1. Summary of Task Analysis, social aspects, and alternative approaches: Chapters 9, 12, 13, (15) 16, A2 IST 331 - Olivier Georgeon and Frank Ritter 23 April 2012 1

2. Agenda of the presentation Task Analysis – Data gathering – Formal task description Social aspects of users Alternative approaches – Non goal-driven – Co-evolution Summaries 2

3. Task Analysis 3

4. Task Analysis: Data Gathering (ch 12) Lots of task analysis methods None completely satisfactory Best solution is to employ a variety of methods – Questionnaires and Interviews – Observational studies – Examination of competing, or similar products – Literature review – Unstructured user input. Spontaneous feedback – Like pizza (not so much like soufle) 4

5. Task Analysis: Formal task description KLM – V. easy to use, fast, simple, clear, timing, can be tightened – For expert behavior only, can’t do dual tasks, learning, multiple strategies, like a single trace Hierarchical Task Analysis – Easy to use, fast, simple, clear – For expert behavior, dual tasks not represented, no learning, cannot be tightened, no timing GOMS – Easy to use, fast, simple, less clear – For expert behavior only. Can’t do dual tasks easily. Require precise goals. – Like a program 5

6. GOMS 6 Goal 1 (or Task) Goal 2 Goal 3 Method 1Method 2 Selection rule 1 Op 1 Op 2 Goal 2 Op 3 Method 3 Op 4 Op 5 Goal 4 Op 6 Time …

7. Activity theory (lecture) For representing tasks where time is not a major issue For representing learning activities and development For representing activities with other desired outcomes Examines relationship between people, tasks, world and social constructs Analysis into:

8. Social aspects 8

9. From sociological studies (ch. 9) Diffusion of Social Responsibility Complementarities between individuals Social loafing Majority/minority effect Risk taking effect Cognitive dissonance – Who you are / Who you want to be / who you want people think you are. 9

10. Prisoner’s Dilemma Interactions can be summarised with payoff matrix People prefer high payoffs Good systems create payoffs to encourage the behavior they want There are ways to encourage good behavior – Make players public – Make their history public – Make payoff matrix public – Payoff what you want to encourage 10

11. How to write: Appendix 3 Be mindful of reader

12. Not always goal driven Users are free and do not fit a pre-defined model Users follow feeling and emotions User behavior evolve overt time New usages emerge New area for human behavior research 12

13. Post-hoc Evaluation When you can’t do gold standard of users and their tasks – Might not know: users, tasks, context, task frequency, how things fit together, etc. When you are driven by new technology There are tools for detailed activity analysis of users of a system studied systematically Human behavior analysis is still an active area of research. 13

14. Chapter 16 Summary

15. Conclusion Know your user's task – Data gathering – Formal task description Social aspects – Know your user's social context and motivations Alternative approaches – Non goal-driven – Co-evolution 15