Introduction to HCIcse.iitkgp.ac.in/~dsamanta/courses/archive/hci/LectureSlides/11... · –Applications of Cognitive Model in HCI. 20 March, 2008 Human Computer Intercati on Spring

Cognitive Models

Lecture #10

20 March, 2008 Human Computer Intercation Spring 2008, Lecture #10

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Agenda

• Cognitive models

– KLM

– GOMS

– Fitt’s Law

– Applications of Cognitive Model in HCI


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Cognitive Models

• Keystroke Level Model (KLM)– It is a low-level description of what users would

have to do to perform a task

• GOMS Model– It is structured, multi-level description of what

users would have to do to perform a task

• Fitt’s Law– It is used to predict a user’s time to select a target


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Keystroke Level Model (KLM)• Proposed by Card, Moran and Newell in 1980

• The model provides a quantitative tools

– To predict time to accomplish a task with a given method on an interactive computer system

• The model is based on counting keystrokes and low-level operations, including user’s mental operations and the system responses

• This models appears as simple, accurate enough and flexible to be applied in practical design and evaluation situations


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Keystroke Level Model (KLM)

• Predicts expert task-completion time with the following inputs:

– A task or series of subtasks

– Method (is a sequence of system commands) used

– Command language of the system

– Motor-skill parameters of the user

– Response-time parameters of the system


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Operator Type Operator Remarks K Key stroking, actually striking keys, including shifts

and other modifier keys B Pressing a mouse button P Pointing, moving the mouse (or similar device) at a

target H Homing, switching the hand between mouse and

keyboard

Physical Motor operator

D Drawing lines using mouse Mental Operator

M

Mentally preparing for a physical action

System Response operator

R

Response from system

KLM decomposes the execution phase into five different operators


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• Assumptions

1. Acquisition – User builds a mental representation of tasks

2. Execution– Error free task execution

Execution time is the sum of the time for each of the operators:

Texecute = TK+TB+TP+TH+TD+TM+TR

Note: KLM gives the best result


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Keystroke Level Model (KLM)• Time for various operators in KLM

Operator Remarks Time (second) K Press key

Good typist (90 wpm) Poor typist (40wpm) Non-typist

0.12 0.28 1.20

B Mouse button press Down or up Click

0.10 0.20

P Point with mouse 1.10 H Home hands to and from keyboard 0.40 D Drawing lines using mouse ----

M Mentally preparing for a physical action

1.35

R

Response from system

----


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Example 1:

• User working with a mouse based editor

• He notices a single character error1. He points at the error (by moving the mouse pointer)

2. Delete the character

3. Retype a character

4. Return to previous typing point


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Example 1: KLM• The execution of the above task will involve

interleaved occurrences of various operators

1. He points at the error (by moving the mouse pointer)Move mouse to the location and place the pointer there

2. Delete the characterMove to the keyboard and press a key (say, Del)

3. Retype a characterPress another key (type the right character)

4. Return to previous typing point Task is done. Move to the previous place of editing


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Example 1: KLM1. Point at the error HPB Move hand to mouse H Moving the mouse after bad character P Pressing the button B [left]

2. Delete the character HMK Return to keyboard H [keyboard] Mentally preparing for the deletion M Actual striking key K

3. Retype a character K Type correction K

4. Return at the typing point HMPB Move hand to mouse H [mouse] Mentally preparing for the moving M Pointing the mouse P Pressing the button B [left]


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Example 1: KLM

• Total execution time is obtained by adding the components time for each of the activities

• Encoding the methodT = HPBHMKKHMPB

Step Activities Keystrokes Time (s) 1. Point at the error HPB 0.40+1.10+0.10 = 1.60 2. Delete the character HMK 0.40+1.35+1.20 = 2.95 3. Retype a character K = 1.20 4. Return at the typing point HMPB 0.40+1.35+1.10+0.10 = 2.95

Total execution time 8.70


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Heuristics for the M operator

• Jef Raskin’s Rules

Rule Statement

Rule 0. Insert Ms in front of all Ks that are not part of argument strings proper (e.g., text strings or numbers). Place Ms in front of all Ps that select commands (not arguments).

Rule 1. If an operator following an M is fully anticipated in the operator just previous to M, then delete the M (e.g. PMK PK).

Rule 2. If a string of MKs belong to a cognitive unit (e.g., the name of a command), then delete all Ms but the first.

Rule 3. If K is a redundant terminator (e.g., the terminator of a command immediately following the terminator of its argument), then delete the M in front of the K.

Rule 4. If a K terminates a constant string (e.g., a command name), then delete the M in front of the K; but if the K terminates a variable string (e.g., an argument string), then keep the M.


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Heuristics for the M operator

• Application of Raskin’s Rules

1. Begin with a method encoding that includes all physical operations and response operations

KPBKKKPBKK

2. Use Rule 0 to place candidate MsMKPBMKMKMKMPBMKMK

3. Repeat through Rule 1 to Rule 4 for each M to see whether it should be deleted or not

MKPBMKKKKMPBMKKMK


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Application of KLM: UI Evaluation

• Example 2

Temperature Converter

Choose which conversion is desired, then type the temperature and press Enter.

