1. After testing users Compile Data Compile Data Summarize Summarize Analyze Analyze Develop recommendations Develop recommendations Produce final report Produce final report

2. Compile Data Compile data as you test Compile data as you test Speeds up overall analysis Speeds up overall analysis Transfer hand written notes to computer Transfer hand written notes to computer Record data that is fresh in you mind Record data that is fresh in you mind Do it each data of testing Do it each data of testing

3. Creating Summaries Create descriptive summaries Create descriptive summaries Quantitative data Quantitative data Transfer information into summary sheets Transfer information into summary sheets Allows you to see patterns Allows you to see patterns

4. Summarize Performance Data Summarize performance data in terms of: Task timings Task timings Task accuracy Task accuracy

5. Task Timings How much time users required to complete a task Mean time to complete Mean time to complete Median time to complete Median time to complete Range of completion times Range of completion times Standard deviation of completion times Standard deviation of completion times

6. Mean time to complete Average time to complete task: Sum of all Completion Times mean = ------------------------------- mean = ------------------------------- Number of Participants Number of Participants

7. Mean time to complete Gives a rough indication of how the group performed Gives a rough indication of how the group performed Can be used to determine if user did better or worst Can be used to determine if user did better or worst If task time are very skewed then use: If task time are very skewed then use: Median time to complete

8. Time that is exactly in the middle position when all are listed in ascending order Time that is exactly in the middle position when all are listed in ascending order

9. Range of completion times Shows highest and lowest completion times for each task Shows highest and lowest completion times for each task Very revealing if there is a huge difference Very revealing if there is a huge difference Might be affected by user’s experiance Might be affected by user’s experiance

10. Standard deviation Measures range of variability Measures range of variability How times differ from one another How times differ from one another

11. Task Accuracy Count of number of errors Three common ones: % of users performing successfully within time benchmark % of users performing successfully within time benchmark % of users performing successfully % of users performing successfully % of users performing successfully including those who required assistance % of users performing successfully including those who required assistance

12. Summarize Preference Data For limited choice questions: Sum counts of number chosen Sum counts of number chosen For free form questions: List all questions and group similar answers List all questions and group similar answers

13. Produce mean scores of Semantic Differentials: Simple 3 2 1 0 1 2 3 Complex 1 2 3 4 5 6 7 1 2 3 4 5 6 7 Summarize Preference Data

14. Other measures # of times help was accessed # of times help was accessed # of times manual # of times manual # of points of hesitation # of points of hesitation

15. Analyze Data Begin analysis with the tasks users had th most problem with Begin analysis with the tasks users had th most problem with Keep focused on the worst problems Keep focused on the worst problems

16. Analyze Data Id and focus on tasks that did NOT meet criteria Id and focus on tasks that did NOT meet criteriaExample: 70% did not complete task A 70% did not complete task A Label this a problem

17. Analyze Data Id user errors and difficulties Id user errors and difficulties Conduct a source of error analysis Conduct a source of error analysis Some will be obvious Some will be obvious Some will be very subtle Some will be very subtle

18. Problem Analysis Prioritize problems by criticality: Criticality = Severity + Probability of Occurrence Severity + Probability of Occurrence

19. Severity Ranking

20. Frequency Ranking

21. Develop Recommendations Translates data and summaries into recommendations Translates data and summaries into recommendations Final step before generating report Final step before generating report Take break from processes for a few days Take break from processes for a few days

22. Recommendations Difference perspective are essential Difference perspective are essential Need a buy-in Need a buy-in Focus on solutions with the widest impact Focus on solutions with the widest impact Also consider global usability issues Also consider global usability issues

23. Recommendations Ignore “Political Considerations” Ignore “Political Considerations” Short and Long term recommendations Short and Long term recommendations Indicate areas where further research is needed Indicate areas where further research is needed Be thorough Be thorough

24. Usability Report Provide solutions Provide solutions Be specific Be specific Clearly state the recommendation Clearly state the recommendation

25. Usability Report Short Short Easy to read Easy to read Communicate findings Communicate findings

26. Usability Report Sections: Executive Summary Executive Summary Method Section Method Section Results Results Findings and recommendations Findings and recommendations Appendices Appendices

27. Memory Usability affected by how we remember Usability affected by how we remember Capability of memory Capability of memory Limitations of memory Limitations of memory

28. Memory What we remember and how we can apply what we already know What we remember and how we can apply what we already know Highly variable Highly variable

29. Memory Based on model of human memory: Based on model of human memory:

30. Memory Short-Term memory is small Short-Term memory is small Long-Term memory stores large amount but fallible Long-Term memory stores large amount but fallible

31. Memory Chunking Chunking Break large data into smaller more recallable chunks Break large data into smaller more recallable chunks SSN vs Drivers license number SSN vs Drivers license number URL Design URL Design

32. Mental Models How users use memory to understand new experiences How users use memory to understand new experiences Mental models used to make predictions of how a system works Mental models used to make predictions of how a system works Can lead to usability issues Can lead to usability issues

33. Bad Designs

34. Conceptual Models Can understand how it works because you build a simulation in your head and simulate it operation Can understand how it works because you build a simulation in your head and simulate it operation Three parts: Constraints Constraints Affordances Affordances Mappings Mappings

35. Constraints Helps users by restricting behaviors Constraints: Physical Physical Semantics Semantics Cultural Cultural Logical Logical

36. Affordances Defines possible: Uses Uses Actions Actions Functions Functions Understand how something works based on appearance

37. Affordances Good affordances enable user to use just by looking Good affordances enable user to use just by lookingNo: Label Label Icon Icon Instructions Instructions

38. Affordances

39. Mapping Relationship between actions and results Relationship between actions and results Controls and their effects Controls and their effects System state and what is visible System state and what is visible

40. Bad Mapping

41. Mental Models Design Model Design Model User Model User Model System Model System Model

42. Mental Models

43. Mental Model

44. Metaphors Help guide mental model choice Help guide mental model choice Speeds the learning process Speeds the learning process Brittle Brittle Do not expand very well Do not expand very well

45. Information Architecture Helps users find information quickly and easily Helps users find information quickly and easily Poor information architecture make users confused, frustrated, and angry Poor information architecture make users confused, frustrated, and angry Defines mapping between what a site is and how it will work Defines mapping between what a site is and how it will work

46. Information Architecture

49. Matter of Perspective

50. Content Organization Major component of user-centered design Major component of user-centered design Major issue with web sites Major issue with web sites Deals with user’s biggest complaint: Deals with user’s biggest complaint: “I can’t find what I am looking for.”

51. Content Organization Two levels of searching: Can’t find it on the web (search engines) Can’t find it on the web (search engines) Can’t find it on site (site organization) Can’t find it on site (site organization) Creates foundation for effective site navigation Creates foundation for effective site navigation

52. Organizational Systems Schemes Schemes Structures Structures

53. Organizational Schemes Classification scheme for content items Classification scheme for content items How to cluster items into groups How to cluster items into groups Scope of content Scope of content

54. Organizational Structures Determines relationships between groups Determines relationships between groups Method of grouping items Method of grouping items

55. Organizational Schemes Taking a drink from a fire hose Taking a drink from a fire hose Question becomes how to organize information into categories which are logically consistent Question becomes how to organize information into categories which are logically consistent Part of every day life Part of every day life

56. Organizational Schemes Two categories of organization schemes: Exact Exact Ambiguous Ambiguous

57. Exact Schemes Divides information into mutually exclusive groups Divides information into mutually exclusive groups Category Category Time Time Location Location Alphabet Alphabet Continuum Continuum

58. Content Organization

59. Organizational Schemes