{ 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 Science University of California - Irvine Emeritus Professor University of Michigan Professor of psychology Institute of Psychology, Chinese Academy of Science – Beijing CHI Academy, ACM SIGCHI, 2003 CHI 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 Olson Professional 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 and Engineering 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 log 2 ( 2D / W ) MT = Movement Time MT = Movement Time W = Target Width W = Target Width D = Distance to Target D = Distance to Target a & b = empirically determined constants Fitts’ Law Video 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 Chair University 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 items Object Pointing  Providing more than one cursor Ninja cursors Reducing distance to the target

 Area Cursors Point cursor Area Cursor 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 ABC

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