifications of color&contrast options
Recruit and test more participants
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REFERENCES1. Kane, S.K., J.O. Wobbrock, and R.E. Ladner, Usable gestures for blind people: understanding preference
and performance, in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems2011, ACM: Vancouver, BC, Canada. p. 413-422.
2. Nicolau, H., et al., Proficient blind users and mobile text-entry, in Proceedings of the 28th Annual European Conference on Cognitive Ergonomics2010, ACM: Delft, Netherlands. p. 19-22.
3. Granata, C., et al. Voice and graphical -based interfaces for interaction with a robot dedicated to elderly and people with cognitive disorders. in RO-MAN, 2010 IEEE. 2010.
4. Guerreiro, T., et al., Mobile text-entry models for people with disabilities, in Proceedings of the 15th European conference on Cognitive ergonomics: the ergonomics of cool interaction2008, ACM: Funchal, Portugal. p. 1-4.
5. Lee, S., et al., EZ ballot with multimodal inputs and outputs, in Proceedings of the 14th international ACM SIGACCESS conference on Computers and accessibility2012, ACM: Boulder, Colorado, USA. p. 215-216.
6. Connell, B.R., Jones, M., Mace, R., Mueller, J., Mullick, A., Ostroff, E., Sanford, J., Steinfeld, E., Story, M. and Vanderheiden, G, The Principles of Universal Design, 1997.
7. Zhai, S. and B.A. Smith, Alphabetically biased virtual keyboards are easier to use: layout does matter, in CHI '01 Extended Abstracts on Human Factors in Computing Systems2001, ACM: Seattle, Washington. p. 321-322.
8. Donald A. Norman, D.F., Why Alphabetic Keyboards Are Not Easy to Use: Keyboard Layout Doesn't Much Matter. Human Factors: The Journal of the Human Factors and Ergonomics Society, 1982.
9. Jo, et al., Blind people and mobile touch-based text-entry: acknowledging the need for different flavors, in The proceedings of the 13th international ACM SIGACCESS conference on Computers and accessibility2011, ACM: Dundee, Scotland, UK. p. 179-186.
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ACKNOWLEDGMENTMany thanks to Professor Jon A. Sanford from Center for Assistive Technology and Environmental Access for advising me along the development of the project. Many thanks to the EZ Ballot team Tina Lee, Elaine Liu and Samrat Ambadekar.
Many thanks to Research Scientist Mr. Matthew E. Swarts for answering technical questions.
Many thanks to the participants in the study.
This project was supported by the Election Assistance Commission through a Grant to the Information Technology and Information Foundation.
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THANKS FOR YOUR ATTENTION!
Q&A?For more questions and play with demo, please contact me at:
xxiong6@gatech.edu
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