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ITM 734Introduction to Human Factors in Information Systems

Cindy Corritorecindycc@gmail.com

This material has been developed by Georgia Tech HCI faculty, and continues to evolve.

Simple Human Performance Models: Predictive Evaluation with Hick’s Law, Fitt’s Law, Power Law of Practice, Keystroke-Level Model

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Simple User Models

• Idea: If we can build a model of how a user works, then we can predict how s/he will interact with the interface Predictive model predictive

evaluation

• No mock-ups or prototypes!

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Two Types of User Modeling

• Stimulus-Response Practice law Hick’s law Fitt’s law

• Cognitive – human as interperter/predictor – based on Model Human Processor (MHP) Key-stroke Level Model

– Low-level, simple GOMS (and similar) Models

– Higher-level (Goals, Operations, Methods, Selections)– Not discussed here

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Power law of practice

• The logarithm of the reaction time for a particular task decreases linearly with the logarithm of the number of practice trials taken Time to perform a task based on

practice trials• Performance improves based on a

“power law of practice” That is, practice improves performance

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Power law of practice

• Tn = T1n-a

Tn time to perform a task after n trials T1 time to perform a task on first trial n number of trials (practice time) a is about .4, between .2 and .6 For learning skills - describes learning curve

– Typing speed improvement– Learning to use mouse– Pushing buttons in response to stimuli– NOT learning

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Uses for Power Law of Practice

• Use measured time T1 on trial 1 to predict whether time with practice will meet usability criteria, after a reasonable number of trials How many trials are reasonable?

• Predict how many practices will be needed for user to meet usability criteria Determine if usabiltiy criteria is realistic

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Hick’s law

• Decision time to choose among n equally likely alternatives – choice reaction time T = Ic log2(n+1) where

T is decision time

Ic ~ 150 msec (constant)

n is number of alternatives

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Uses for Hick’s Law

• Menu selection• Which will be faster as way to choose from

64 choices? Go figure: Single menu of 64 items Two-level menu of 8 choices at each level Two-level menu of 4 and then 16 choices Two-level menu of 16 and then 4 choices Three-level menu of 4 choices at each level Binary menu with 6 levels

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Fitts’ Law

• Models movement times for selection (reaching) tasks in one dimension

• Basic idea: Movement time for a selection task Increases as distance to target increases Decreases as size of target increases

• Function of distance and width (of target)

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Fitts model

MT = a +b log2(d/w +1)

• MT is average time taken to complete the movement

• a and b are constants and can be determined by fitting a straight line to measured data.

• d is the distance from the starting point to the center of the target.

• w is the width of the target measured along the axis of motion.

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Exact Equation

• Run empirical tests to determine k1 and k2

• Will get different ones for different input devices and device uses

MT

log2(d/w + 1.0)

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Uses for Fitt’s Law

• Menu item size• Icon size• Scroll bar target size and placement

Up / down scroll arrows together or at top and bottom of scroll bar

• Pie menus

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Keystroke-Level Model (KSLM)

• KSLM - developed by Card, Moran & Newell, see their book* and CACM* The Psychology of Human-Computer

Interaction, Card, Moran and Newell, Erlbaum, 1983

• Skilled users performing routine tasks• Assigns times to basic human operations -

experimentally verified• Based on MHP - Model Human Processor

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KSLM Accounts for

• Keystroking TK

• Mouse Button press TB

• Pointing (typically with mouse) TP

• Hand movement betweenkeyboard and mouse TH

• Drawing straight line segments TD

• “Mental preparation” TM – how measure?

• System Response time TR – ignore (fast)

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Using KSLM - Step One

• Decompose task into sequence of operations - K, B, P, H, D (no M operators yet; R can be used always or not at all) Typically system response time appears

instantaneous, so can be ignored

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Step One : MS Word Find Command

• Use Find Command to locate a six character word H (Home on mouse) P (Edit) B (click on mouse button - press/release) P (Find) B (click on mouse button) H (Home on keyboard) 6K (Type six characters into Find dialogue box) K (Return key on dialogue box starts the find)

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Using KSLM - Step Two

• Place M (mental prep) operatorsRule 0a. In front of all K’s that are NOT part of

argument strings (ie, not part of text or numbers)

Rule 0b. In front of all P’s that select commands (not arguments)

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Step Two : MSoft Word Find Command

H (Home on mouse)MP (Edit)B (click on mouse button)MP (Find)B (click on mouse button)H (Home on keyboard)6K (Type six characters)MK (Return key on dialogue

box starts the find)

Rule 0b: Pselects command

Rule 0b: Pselects command

Rule 0a: Kis argument

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Using KSLM - Step 3

Remove M’s according to heuristic rules (Rules relate to chunking of actions)Rule 1. Anticipated by prior operation

– PMK ->PK (point and then click is a chunk)Rule 2. If string of MKs is a single cognitive unit (such as a

command name), delete all but first– MKMKMK -> MKKK (same as M3K) (type “run rtn is a

chunk)Rule 3. Redundant terminator, such as )) or rtn rtnRule 4. If K terminates a constant string, such as command-

rtn, then delete M– M2K(ls)MK(rtn) -> M2K(ls)K(rtn) (typing “ls” command in

Unix followed by rtn is a chunk)

