COMP5047 Pervasive Computing: 2012 GOMS and keystroke predictive methods Judy Kay CHAI: Computer...

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COMP5047 Pervasive Computing: 2012 GOMS and keystroke predictive methods Judy Kay CHAI: Computer human adapted interaction research group School of Information Technologies

Transcript of COMP5047 Pervasive Computing: 2012 GOMS and keystroke predictive methods Judy Kay CHAI: Computer...

Page 1: COMP5047 Pervasive Computing: 2012 GOMS and keystroke predictive methods Judy Kay CHAI: Computer human adapted interaction research group School of Information.

COMP5047 Pervasive Computing: 2012COMP5047 Pervasive Computing: 2012

GOMS and keystroke predictive methods

Judy Kay

CHAI: Computer human adapted interaction research group

School of Information Technologies

Page 2: COMP5047 Pervasive Computing: 2012 GOMS and keystroke predictive methods Judy Kay CHAI: Computer human adapted interaction research group School of Information.

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Overview

• Predictive methods

• GOMS and keystroke analyses

• Benefits

• Disadvantages

• Adapting GOMS to Pervasive Computing

(>1 million Google matches)

Page 3: COMP5047 Pervasive Computing: 2012 GOMS and keystroke predictive methods Judy Kay CHAI: Computer human adapted interaction research group School of Information.

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Postconditions for this week (incl private study)

• 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

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GOMS

• Goal• Operations - keystrokes, clicks• Methods - sets of operations• Selection rules - decide between methods

• For expert users

Page 5: COMP5047 Pervasive Computing: 2012 GOMS and keystroke predictive methods Judy Kay CHAI: Computer human adapted interaction research group School of Information.

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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?

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• K - keypress• P - point with mouse• C - click with mouse• H - home hands on new device• M - mentally prepare• R(t) - system response time

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• 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?

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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”

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Method 1 – highlighting “the cat” • Assumptions: hands were on keyboard and R = 0.• H - 0.40 - Reach for mouse • M – 1.35 – mentally prepare• P - 1.10 - Point to the left of "the"• C - 0.20 – Click mouse• M – 1.35 – mentally prepare• P - 1.10 - Point to right of "cat"• C - 0.20 - Release mouse• Total = 5.7

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Method 1 cont – bolden keyboard shortcut

• M – 1.35 – mentally prepare• K - 0.60 - Press and hold "Control"• K - 0.60 - Press "B"• K - 0.60 - Release "Control"

• Total = 3.15

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Method 2 - use menu

Assumptions: hands were on keyboard and R = 0 M – 1.35 – mentally prepare• P - 1.10 - Point to "Format" menu• C - 0.60 - Click and hold• M – 1.35 – mentally prepare• P - 1.20 - Point to "Bold" menu item• C - 0.60 - Release mouse

• Total = 6.2

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Conclusion for this case

• Assumtions: Hand position, R, K, P• Common part is 5.7 (sweeping out “the cat”)• Rest of

– Keyboard shortcut takes 3.15 seconds

– Mouse menu method takes 6.2 seconds

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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

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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?