1. { Building Blocks Scientific foundations for Interface Design HCI Remixed “Chapter 47: A Most Fitting Law” Presented by Sarah Deighan

2. 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

4. 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

5. 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

6. Fitts’ Experiment

7. 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

8. 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

9. What types of interactions or interfaces are exempt from Fitts’ Law? Discussion Questions

10. What do you believe is more useful to the HCI field, the equation or the principle represented? Discussion Questions

11. How important or unimportant is it for new interfaces to be assessed with quantitative methods as opposed to only qualitative methods? Discussion Questions

12. Do we as the HCI community focus too much on user feedback and qualitative evaluations? Discussion Questions

13. Ravin Balakrishnan Professor & Canada Research Chair University of Toronto CHI Academy, ACM SIGCHI 2011

14. Applying Fitts’ law principles to decrease MT by manipulating the variables  Distance to the target  Target Size  Control-Device Gain Applying Fitts’ Law

15.  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

16.  Taking the cursor to selectable items Object Pointing  Providing more than one cursor Ninja cursors http://youtu.be/l0QM-RPlL8s Reducing distance to the target

17.  Area Cursors Point cursor Area Cursor http://youtu.be/JUBXkD_8ZeQ Increasing width of the target

18.  Expanding the target Increasing width of the target

19.  Basic version  Single gain setting that the user must use  Dynamically adjusting gain  “Sticky” targets Manipulating Gain ABC

20. What represents C-D gain in the equation for Fitts’ Law? Discussion Questions

21. Do you think that participant results from basic manipulations of C-D gain is a manipulation or reflection of Fitts’ Law? Discussion Questions

22. Do any of these interaction techniques discussed actually “beat” Fitts’ Law? Discussion Questions

23. 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

24. What interaction techniques discussed do you think would be found most and least acceptable? Discussion Questions

25. Do you think that we should expend energy in developing more quantitative evaluation techniques? Discussion Questions

26. Do you think that HCI as a discipline should be more concerned with “basic” work or should we focus on “applied” work? Discussion Questions