1. IAT 334 Experimental Evaluation ______________________________________________________________________________________ SCHOOL OF INTERACTIVE ARTS + TECHNOLOGY [SIAT] | WWW.SIAT.SFU.CA

2. March 10, 2011IAT 3342 Evaluation  Evaluation styles  Subjective data –Questionnaires, Interviews  Objective data –Observing Users Techniques, Recording  Usability Specifications –Why, How

3. March 10, 2011IAT 3343 Our goal?

4. March 10, 2011IAT 3344 Evaluation  Earlier: –Interpretive and Predictive Heuristic evaluation, walkthroughs, ethnography…  Now: –User involved Usage observations, experiments, interviews...

5. March 10, 2011IAT 3345 Evaluation Forms  Summative –After a system has been finished. Make judgments about final item.  Formative –As project is forming. All through the lifecycle. Early, continuous.

6. March 10, 2011IAT 3346 Evaluation Data Gathering  Design the experiment to collect the data to test the hypothesis to evaluate the interface to refine the design  Information we gather about an interface can be subjective or objective  Information also can be qualitative or quantitative –Which are tougher to measure?

7. March 10, 2011IAT 3347 Subjective Data  Satisfaction is an important factor in performance over time  Learning what people prefer is valuable data to gather

8. March 10, 2011IAT 3348 Methods  Ways of gathering subjective data –Questionnaires –Interviews –Booths (eg, trade show) –Call-in product hot-line –Field support workers

9. March 10, 2011IAT 3349 Questionnaires  Preparation is expensive, but administration is cheap  Oral vs. written –Oral advs: Can ask follow-up questions –Oral disadvs: Costly, time-consuming  Forms can provide better quantitative data

10. March 10, 2011IAT 33410 Questionnaires  Issues –Only as good as questions you ask –Establish purpose of questionnaire –Don’t ask things that you will not use –Who is your audience? –How do you deliver and collect questionnaire?

11. March 10, 2011IAT 33411 Questionnaire Topic  Can gather demographic data and data about the interface being studied  Demographic data: –Age, gender –Task expertise –Motivation –Frequency of use –Education/literacy

12. March 10, 2011IAT 33412 Interface Data  Can gather data about –screen –graphic design –terminology –capabilities –learning –overall impression –...

13. March 10, 2011IAT 33413 Question Format  Closed format –Answer restricted to a set of choices Characters on screen hard to read easy to read 1 2 3 4 5 6 7

14. March 10, 2011IAT 33414 Closed Format  Likert Scale –Typical scale uses 5, 7 or 9 choices –Above that is hard to discern –Doing an odd number gives the neutral choice in the middle

15. March 10, 2011IAT 33415 Closed Format  Advantages –Clarify alternatives –Easily quantifiable –Eliminates useless answers  Disadvantages –Must cover whole range –All should be equally likely –Don’t get interesting, “different” reactions

16. March 10, 2011IAT 33416 Issues  Question specificity –“Do you have a computer?”  Language –Beware terminology, jargon  Clarity  Leading questions –Can be phrased either positive or negative

17. March 10, 2011IAT 33417 Issues  Prestige bias –People answer a certain way because they want you to think that way about them  Embarrassing questions  Hypothetical questions  “Halo effect” –When estimate of one feature affects estimate of another (eg, intelligence/looks)

18. March 10, 2011IAT 33418 Deployment  Steps –Discuss questions among team –Administer verbally/written to a few people (pilot). Verbally query about thoughts on questions –Administer final test

19. March 10, 2011IAT 33419 Open-ended Questions  Asks for unprompted opinions  Good for general, subjective information, but difficult to analyze rigorously  May help with design ideas –“Can you suggest improvements to this interface?”

20. March 10, 2011IAT 33420 Ethics  People can be sensitive about this process and issues  Make sure they know you are testing software, not them  Attribution theory –Studies why people believe that they succeeded or failed--themselves or outside factors (gender, age differences)  Can quit anytime

21. March 10, 2011IAT 33421 Objective Data  Users interact with interface –You observe, monitor, calculate, examine, measure, …  Objective, scientific data gathering  Comparison to interpretive/predictive evaluation

22. March 10, 2011IAT 33422 Observing Users  Not as easy as you think  One of the best ways to gather feedback about your interface  Watch, listen and learn as a person interacts with your system

23. March 10, 2011IAT 33423 Observation  Direct –In same room –Can be intrusive –Users aware of your presence –Only see it one time –May use semitransparent mirror to reduce intrusiveness  Indirect –Video recording –Reduces intrusiveness, but doesn’t eliminate it –Cameras focused on screen, face & keyboard –Gives archival record, but can spend a lot of time reviewing it

24. March 10, 2011IAT 33424 Location  Observations may be –In lab - Maybe a specially built usability lab Easier to control Can have user complete set of tasks –In field Watch their everyday actions More realistic Harder to control other factors

