Cognitive Models Lecture #10

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 2 Agenda Cognitive models –KLM –GOMS –Fitt’s Law –Applications of Cognitive Model in HCI

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 3 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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20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 5 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

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 6 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

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 7 Keystroke Level Model (KLM) KLM decomposes the execution phase into five different operators

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 8 Keystroke Level Model (KLM) 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: T execute = T K +T B +T P +T H +T D +T M +T R Note: KLM gives the best result

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 9 Keystroke Level Model (KLM) Time for various operators in KLM

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 10 Keystroke Level Model (KLM) Example 1: User working with a mouse based editor He notices a single character error 1.He points at the error (by moving the mouse pointer) 2.Delete the character 3.Retype a character 4.Return to previous typing point

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 11 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 character Move to the keyboard and press a key (say, Del) 3.Retype a character Press another key (type the right character) 4.Return to previous typing point Task is done. Move to the previous place of editing

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 12 Example 1: KLM

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 13 Example 1: KLM Total execution time is obtained by adding the components time for each of the activities Encoding the method T = HPBHMKKHMPB

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 14 Heuristics for the M operator Jef Raskin’s Rules

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 15 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 Ms MKPBMKMKMKMPBMKMK 3.Repeat through Rule 1 to Rule 4 for each M to see whether it should be deleted or not MKPBMKKKKMPBMKKMK

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 16 Application of KLM: UI Evaluation Example 2

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 17 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 T execution = 5 x.12+2 x.20+2 x x.40+4 x 1.35 = 9.80

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 18 UI Evaluation: Temperature Converter Other way of improving the interface? Ends up being slower: T execution = 16.8 seconds! Assume a button for compressing scale

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 19 UI Evaluation: Temperature Converter Another way of improving the UI of Temperature Converter? Solution T execution = MKKKKMK = 3.7 seconds

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 20 UI Evaluation: Temperature Converter Any other way of improving the UI of Temperature Converter? Tricks: Armed with knowledge of the minimum information the user has to specify Solution?

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 21 UI Evaluation: Temperature Converter Solution 2: Translates to both simultaneously T execution = MKKKK = 2.15 seconds

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20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 23 GOMS Model (revisited) Engineering model of user interaction G oals - user’s intentions (tasks) –e.g. delete a file, edit text, assist a customer O perators - actions to complete task –cognitive, perceptual & motor (MHP) –low-level (e.g., move the mouse to menu) M ethods - sequences of actions (operators) –based on error-free expert –may be multiple methods for accomplishing same goal »e.g., shortcut key or menu selection S elections - rules for choosing appropriate method –method predicted based on context

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 24 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)

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 25 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

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 26 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

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 27 Example: CMN-GOMS Model Text Editing Method

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20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 29 Cognitive-Perceptual-Motor GOMS Example 1: Read Screen::When eye movement is required

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 30 CPM-GOMS (contd..) Example 2: Read Screen::When eye movement is not required

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20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 32 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

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 33 Fitt’s Law Time (in msec) = a + b log 2 (D/S+1) where a, b = constants (empirically derived) D = distance S = size ID is Index of Difficulty = log 2 (D/S+1)

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 34 Illustration of Fitt’s Law Time (in msec) = a + b log 2 (D/S+1) Same ID → Same Difficulty

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 35 Illustration of Fitt’s Law Time (in msec) = a + b log 2 (D/S+1) Smaller ID → Easier

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 36 Illustration of Fitt’s Law Time (in msec) = a + b log 2 (D/S+1) Larger ID → Harder

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 37 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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20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 39 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)

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 40 Cognitive Model-based Evaluation Drawbacks –Assumes an expert user –Assumes an error-free usage –Overall, very idealized

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 41 Recommended Materials See the course web page (For the presentation slides of the current lecture and other materials) Book Human-Computer Interaction by Alan Dix et al. Pearson-Education, Chapter 12

20 March, 2008Human Computer Intercation Spring 2008, Lecture #10 42 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 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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