Presentation is loading. Please wait.

Presentation is loading. Please wait.

GOMS and keystroke predictive methods Judy Kay CHAI: Computer human adapted interaction research group School of Information Technologies.

Similar presentations


Presentation on theme: "GOMS and keystroke predictive methods Judy Kay CHAI: Computer human adapted interaction research group School of Information Technologies."— Presentation transcript:

1 GOMS and keystroke predictive methods Judy Kay CHAI: Computer human adapted interaction research group School of Information Technologies

2 HAI2008. Lifelong ambient companions: challenges and steps to overcome them Overview Predictive methods GOMS and keystroke analyses Benefits Disadvantages Adapting GOMS to Pervasive Computing (>1 million Google matches)‏

3 HAI2008. Lifelong ambient companions: challenges and steps to overcome them Postconditions for this week (incl studio)‏ Describe the uses of GOMS Describe the processes for conducting GOMS analyses Describe advantages and limitations Ability to perform a GOMS study on conventional interfaces and explore the approach for pervasive systems Justify the use of GOMS in the overall testing of a pervasive computing application

4 HAI2008. Lifelong ambient companions: challenges and steps to overcome them GOMS Goal Operations - keystrokes, clicks Methods - sets of operations Selection rules - decide between methods

5 HAI2008. Lifelong ambient companions: challenges and steps to overcome them GOMS example (Newman and Lamming)‏ Make "the cat" bold in "the cat sat on the mat" Goal - to make "the cat" bold Operations - keystrokes, clicks Methods - ctrl-b or mouse/menu Selection rules - which method?

6 HAI2008. Lifelong ambient companions: challenges and steps to overcome them K - keypress P - point with mouse C - click with mouse H - home hands on new device M - mentally prepare R(t) - system response time

7 HAI2008. Lifelong ambient companions: challenges and steps to overcome them K – keypress.08 - 1.20 P - point with mouse.8 - 1.5 (Fitt's Law)‏ C - click with mouse.2 H - home hands on new device.4 M - mentally prepare 1.35 R(t) - system response time ? How would you determine values for a pervasive system?

8 HAI2008. Lifelong ambient companions: challenges and steps to overcome them Method 1 - keyboard shortcut H - 0.40 - Reach for mouse P - 1.10 - Point to "the" C - 0.60 - Click and hold P - 1.10 - Point to "cat" C - 0.60 - Release mouse K - 0.60 - Press and hold "Control" K - 0.60 - Press "B" K - 0.60 - Release "Control"

9 HAI2008. Lifelong ambient companions: challenges and steps to overcome them Method 2 - use menu H - 0.40 - Reach for mouse P - 1.10 - Point to "the" C - 0.60 - Click and hold P - 1.10 - Point to "cat" C - 0.60 - Release mouse P - 1.10 - Point to "Format" menu C - 0.60 - Click and hold P - 1.10 - Point to "Bold" menu item C - 0.60 - Release mouse

10 HAI2008. Lifelong ambient companions: challenges and steps to overcome them Conclusion for this case Keyboard shortcut takes 5.6 seconds Mouse menu method takes 7.2 seconds

11 HAI2008. Lifelong ambient companions: challenges and steps to overcome them NOTES: M before K/C or P except PMK... PK if K “anticipated” –e.g. move mouse to target and click MKMKMK... MKKK for cognitive unit –e.g. type “cat”

12 HAI2008. Lifelong ambient companions: challenges and steps to overcome them Summary of approach Focus on speed Known sequence of operations Can predict performance for experienced users Walkthrough steps, calculate time for each step, sum Can sometimes predict choices of method

13 HAI2008. Lifelong ambient companions: challenges and steps to overcome them Summary of uses Relatively inexpensive Can be used to compare “methods” Challenging to apply for conventional interfaces.... pervasive? Expert users only Would you expect software that assist in this?


Download ppt "GOMS and keystroke predictive methods Judy Kay CHAI: Computer human adapted interaction research group School of Information Technologies."

Similar presentations


Ads by Google