1. UNDERSTANDING USERS: MODELING TASKS AND LOW- LEVEL INTERACTION Human-Computer Interaction 10.13.2012

2. Agenda  Project Part 1 notes  Task analysis review  An overview of HCI design  Fitts’s Law  Project group time

3. Project Part 1  Problem or task description, revised and refined  Description and justification of how the information above was collected  Description of the users and their tasks related to the problem, including a task analysis of a single task  Description of the larger system and environment  Analysis of the existing systems and tools used in the problem  Initial list of three usability criteria you will focus on, with justification  Support your claims with specific data and examples!  Prepare a poster about your work

4. Task Analysis review

5. Task analysis  Hierarchical Task Analysis (HTA)  Knowledge-Based Task Analysis

6. Hierarchical Task Analysis (HTA)  Two parts  Task breakdown – a listing of all tasks broken down into subtasks  Plans – specifications of the order of subtasks within the supertask  Often represented as a graphical diagram for clarity Example: changing a light bulb

7. Hierarchical Task Analysis

8. Knowledge-based analysis: TAKD  Focused on categorizing objects by action, function, or other properties  List all objects associated with the task  Build taxonomy using AND, OR, and XOR branching

9. Knowledge Based Analysis Kitchen item AND shape XOR dished mixing bowl, saucepan, soup bowl, glass flat plate, chopping board, frying pan function OR preparation mixing bowl, saucepan eating XOR for food plate, soup bowl for drink glass

10. Knowledge-based analysis TAKD – Task Analysis for Knowledge Description Taxonomic - unique categorizations of items, characteristics, and functions Good for understanding a problem language or an environment

11. Task analysis  When to use which?

12. Design process basics

13. Why is HCI Design Difficult? Difficult to deeply analyze human behavior May be too close to the domain Multiple clients with different needs Co-evolution of technology and users

14. Software life cycles – Waterfall Model Requirements Specification Architectural Design Detailed Design Coding and Unit Testing Integration and Testing Operation and Maintenance

15. Limitations of the waterfall model

16.  You can’t determine all requirements from the start  Some tasks will only be known after the user has interacted with the system  Users will perform tasks that weren’t intended by the designer  Doesn’t support the user’s perspective of the system

17. Software Life cycles – Iterative Waterfall Model Requirements Specification Architectural Design Detailed Design Coding and Unit Testing Integration and Testing Operation and Maintenance

18. Iterative design

19. Applying HCI in the cycle  Formative  Strategies to build a better interface prior to creating the technology  Summative  Assessing an existing interface after creating the technology

20. Formative techniques  Apply principles  “Don’t assume the user is right-handed”  Build prototypes  Apply design rules / standards  Java look and feel  Create usability specifications  The XYZ dialog takes < 5 sec.  Study potential users to understand their needs

21. Summative techniques  Empirical / laboratory evaluation  Expert review  Field study or deployment

22. Iterative design

23. Understanding users: Modeling

24. Modeling takes many forms  Interaction  Low-level/physical actions  Complex activities/tasks  Cognitive  Contextual

25. What is a model?

26.  A constructed representation intended to help understand and reason about the world  Abstracted and simplified  Generalized  Not necessarily reflective of how the world actually works

27. Fitts’s Law – Modeling physical actions

28. Physical modeling: Using Fitts’s Law  Models movement time for selection tasks  Quantitative modeling technique  A summative technique

29. Fitts’s Law Live!

30. Fitts’s Law demo  Tap back and forth between the two rectangles as quickly as you can!  Don’t worry about where in the rectangle you tap- just tap as many times as you can somewhere within the shape

31. Basics Movement time (MT) is proportional to Index of Difficulty (ID) of a selection task

32. The big picture The movement time for a well-rehearsed selection task: increases as the distance A to the target increases; and decreases as the size of the target W increases

33. Index of difficulty (ID) Measure difficulty of selection task ID = log 2 (2A/W) “bits” A = distance between targets W = target width

34. Movement time (MT) MT = a + b ID (a=0 if line passes through the origin) MT Difficulty

35. How MT is determined Empirical measurement establishes constants a and b Different for different devices and different ways the same device is used.

36. Original application of Fitts’s Law 1-dimensional selection task

37. Original application of Fitts’s Law W A

38. Extending to 2D  What is W when we consider 2 dimensions of movement? θ

39. Extending to 2D  What is W when we consider 2 dimensions of movement?  Same as usual? θ W’

40. Extending to 2D  What is W when we consider 2 dimensions of movement?  Smallest dimension? θ W’

41. Extending to 2D  What is W when we consider 2 dimensions of movement?  Distance from edge to centroid? θ W’

42. Application of Fitts’s law? When does it apply? When does it not?

43. Application of Fitt’s law? When does it apply? When does it not?  Used for predicting performance low-level physical actions  Automated tasks and actions  Minimal cognition – you don’t have to “think” about it

44. A possible example

45. How is Fitts’s Law used in UI design?  Predicting performance with an interface  May substitute for empirical testing, particularly in early stages  Comparing alternative UI layouts

46. KLM- another way of modeling physical action

47. Keystroke-Level Model (KLM)  Another way of doing physical modeling  Decompose tasks into low-level elements with time values  Calculate prediction for total execution time  Best for automated behavior

48. Keystroke-Level Model (KLM)  K – striking keys  B – pressing a mouse button  P – pointing (dragging a pointer to a target)  H – homing – switching the hand between the mouse and keyboard  D – drawing lines using the mouse  M – mentally preparing for a physical action  R – system response time

49. Keystroke-Level Model (KLM)  Calculate time required for individual generic actions  Decompose tasks into individual actions  Calculate the total time for a task as a sum of the time for each action  Can be used for comparing alternate ways of executing a task  Does not take time for cognition into account

50. For next week  Read “The Model Human Processor” by Card, Moran, and Newell