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ITM 734 Introduction to Human Factors in Information Systems

ITM 734 Introduction to Human Factors in Information Systems. Cindy Corritore cindycc@gmail.com. Simple Human Performance Models: Predictive Evaluation with Hick’s Law, Fitt’s Law, Power Law of Practice, Keystroke-Level Model.

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ITM 734 Introduction to Human Factors in Information Systems

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  1. ITM 734Introduction to Human Factors in Information Systems Cindy Corritore cindycc@gmail.com Simple Human Performance Models: Predictive Evaluation with Hick’s Law, Fitt’s Law, Power Law of Practice, Keystroke-Level Model This material has been developed by Georgia Tech HCI faculty, and continues to evolve. 1

  2. 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!

  3. Two Types of User Modeling • 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 • Stimulus-Response • Practice law • Hick’s law • Fitt’s law

  4. 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 and GOMS • Focuses on very low level actions • Assumes no high level thinking during action

  5. 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” for an action TM – how measure? (fast recall) • System Response time TR – ignore (fast)

  6. 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

  7. Step One Example : 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)

  8. Using KSLM - Step Two • Place M (mental prep) operators - In front of all K’s that are NOT part of argument strings (ie, not part of text or numbers) - In front of all P’s that select commands (not arguments)

  9. Step Two Example : 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

  10. Using KSLM - Step 3 Remove M’s according to heuristic rules (Rules relate to chunking of actions) Rule 1. If action is anticipated by prior operation – it is a chunk action • change PMK to PK (point and then click is a chunk) Rule 2. If a string of MKs is a single cognitive unit (such as a command name), delete all MKs except the first • MKMKMK -> MKKK (same as M3K) (again, it is a chunk) Rule 3. If it is a redundant terminator, such as )) at end of something, then remove M Rule 4. If the K terminates a constant string, such as command word (such as return after typing in command), then delete M

  11. Step 3 Example: MS 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 1 delete M H anticipates P Rule 1 delete M H anticipates P Rule 4 Keep M

  12. 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

  13. Step 4 Example : 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 http://www.syntagm.co.uk/design/klmcalc.shtml - website with KSLM calculator

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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)

  20. 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.

  21. 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)

  22. 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

  23. Cognitive models - many flavors More complex than KSLM Hierarchical GOMS - Goals, Operators, Methods, Selectors CCT - Cognitive Complexity Theory Linguistic TAG - Task Action Grammar CLG - Command Language Grammar Cognitive architectures SOAR, ACT

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