Convert F to C Convert C to F


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UI Evaluation: Temperature Converter

• Prediction of Execution Time according to KLM

T = HPBHPBHKKKKK

After Raskin’s Rules

T = MHPBMHPBHMKKKKMK

T = 5K+2B+2P+3H+4M

Texecution = 5x.12+2x.20+2x1.10+3x.40+4x1.35

= 9.80


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• Other way of improving the interface?

Temperature Converter

Choose which conversion is desired, then type the temperature and press Enter.

Convert F to C Convert C to F

• Ends up being slower: Texecution = 16.8 seconds!

Assume a button for compressing scale


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• Another way of improving the UI of Temperature Converter?

• Solution

Texecution = MKKKKMK

= 3.7 seconds

To convert temperatures, Type in the numeric temperature,Followed by C for Celcius or

F for Fahrenheit. The converted Temperature will be displayed.


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• Any other way of improving the UI of Temperature Converter?

• Tricks: Armed with knowledge of the minimum information the user

has to specify

• Solution?


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• Solution 2: Translates to both simultaneously

C

F

Texecution = MKKKK

= 2.15 seconds


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GOMS Model (revisited)

• Engineering model of user interaction• Goals - user’s intentions (tasks)

– e.g. delete a file, edit text, assist a customer

• Operators - actions to complete task– cognitive, perceptual & motor (MHP)– low-level (e.g., move the mouse to menu)

• Methods - sequences of actions (operators)– based on error-free expert– may be multiple methods for accomplishing same goal

» e.g., shortcut key or menu selection

• Selections - rules for choosing appropriate method– method predicted based on context


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GOMS Family

• CMN-GOMS– Card, Moran and Newell GOMS, 1983

• NGOMSL– Natural GOMS Language, (Kieras et al. 1988)

• CPM-GOMS– Cognitive Perceptual Motor GOMS (Gray at al.

1993)


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CMN-GOMS Model

• Proposed by Card, Moran & Newell in 1983– Apply psychology to CS

• Employ model human processor (MHP) to predict performance of tasks in UI

– Task completion time, short-term memory requirements

– Applicable to • User interface design and evaluation

• Training and documentation

– Example of• Automating usability assessment


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CMN-GOMS Model

• Card, Moran & Newell (1983)

– most influential model of user interaction • used in GOMS analysis

– 3 interacting subsystems• cognitive, perceptual & motor

• each with processor & memory – described by parameters

» e.g., capacity, cycle time

• serial & parallel processing


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Example: CMN-GOMS Model

• Text Editing Method


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Cognitive-Perceptual-Motor GOMS

• Example 1: Read Screen::When eye movement is required


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CPM-GOMS (contd..)

• Example 2: Read Screen::When eye movement is not required


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Fitt’s Law

• Models movement time for selection tasks

• The movement time for a well-rehearsed selection task• Increases as the distance to the target increases• Decreases as the size of the target increases


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Fitt’s Law

Time (in msec) = a + b log2(D/S+1)

where

a, b = constants (empirically derived)

D = distance

S = size

ID is Index of Difficulty = log2(D/S+1)


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Illustration of Fitt’s Law


Same ID → Same Difficulty

T a r g e t 1T a r g e t 2


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Smaller ID → Easier



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Larger ID → Harder



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Determining the Constants in Fitt’s Law

• To determine a and b design a set of tasks with varying values for D and S (conditions)

• For each task condition – Multiple trials conducted and the time to execute each is recorded and

stored electronically for statistical analysis

• Accuracy is also recorded– Either through the x-y coordinates of selection or

– Through the error rate — the percentage of trials selected with the cursor outside the target


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Cognitive Model-based Evaluation

• Some existing applications

– Mouse-driven text editor (KLM/CMN-GOMS)

– CAD system (KLM/CPM-GOMS)

– Television control system (NGOMSL)

– Minimalist documentation (NGOMSL)

– Telephone assistance operator workstation (CMP-GOMS)


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Cognitive Model-based Evaluation

• Drawbacks

– Assumes an expert user

– Assumes an error-free usage

– Overall, very idealized


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Recommended Materials

• See the course web pagehttp://www.iitkgp.ac.in/course/it60110/(For the presentation slides of the current lecture and

other materials)

• BookHuman-Computer Interaction by Alan Dix et al.

Pearson-Education, Chapter 12


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Recommended Materials

• References:1. The Keystroke-Level for User Performance Time with

Interactive Systems by Stuart K. Card, Thomas P. Moran and Allen Newell, Communication of the ACM, Vol. 23, No. 7, July 1980

2. The GOMS Family of User Interface Analysis Techniques: Comparison and Contrast, Bonnie E. John and David E. Kieras, ACM Transaction on Computer-Human Interaction, Vol. 3, No. 4, December 1996


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Documents

Introduction to HCIcse.iitkgp.ac.in/~dsamanta/courses/archive/hci/LectureSlides/11... · –Applications of Cognitive Model in HCI. 20 March, 2008 Human Computer Intercati on Spring