The art and science of measuring people

1. The art and science of measuring people • Reliability • Validity • Operationalizing

2. Overview of design and analysis Posing a usability question Conceptualizing the question Operationalizing the related concepts Identifying Independent, Dependent, & Controlled Variables Developing the Hypothesis

3. Choosing the testing method What method is appropriate for the current situation? (experiment, observation, surveys etc.) >> choice of method as a trade off between control realism Experimental, Quasi-Experimental and Non-Experimental Methods.

4. Collecting data The art of finding and recruiting participants A practical view of randomization: Randomization and Pseudo Randomization Random Selection and Random Assignment. Practical issues about sample size and statistical power.

5. Analyzing the data: Basic Statistics Levels of measurement: nominal, ordinal, interval, and ratio Mean, median, standard deviation Testing mean differences Significance levels and what they mean

6. Analysis of experimental designs: Single Factor Experiments Statistical Hypothesis Testing Estimates of Experimental Error Estimates of Treatment Effects Evaluation of the Null Hypothesis Various ANOVA models

7. Multi Factor Experiments Advantages of the factorial design Interaction Effects The power of within-subjects designs (reduction of variance) The two factorial experiment Higher Order Factorial Designs

8. Analysis of Non-Experimental Studies Statistical methods for analyzing correlational data Correlations, Scatter Plots, Partial Corrs Multiple Regression Introduction to Factor Analysis, Cluster Analysis and Multidimensional Scaling

9. Surveys and Questionnaires The design of surveys and questionnaires How to frame questions Kinds of scales: Likert, Semantic Differential etc. Analyzing survey data: which items are useful, Item Response Theory Forming a scale to measure an attribute, e.g., satisfaction. Reliability, validity of scale

10. Measuring Individual Differences How to test for individual differences within users Kinds of individual differences variables: -demographic: such a age, gender etc. -situational: motivation, interest, fatigue -cognitive: memory, cognitive style etc., -personality: internal/external locus of control How to analyze existing data to identify individual differences, and how to design studies to test for individual differences?

11. Frenzied Shopping: Obstacles to purchase, and the perception of download times -A study on ecommerce conducted by Jared Spool A critical analysis andIllustration of alternative methods of examining this question

12. Create a realistic scenario: in present situation, get person motivated Counted obstacles to purchase Advantages of measure: concrete: people agree about measure valid: good measure of actual ecommerce experience Disadvantages of measure: not reliable: since situation is not structured data analysis problems Frenzied shopping

13. Results • Found more than 200 obstacles to purchase • The more the no of users, the greater the no of problems • What’s wrong with each test discovering hundreds of problems? • Client has limited resources, need to focus on solving important (most common / most catastrophic problems)

14. More results:Perception of download times How long will users wait for pages to download? -Should web developers waste their time in making pages faster. Method:Users were asked to rate the perceived speed of pages after they had completed task. Ave. Speed Rated Amazon.com 30 sec Fastest About.com 8 sec Slowest

15. So what do download times relate to? • Only correlated with success or failure of shopping. • (Amazon.com judged to be slower than About.com even though About.com was much faster) • Result is foregone conclusion given the task. • Problems with method: • Memory issues: Users asked for ratings at the end of their experience with all the sites. Retrospective memory problems. • Ask someone waiting for a page to download if it is taking too long!

16. Timeline Issues Rated speed no longer reflects the browsing, searching part of the experience. Cannot infer that download speeds are not important, can only infer that perception of download speeds can be influenced by other aspects of site

17. Perception of download speed and all the ways to study it...

18. Survey: Are people bothered by long download times? • Sample Question: • How often do you leave a site without waiting for the first page to download? • 0-5% of times • 5-10% of times • 10 % and higher • In your opinion, how important are the below web site characteristics. Rate their relative importance. • Download speed • site content • site interactivity Possibilities: Task based surveys

19. Observation: Do people seem to like fast (without graphics) sites as compared to slow (with graphics) sites? • Method: Make two versions of a site, one with sophisticated graphics (slower site) and the other mostly text (faster site). Ask subjects to browse / complete a task on both sites. • Measurement: Watch participants for signs of frustration or satisfaction with speed of site

20. Experiment: Relationship of perceived download times to actual download times? • Method: Find similar sites with differential speeds. Ask people to complete the same tasks on both sites. Give them some interesting and some boring tasks, and less than enough time to complete the task. • Measurement: Log the clicks of the users as they traverse the sites. How many of the interesting and how many boring tasks did they complete. Relate that to download speed of site. • Do some users tend to be more frustrated with slower sites.

21. User Logs: Do people leave sites while waiting for slow pages to download? • Method: Find similar sites with differential speeds. Analyze the server logs for the sites. • Measurement: Log the clicks of the users as they traverse the sites. How many of the interesting and how many boring tasks did they complete. Relate that to download speed of site. • Do some users tend to be more frustrated with slower sites.

22. The state of the art • What usability methods are currently prevalent and accepted in the field • CUE 2

23. Comparative Usability Evaluation(CUE) 2 • Purpose: Too much emphasis on one-way mirrors and scan converters • Little knowledge of REAL usability testing procedures • ”Who checks the checker?” • Method: Nine teams tested the usability of a web site • Seven professional teams • Two student teams • Four European, five US teams • Test web-site: www.hotmail.com Molich et al., 1999

24. Problems found in Comparative Usability Evaluation

25. Problem Found by Seven Teams During the registration process Hotmail users are asked to provide a password hint question. The corresponding text box must be filled. Most users did not understand the meaning of the password hint question. Some entered their Hotmail password in the Hint Question text box.

26. Characteristics of the tests

27. Problems by teams

28. What factors predict no of problems & no of common (non-exclusive) problems?

29. Inferences from CUE study Much disagreement about methods of usability testing How to test? Who should test? What methods to use? How many testers to have? How many users to have?