1. Evaluation Methods April 20, 2005 Tara Matthews CS 160

2. In 160 We’ve Covered… Task Analysis & Contextual Inquiry Cognitive Walkthrough Heuristic Evaluation WOZ usability study w/ paper prototypes

3. There are many more methods… Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

4. How to chose a method? Stage of study –formative, iterative, summative Pros & cons Metrics –depends on what you want to measure Qualitative vs. quantitative Research perspective –CS vs. psychology vs. sociology

5. Pros & Cons Realism Precision Generalizability Time & cost Researcher expertise

6. Methods Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

7. Survey Online / paper questionnaires distributed to target audience Can be used to –tabulate quantitative data –gather qualitative feedback (opinions, feelings, etc.) Useful at any time in study

8. Survey Pros –Easy to get a large number of responses. –Quick and easy to conduct. –Highly generalizable. Cons –Self-selection. –Participants often only offer enough information to answer the question. –Can miss details. –Low in realism and precision.

9. Interview Evaluators formulate questions on the issues of interest. Interview representative users, asking them these questions in order to gather information desired. Interviewer reads questions to user, who replies verbally; interviewer records responses.

10. Interview Pros –Quick and easy to conduct. –Gives designer quick feedback on a range of ideas. –Can get a person’s initial reaction to an idea. –Can get detailed information from a person. Cons –Often takes place away from natural setting. –Question wording or interviewer “body language” can bias answers. –High probability of false positives and missed problems (e.g., users may not have a clear idea of how an app will be used). –Can miss details if interviewer doesn’t know what issues to draw out.

11. Controlled Lab Experiment In lab, manipulate one feature of a system to assess the causal effects of the difference in that manipulated feature on other behaviors of the system. Example: –in lab, show users 4 versions of a website: blue, yellow, red, and black text –measure time to find specific words –compare

12. Controlled Lab Experiment Pros –Provides precise, quantifiable data. –Easier to draw inferences from data. –Relatively quick. –Can get a medium-sized number of participants. Cons –Short duration of a lab experiment may not be enough to allow users to become accustomed to an app. –Not a natural setting – interaction may not be normal.

13. In-lab Observation Participants come to lab to "use" an interface Given sample tasks to complete with it Evaluators observe and possibly audio- or videotape Participants may "think out loud" Can use lo-fi prototype (for a project in the design stage) to an almost-complete interface Evaluators note participants’ –emotions, exclamations, facial expressions, and other "qualitative" data –take note of quantitative data such as time to complete a task or number of errors

14. In-lab Observation Pros –Relatively quick. –Can get a medium-sized number of participants. Cons –Observations are subjective and error prone. –Short duration of lab observation is not enough time for user to get accustomed to using the interface. –Not a natural setting – interaction may not be normal.

15. Controlled Field Experiment In natural setting, manipulate one feature of a system to assess the causal effects of the difference in that manipulated feature on other behaviors of the system. Example: –Participants use 3 different input devices in their own office: mouse with 1, 2, or 3 buttons –Perform a set of tasks –Measure differences

16. Controlled Field Experiment Pros –Less intrusive than most other evaluation methods. –Provides more precise data than field observation. –Can observe natural behavior of user (though some part of the system will be controlled/unnatural). Cons –More intrusive than field observation. –Less natural than field observation.

17. Field Observation Study Evaluator makes direct observations of “natural” systems Takes care to not intrude on / disturb those systems A.K.A. “ethnography”

18. Field Observation Study Pros –Only way to observe natural behavior of user & interaction between user & tools. Cons –Difficult and time consuming. –Hard to get permission to observe people. –Observations are subjective and error prone. –Cannot make strong interpretations from observations. –Not very generalizable.

19. Heuristic Evaluation Pros –Quick and easy. Cons –Nielson’s heuristics may not be as relevant to non-GUIs. –Results in false positives in missed problems, especially when experts are not part of target audience.

20. Cognitive Walkthrough Pros –Quick and easy. Cons –Results in false positives and missed problems when evaluator is different from target audience.