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Step 3 : MS Word Find Command

Rule 4 Keep M

Rule 1 delete MH anticipates P

Rule 1 delete MH anticipates P

H (Home on mouse)MP (Edit)B (click on mouse button)MP (Find)B (click on mouse button)H (Home on keyboard)6K (Type six characters)MK (Return key on dialogue

box starts the find)

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Using KSLM - Step 4

• Plug in real numbers from experiments K: .08 sec for best typists, .28 average,

1.2 if unfamiliar with keyboard B: down or up - 0.1 secs; click - 0.2 secs P: 1.1 secs H: 0.4 secs M: 1.35 secs R: depends on system; often negligible

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Step 4 : MS Word Find Command

H (Home on mouse)P (Edit)B (click on mouse button - press/release)P (Find)B (click on mouse button)H (Home on keyboard)6K (Type six characters into Find dialogue box)MK (Return key on dialogue box starts the find)• Timings

H = 0.40, P = 1.10, B = 0.20, M = 1.35, K = 0.28 2H, 2P, 2B, 1M, 6K

• Predicted time = 6.43 secs

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Example: MSoft Windows Menu Selection

• Get hands on mouse• Select from menu bar with click of

mouse button• The “pull down” menu appears• Select desired item from the pull

down menu

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Step 1: MS Windows Menu

H (Home on mouse)P (point to menu bar item)B (left-click with mouse button)P (point to menu item)B (left-click with mouse button)

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Step 2: MS Windows Menu - Add M’s

H (get hand on mouse)MP (point to menu bar item)B (left-click with mouse

button)MP (point to menu item)B (left-click with mouse

button)

Rule 0b: Pselects command

Rule 0b: Pselects command

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Step 3: MS Windows Menu - Delete M’s

• H (get hand on mouse)• MP (point to menu bar item)• B (left-click with mouse

button)• MP (point to menu item)• B (left-click with mouse

button)

Keep M

Rule 1 Manticipated by P

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Step 4: MS Windows Menu Calculate Time

• H (get hand on mouse)• P (point to menu bar item)• B (left-click with mouse button)• MP (point to menu item)• B (left-click with mouse button)• Textbook timings (all in seconds)

H = 0.40, P = 1.10, B = 0.20, M = 1.35 H, 2P, 2B, 1 M

• Total predicted time = 4.35 sec

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Macintosh-style Menu Selection

• Operator sequence H(mouse)P(to menu item)B(down)PB(up)

• Now place Ms H(mouse)MP(to menu item)B(down)MPB(up)

• Selectively remove Ms H(mouse)MP(to menu item)B(down)MPB(up)

• Textbook timings (all in seconds)– H = 0.40, P = 1.10, B = 0.10 for up or down, M = 1.35– H, 2P, 2 B, 1 M

• Total predicted time = 4.15 sec • Macintosh is predicted to be .2 secs faster than MS Windows,

about 5%

Rule 0b

Rule 0b

Rule 1 Delete: H anticipates P

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KSLM Comparison Problem

• Are keyboard accelerators always faster than menu selection?

• Use MS Windows to compare Menu selection of File/Print (previous example

estimated 4.35 secs.) Keyboard accelerator

– ALT-F to open the File pull down menu– P key to select the Print menu item

• Assume hands start on keyboard

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KSLM Comparison:Keyboard Accelerator for Print

• Use Keyboard for ALT-F P (hands already there) K(ALT)K(F)K(P)

MK(ALT)MK(F)MK(P)

MK(ALT)K(F)MK(P)– 2M + 3K = 2.7 + 3K

• Times for K based on typing speed Good typist, K = 0.12 s, total time = 3.06 s Poor typist, K = 0.28 s, total time = 3.54 s Non-typist, K = 1.20 s, total time = 6.30 s Time with mouse was 4.35 sec

• Conclusion: Accelerator keys not necessarily faster than mouse!

First Kanticipatessecond K

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KSLM Example - select a word and replace with new typed text

Home on mouse H(mouse)Point to word P(word)Select word BB(mouse

button)Home on keyboard HType new word KKKKK

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KSLM Example

• No M’s to add K’s are part of argument, so rule 0a does not apply No P’s to use with rule 0b

• Sequence remains asHome on mouse H(mouse)Point to word P(word)Select word BB(mouse button)Home on keyboard HType new 5-letter word 5K

• T = 5TK +2TB +TP +2TH +TM= 5(.28)+2(.2)+1.1+2(.4)+1.35= 5.05 secs

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Using KSLM

• Skilled users• Performing routine tasks

The user has done it many times before No real learning going on Some modest “thinking” as captured by Ms

• Rules for placing Ms are heuristics• Best use is for comparing alternatives

Sometimes predictions are off But rankings of faster - slower tend to be

accurate

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Cognitive models - many flavors

More complex than KSLMHierarchical

GOMS - Goals, Operators, Methods, SelectorsCCT - Cognitive Complexity Theory

LinguisticTAG - Task Action GrammarCLG - Command Language Grammar

Cognitive architecturesSOAR, ACT