25. March 10, 2011IAT 33425 Challenge  In simple observation, you observe actions but don’t know what’s going on in their head  Often utilize some form of verbal protocol where users describe their thoughts

26. March 10, 2011IAT 33426 Verbal Protocol  One technique: Think-aloud –User describes verbally what s/he is thinking and doing What they believe is happening Why they take an action What they are trying to do

27. March 10, 2011IAT 33427 Think Aloud  Very widely used, useful technique  Allows you to understand user’s thought processes better  Potential problems: –Can be awkward for participant –Thinking aloud can modify way user performs task

28. March 10, 2011IAT 33428 Teams  Another technique: Co-discovery learning –Join pairs of participants to work together –Use think aloud –Perhaps have one person be semi-expert (coach) and one be novice –More natural (like conversation) so removes some awkwardness of individual think aloud

29. March 10, 2011IAT 33429 Alternative  What if thinking aloud during session will be too disruptive?  Can use post-event protocol –User performs session, then watches video afterwards and describes what s/he was thinking –Sometimes difficult to recall

30. March 10, 2011IAT 33430 Historical Record  In observing users, how do you capture events in the session for later analysis?

31. March 10, 2011IAT 33431 Capturing a Session  1. Paper & pencil –Can be slow –May miss things –Is definitely cheap and easy Time 10:00 10:03 10:08 10:22 Task 1 Task 2 Task 3 … SeSe SeSe

32. March 10, 2011IAT 33432 Capturing a Session  2. Audio tape –Good for talk-aloud –Hard to tie to interface  3. Video tape –Multiple cameras probably needed –Good record –Can be intrusive

33. March 10, 2011IAT 33433 Capturing a Session  4. Software logging –Modify software to log user actions –Can give time-stamped key press or mouse event –Two problems: Too low-level, want higher level events Massive amount of data, need analysis tools

34. March 10, 2011IAT 33434 Assessing Usability  Usability Specifications –Quantitative usability goals, used a guide for knowing when interface is “good enough” –Should be established as early as possible in development process

35. March 10, 2011IAT 33435 Measurement Process  “If you can’t measure it, you can’t manage it”  Need to keep gathering data on each iterative refinement

36. March 10, 2011IAT 33436 What to Measure?  Usability attributes –Initial performance –Long-term performance –Learnability –Retainability –Advanced feature usage –First impression –Long-term user satisfaction

37. March 10, 2011IAT 33437 How to Measure?  Benchmark Task –Specific, clearly stated task for users to carry out  Example: Calendar manager –“Schedule an appointment with Prof. Smith for next Thursday at 3pm.”  Users perform these under a variety of conditions and you measure performance

38. March 10, 2011IAT 33438 Assessment Technique Usability Measure Value to Current Worst Planned Best poss Observ attribute instrument be measured level acc level target level level results Initial Benchmk Length of 15 secs 30 secs 20 secs 10 secs perf task time to (manual) success add appt on first trial First Quest -2..2 ?? 0 0.75 1.5 impression

39. March 10, 2011IAT 33439 Summary  Measuring Instrument –Questionnaires –Benchmark tasks

40. March 10, 2011IAT 33440 Summary  Value to be measured –Time to complete task –Number of percentage of errors –Percent of task completed in given time –Ratio of successes to failures –Number of commands used –Frequency of help usage

41. March 10, 2011IAT 33441 Summary  Target level –Often established by comparison with competing system or non-computer based task

42. Ethics  Testing can be arduous  Each participant should consent to be in experiment (informal or formal) –Know what experiment involves, what to expect, what the potential risks are  Must be able to stop without danger or penalty  All participants to be treated with respect Nov 2, 2009IAT 33442

43. Consent  Why important? –People can be sensitive about this process and issues –Errors will likely be made, participant may feel inadequate –May be mentally or physically strenuous  What are the potential risks (there are always risks)? –Examples?  “Vulnerable” populations need special care & consideration (& IRB review) –Children; disabled; pregnant; students (why?) Nov 2, 2009IAT 33443

44. Before Study  Be well prepared so participant’s time is not wasted  Make sure they know you are testing software, not them –(Usability testing, not User testing)  Maintain privacy  Explain procedures without compromising results  Can quit anytime  Administer signed consent form Nov 2, 2009IAT 33444

45. During Study Make sure participant is comfortable Session should not be too long Maintain relaxed atmosphere Never indicate displeasure or anger Nov 2, 2009 IAT 33445

46. After Study State how session will help you improve system Show participant how to perform failed tasks Don’t compromise privacy (never identify people, only show videos with explicit permission) Data to be stored anonymously, securely, and/or destroyed Nov 2, 2009 IAT 33446

47. March 10, 2011IAT 33447 One Model