1. Task Analysis (continued)

2. Task analysis Observations can be done at different levels of detail fine level (primitives, e.g. therbligs, keystrokes,GOMS - the “micro” level) intermediate level (flow charts, plans, or steps for sequences of actions) high level (cognitive goals; social impact - the “macro” level)

3. General principles of human information processing Fitt's Law Reaction time (the Model Human Processor) Power Law of Practice Principle of uncertainty GOMS - an approach to task analysis

4. The Model Human Processor Perceptual system (sensors) Cognitive system (processors) Motor system (effectors) (Card, Moran, & Newell, 1983)

5. Important parameters Memory capacity Decay Representation Processing cycle time

6. Sample times Eye-movement = 230 [70~700] ms Typical time = 230 ms “Fastman” = 70 ms “Slowman” = 700 ms Perceptual processor:100 [50~200] Cognitive processor:70 [25~170] Motor processor:70 [30~100]

7. Model of simple RT problem: Task: Press button when symbol appears.

8. Model of simple RT problem: Task: Press button when symbol appears. 1. Perceptual processor captures it in the visual image store & represents it in working memory. 100 [50~200]

9. Model of simple RT problem: Task: Press button when symbol appears. 2. Cognitive processor recognizes the presence of a symbol. 70 [25~170]

10. Model of simple RT problem: Task: Press button when symbol appears. 3. Motor processor pushes the button 70 [30~100]

11. Model of simple RT problem: Task: Press button when symbol appears. 1. The perceptual processor captures it in the visual image store and represents it in working memory. 100 [50~200] 2. The cognitive processor recognizes the presence of a symbol. 70 [25~170] 3. The motor processor pushes the button 70 [30~100] Total time?

12. Each of these action primitives takes some small amount of time (in msec.). The Model Human Processor provides a range of parameters you can use to predict precisely how long something will take, or to compare the time needed for alternative actions

13. More complex RT example Task: you see one symbol, then another. Push yes if they match, no if they don’t. Same first step as in simple RT problem: 1. The perceptual processor captures symbol #1 in the visual image store and represents it in working memory 100 [50~200]

14. Complex RT example, cont. 2. Ditto for symbol #2 100 [50~200] 3. If symbol #1 is still in the visual store, the cognitive processor can compare the two symbols 70 [25~170] 4. If they match, the cognitive processor decides to hit “yes” 70 [25~170] 5. The motor processor hits “yes” 70 [30~100] How long from step #2 until the end?

15. Something to think about: If you’re driving down the highway at 60 mph, how quickly can you react to an emergency? Mean RT in simplest situation is 240 msec. You travel 5280 * 60 = 316,800 ft./hr. 1 hour = 60 * 60 = 3600 sec. You travel 88 ft./sec. or > 21 ft. in 240 msec. before you can even react (let alone stop)!

16. What about Fastman & Slowman? If you’re driving down the highway at 60 mph, how quickly can you react to an emergency? Mean RT in simplest situation is 240 sec. You travel 5280 * 60 = 316,800 ft./hr. 1 hour = 60 * 60 = 3600 sec. You travel 88 ft./sec. or > 21 ft. in 240 sec. [between ~11 and ~41 ft.] before you can even react (let alone stop)!

17. General principles of human information processing Reaction time Power Law of Practice Fitt's Law GOMS - an approach to task analysis Principle of uncertainty

18. Power Law of Practice When something is done again and again, performance follows a power law (You keep improving with practice, but as you become an expert, you improve less and less.)

19. Power Law of Practice

21. Note: The power law of practice describes quantitative changes in skilled behavior (both cognitive and motor), but not qualitative changes (changes in strategies).

22. GOMS (Card, Moran, & Newell) Goal - what the user wants to achieve Operator - elementary perceptual, motor, or cognitive act Method - a series of operators that forms a procedure for doing something Selection rule - how the user decides between methods (if...then...). Skill is particularly important here.

23. GOMS (continued) Examples: Goal - editing a paper (high level) cutting and pasting text (low level) Operator - typing a keystroke Method - set of operators for cutting Selection rule - how the user chooses a method

24. Advantages of GOMS very general purpose allows for individual differences much predictive power about timing good at predicting "ideal" performance

25. Disdvantages of GOMS not so good at predicting errors takes a long time to conduct analysis whole may not be the sum of the parts ignores the nature of internal symbolic representations - focus is very low-level

26. Skill acquisition and transfer Transfer (positive transfer) Interference (negative transfer)

27. Hick’s principle of uncertainty Predicts how long a response will take in a given situation, based on how likely (or uncertain) the different possibilities are

28. Hick’s principle of uncertainty A secretary has a telephone console with 10 buttons for answering calls on 10 lines. When a light behind a button comes on, his job is to push the button and answer the phone. Which of these situations is going to be faster to react to? A: where each line gets an equal number of calls B: where two lines are used heavily, getting 50% and 40% of the calls, with the other 10% divided evenly among the other eight lines.

29. Hick’s principle of uncertainty T = I * log2(n+1) T = time I = a constant n = number of possible responses, assuming all are equally probable +1 is due to uncertainty whether to respond

30. Hick’s principle of uncertainty A: where each line gets equal number of calls 3.46 units B: where two lines are used heavily, getting 50% and 40% of the calls, with the other 10% divided evenly among the other eight lines. 2.14 units So the RT for B is 62% of the RT for A. (2.14/3.46)

31. Miscellaneous points to review Experiment design Breadth-first vs. depth first in menus and in spoken dialog design Writing VoiceXML info

32. Improve your writing Everyone can write better (and you are no exception!)  Advice from Clark Advice from Clark  Addendum: Brennan Addendum: Brennan Writing for the Internet (Nielsen)  How users read on the Web How users read on the Web