{ building blocks scientific foundations for interface design hci remixed “chapter 47: a most...
TRANSCRIPT
{Building Blocks
Scientific foundations for Interface Design
HCI Remixed “Chapter 47: A Most Fitting Law”Presented by Sarah Deighan
Gary Olson
Donald Bren Professor of Information& Computer ScienceUniversity of California - Irvine
Emeritus ProfessorUniversity of Michigan
Professor of psychologyInstitute of Psychology, Chinese Academy of Science – Beijing
CHI Academy, ACM SIGCHI, 2003CHI Lifetime Achievement Award, ACM SIGCHI, 2006
Human-Computer Interaction Collaboration
Technology Computer Supported
Cooperative Work Interface Design Intelligent Tools Organizational Issues
Cognitive Science Cognition in its
Social and Physical Settings
Problem-Solving and Reasoning
Communication
Gary OlsonProfessional Interests
Paul M. Fitts
Psychologist,The Ohio State University
Psychologist,University of Michigan
Lieutenant Colonel,US Air Force
President of the Division of Applied Experimental andEngineering Psychology,American Psychological Association
President,Human Factors and Ergonomics Society
Fitts’ Experiment
The rate of performance of all the tasks studied increased uniformly as movement amplitude was decreased and as tolerance limits were extended.Pg 387
Fitts’ Conclusion
MT = a + b log2 ( 2D / W )
MT = Movement Time W = Target Width D = Distance to Targeta & b = empirically determined constants
Fitts’ Law Video
Fitts’ Law
What types of interactions or interfaces are exempt from Fitts’ Law?
Discussion Questions
What do you believe is more useful to the HCI field, the equation or the principle represented?
Discussion Questions
How important or unimportant is it for new interfaces to be assessed with quantitative methods as opposed to only qualitative methods?
Discussion Questions
Do we as the HCI community focus too much on user feedback and qualitative evaluations?
Discussion Questions
Ravin Balakrishnan
Professor & Canada Research ChairUniversity of Toronto
CHI Academy, ACM SIGCHI 2011
Applying Fitts’ law principles to decrease MT by manipulating the variables Distance to the target Target Size Control-Device Gain
Applying Fitts’ Law
Making the target appear on command Pop-up menus Drop-down menus Circle Menus
Bringing items to the cursor temporarily
Drag and Pop
Reducing distance to the target
Taking the cursor to selectable itemsObject Pointing
Providing more than one cursorNinja cursorshttp://youtu.be/l0QM-RPlL8s
Reducing distance to the target
Area Cursors
Point cursor Area Cursor
http://youtu.be/JUBXkD_8ZeQ
Increasing width of the target
Expanding the target
Increasing width of the target
Basic version Single gain setting that the user
must use
Dynamically adjusting gain “Sticky” targets
Manipulating Gain
AB
C
What represents C-D gain in the equation for Fitts’ Law?
Discussion Questions
Do you think that participant results from basic manipulations of C-D gain is a manipulation or reflection of Fitts’ Law?
Discussion Questions
Do any of these interaction techniques discussed actually “beat” Fitts’ Law?
Discussion Questions
Do you believe that Balakrishnan’s analysis of any of these new techniques would have changed if he had been including more qualitative methods?
Discussion Questions
What interaction techniques discussed do you think would be found most and least acceptable?
Discussion Questions
Do you think that we should expend energy in developing more quantitative evaluation techniques?
Discussion Questions
Do you think that HCI as a discipline should be more concerned with “basic” work or should we focus on “applied” work?
Discussion Questions