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Stanford hci group / cs376 u Scott Klemmer · 02 November 2006 Inpu t Techniqu es.

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Presentation on theme: "Stanford hci group / cs376 u Scott Klemmer · 02 November 2006 Inpu t Techniqu es."— Presentation transcript:

1 stanford hci group / cs376 http://cs376.stanford.ed u Scott Klemmer · 02 November 2006 Inpu t Techniqu es

2 2 Final project papers & presentations  Final papers: 4 pages in the traditional CHI format or 6 pages in the work-in-progress format (same effective length, I suggest the latter as you can submit it to CHI WIP)  Final presentations: 4 minutes each, followed by posters/demos  There will be outside reviewers, also folks from industry will be coming

3 3 How to write a good paper  Have a clear hypothesis  Explain design ideas, system, and eval  Read your critiques of earlier work  Compare your results to 4-5 pieces of related work  is a great resource

4 4 Milestone 2 demo times 1:30 - Deepak Kumar and David Tu 1:40 - David Akers 1:50 - Luping May, Kevin Collins, Scott Doorley 2:00 - Malte F. Jung, Howard Kao, Ravi Teja Tiruvury, Parul Vora 2:10 - Becky Currano and Murad Akhter 2:20 - Christina Chan 2:30 - Tom Hurlbutt 2:40 - Dhyanesh Narayanan 2:50 - BREAK 3:00 - Dean Eckles, Tony Tulathimutte, Tanya Breshears 3:10 - Jonathan Effrat and May Tan 3:20 - Shailendra Rao and Abhay Sukumaran 3:30 - Adam Kahn and Doug Wightman 3:40 - Brandon Burr 3:50 - Angela Kessell and Chris Chan

5 5 Pointing Device Evaluation  Real task: interacting with GUI’s  pointing is fundamental D W  Experimental task: target acquisition  abstract, elementary, essential

6 6 Fitts’ Law (Paul Fitts, 1954) D W Index of Performance (IP ) = ID/MT (bits/s) Throughput Bandwidth Index of Difficulty (ID ) Task difficulty is analogous to information - execution interpreted as human rate of information processing

7 7 50 years of data Reference: MacKenzie, I. Fitts’ Law as a research and design tool in human computer interaction. Human Computer Interaction, 1992, Vol. 7, pp. 91-139

8 8 What does Fitts’ law really model? Veloci ty (c) (b) (a) Target Width Distance

9 9 Using these law’s to predict performance Which will be faster on average?  pie menu (bigger targets & less distance)? Today Sunday Monday Tuesday Wednesday Thursday Friday Saturday Pop-up Linear Menu Pop-up Pie Menu

10 10 Beyond pointing: Trajectory based tasks

11 11 Gaming Fitts Law  The Macintosh menu bar and taskbar and the Windows XP Taskbar have “infinite height” improving their Fitts Law performance  …as does the back button in the Firefox browser

12 12


14 14 Yves Guiard: Kinematic Chain  Asymmetry in bimanual activities  “Under standard conditions, the spontaneous writing speed of adults is reduced by some 20% when instructions prevent the non-preferred hand from manipulating the page”  Non-dominant hand (NDH) provides a frame of reference for the dominant hand (DH)  NDH operates at a course temporal and spatial scale; DH operates at a fine temporal and spatial scale

15 15 Next Time… Information Visualization Readings in Information Visualization: Using Vision to Think, Chapter 1, Stuart K. Card, Jock D. Mackinlay, Ben Shneiderman The Table Lens: Merging Graphical and Symbolic Representations in an Interactive Focus+Context Visualization for Tabular Information, Ramana Rao and Stuart K. Card

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