21. Automate Observation Study Techniques include –video or audio recording of user –pop-up screens –screen shots –time logging –log users actions (collecting statistics about detailed system use)

22. Automate Observation Study Pros –Eases burden on observers for data collection & analysis. Cons –Setup is often more time-consuming to complete. –Harder to get approved if it involves analysis of videotape or audiotape. –May miss nuanced/interpretive details.

23. Experimental Simulation In-lab experiment that is as much like some real situation as possible. Example: –ground-based flight simulator –behaves as closely as possible to a real flight –still under researcher control

24. Experimental Simulation Pros –Still fairly precise. –More realistic than in-lab experiment. Cons (same as lab exp.) –Short duration of a lab experiment may not be enough to allow users to become accustomed to an app. –Not a natural setting – interaction may not be normal.

25. Claims Analysis Claim = statement that a certain aspect (button, scrollbar) of a design has psychological implications reflected in how capable a user is in using that design UI artifacts are listed along with their design features & pros/cons Helps –select among alternative designs –clarify questions to be analyzed through user testing by stating how the design should work (in claims)

26. GOMS A method to describe user tasks and how a user performs those tasks with a specific interface design Views humans as information processors –Small number of cognitive, perceptual, and motor operators characterize user behavior To apply GOMS: –Analyze task to identify user goals (hierarchical) –Identify operators to achieve goals –Sum operator times to predict performance GOMS = –Goals: What a user wants to accomplish –Operators: Cognitive or physical actions that change the state of the user or the system –Methods: Groups of goals and operators –Selection rules: Determine which method to apply

27. GOMS Pros –Predict human performance before committing to a specific design in code or running user studies –Many studies have validated the model (it works) Cons –Assumes error-free, skilled user behavior –No formal recipe for how to perform analysis –Significant time investment

28. Computer Simulation Creating a complete & closed system that models the operation of the concrete system without users. Example: –geophysical process going on in connection with the eruption of Mount St. Helens

29. Computer Simulation Pros –Supposedly high in realism (depends on accuracy of data/system replication) Cons –Low in precision & generalizability

30. Formal Theory Formulating general relations (propositions, hypothesis, or postulates) among a number of variables of interest. Pros –Relatively generalizable Cons –Not realistic or precise

31. How to chose a method? Stage of study Pros & cons –Realism –Precision –Generalizability –Time & cost Researcher expertise Metrics Qualitative vs. quantitative Research perspective

32. Methods Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Heuristic Evaluation Cognitive Walkthrough Contextual Inquiry Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

33. Early Stage Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Heuristic Evaluation Cognitive Walkthrough Contextual Inquiry Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

34. Early Stage Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Heuristic Evaluation Cognitive Walkthrough Contextual Inquiry Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

35. Iterative & Summative Stages Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Heuristic Evaluation Cognitive Walkthrough Contextual Inquiry Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

36. Iterative & Summative Stages Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Heuristic Evaluation Cognitive Walkthrough Contextual Inquiry Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

37. Realism Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Heuristic Evaluation Cognitive Walkthrough Contextual Inquiry Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

38. Realism Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Heuristic Evaluation Cognitive Walkthrough Contextual Inquiry Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

39. Precision Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Heuristic Evaluation Cognitive Walkthrough Contextual Inquiry Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

40. Precision Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Heuristic Evaluation Cognitive Walkthrough Contextual Inquiry Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

41. Generalizability Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Heuristic Evaluation Cognitive Walkthrough Contextual Inquiry Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

42. Generalizability Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Heuristic Evaluation Cognitive Walkthrough Contextual Inquiry Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

43. Time & Cost Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Heuristic Evaluation Cognitive Walkthrough Contextual Inquiry Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

44. Time & Cost Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Heuristic Evaluation Cognitive Walkthrough Contextual Inquiry Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

45. Researcher Perspective Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Heuristic Evaluation Cognitive Walkthrough Contextual Inquiry Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

46. Metrics: examples Traditional GUIs: –efficiency (time to complete task) –accuracy (# of errors) –simplicity Peripheral Displays: –awareness (recall) –distraction (dual-task behavior) –aesthetics

47. Peripheral Displays Survey Interview Controlled-lab experiment In-lab observation Controlled field experiment Field observation study Heuristic Evaluation Cognitive Walkthrough Contextual Inquiry Automated observation user study Experimental simulation Claims analysis GOMS Computer simulation Formal theory

48. Questions?