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3.2 Cognitive Task Analysis

3.2 Cognitive Task Analysis. What is wanted. Analysis. Design. Evaluation. Cognitive Task Analysis. Core methodology used in cognitive science Study human performance In laboratory In field Decision making, reasoning, and information needs Physical & mental

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3.2 Cognitive Task Analysis

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  1. 3.2 Cognitive Task Analysis What is wanted Analysis Design Evaluation

  2. Cognitive Task Analysis • Core methodology used in cognitive science • Study human performance • In laboratory • In field • Decision making, reasoning, and information needs • Physical & mental • GOMS(Goals, Operators, Methods, and Selection rules)

  3. Goal • 「使用者必須完成的事物」 • 「花費努力的方向」

  4. Operator • 「針對目標所進行的動作(action)」 • 「移動滑鼠」、「按滑鼠左鍵」 • 「按滑鼠右鍵」、「移動DELETE鍵」 • 導致狀態改變 • Mentally or physically • 執行時間 • 操作時間獨立性 • Operartor估計的正確性模型整體的正確性

  5. Method 標定 刪除法 字元 刪除法

  6. Selection Rules • IF 段落字元數 > 10 • THEN Use 標定刪除法 • ELSE Use 字元刪除法

  7. Coarse GOMS model

  8. Fine GOMS model Goal Subgoal Operator

  9. Decomposition Criteria 操作時間可衡量性 操作時間獨立性

  10. Keystroke-Level Model (KLM)Operators

  11. KLM Example Design 1: Use 資源回收桶 Design 2: 檔案總管刪除選單

  12. Action Sequence in Design 1

  13. Operator Sequence in Design 1

  14. Action Sequence in Design 2

  15. Operator Sequence in Design 2

  16. Modeling with Ms How much $$? Password? Where the button? The account#? Final check

  17. Adding Ms to Operator Sequence in Design 1(Novice)

  18. Adding Ms to Operator Sequence in Design 1(Novice)

  19. Adding Ms to Operator Sequence in Design 1(Experienced User)

  20. 3.3 Experiment What is wanted Analysis Design Evaluation

  21. Experiment • Manipulate and measure variables • Under controlled conditions • Test the hypothesis

  22. Participants • Match the expected user population • Test UML diagrams with students? • Similar subjects • Age • Level of education • Experience with computers • Experience with tested interface • Experience or knowledge of the task domain • The representativeness issue

  23. Participants • pragmatic considerations • Nielsen and Landauer • usability testing with a single participant will find about a third of the usability problems • little to be gained from testing with more than five • For observation-based studies (alandix) • Alan dix • >= 10

  24. Variables • Independent variables • manipulated to produce different conditions for comparison • Levels • Dependent variables • Measured • Ex: Usability metrics • Hypotheses

  25. User perceptions of security, convenience and usability for ebanking authentication tokens Computers & Security, 28 (2009), pp. 47-62

  26. Independent Variable all small and portable as similar as possible to control extraneous variables

  27. Device 1 & 2

  28. Device 3

  29. Instruction Page Two-factor authentication

  30. Dependent Variable

  31. Dependent Variable- Satisfaction

  32. Dependent Variable- Satisfaction

  33. Tasks Data collection: Satisfaction Data collection: Overall Log on Find Account Balance Do Transaction (Type 1, 2, 3) Confirmation Log off Device A or B or C randomization T0 Log on Find Account Balance Do Transaction (Type 1, 2, 3) Confirmation Log off Device A or B or C T1 Log on Find Account Balance Do Transaction (Type 1, 2, 3) Confirmation Log off Device A or B or C T2 Log on Find Account Balance Do Transaction (Type 4) Confirmation Log off Pick one device Counter- balance T3

  34. Participants • Bank customers using e-banking services • 50 participants • Balanced by age (35 & 35) • 50% vs. 50% • Also balanced by gender • M: F = 24: 26 • Usage • At home (92%); at work (32%); at college or int. café (4%)

  35. Analysis on Log-on Time Repeated-measures ANOVA with age and gender as the between-subject factors: F = 126.1; df = 1.167; p < 0.001 Younger < Older p = 0.058 Post hoc pairwise comparisons (Bonferroni) PB < CA; PB < PIN; CA < PIN

  36. Analysis on Confirmation Time Repeated-measures ANOVA with age and gender as the between-subject factors: F = 49.162; df = 1.427; p < 0.001 Post hoc pairwise comparisons (Bonferroni) PB < CA; PB < PIN; CA < PIN Younger < Older p < 0.0001 With all three devices

  37. Analysis on Effectiveness • No errors made • Need to re-orient • 0% access Help page • No errors made • Failing to insert the card before pressing the button • No assistance needed due to the on-screen instructions • 0% access Help page

  38. Analysis on Effectiveness • Assistance needed (9) • Using PINs as OTPs • Using the default ‘CODE’ • Trouble in entering PIN • Often re-boot • Little instruction reading • Complain … • 4% access Help page

  39. Analysis on Mean Usability Repeated-measures ANOVA with age and gender as the between-subject factors: F = 81.040; df = 2; p < 0.0001 Post hoc pairwise comparisons PB > CA; PB > PIN; CA > PIN

  40. Analysis on Perceived Quality Repeated-measures ANOVA with age and gender as the between-subject factors: F = 25.5; df = 1.45; p < 0.0001 Post hoc pairwise comparisons PB > CA; PB > PIN; CA > PIN female < male p = .003

  41. Analysis on Perceived Convenience Repeated-measures ANOVA with age and gender as the between-subject factors: F = 141.26; df = 1.56; p < 0.0001 Post hoc pairwise comparisons PB > CA; PB > PIN; CA > PIN female < male p = 0.035

  42. Analysis on Perceived Security Repeated-measures ANOVA with age and gender as the between-subject factors: F = 21.84; df = 1.59; p < 0.0001 Post hoc pairwise comparisons PB < CA; PB < PIN; CA < PIN

  43. Comparison of Devices

  44. Analysis on Usability in Re-Use

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