9. Image by MIT OpenCourseWare.6 14 12 10 8 5
Troughput (bps)
Error rate (%) 4 3 6 4 2 2 1
Mouse Trackball Joystick Touchpad
Troughput Error rate
Image by MIT OpenCourseWare.

11. © source unknown. All rights reserved.

16. Menu accelerators (Windows)
Keyboard Shortcuts
Keyboard commands
Menu accelerators (Windows)

18. Aggregating Questions

19. Use Defaults and History
Initially, most likely entry
After use, previous entry
Keep histories
Offer autocompletion

20. Anticipation

29. Image by MIT OpenCourseWare.50 40 30 20 15 10 8 6 5 4 3 2
Observed execution time (sec) 1 1
Predicted execution time (sec)
Text Editors
POET SOS DISPED
Graphic Editors
MARK UP DRAW SIL
Executive Subsystems
All Subsystems
Image by MIT OpenCourseWare.

35. High-level models of human-computer behavior
Developing Theories in HCI
must explain and predict human behaviour in the human-computer system
must work in a wide variety of task situations
must work within broad spectrum of system designs and implementations
Some low-level theories can be used to predict human performance
Fitts’ law: time to select an item with a pointing device
Keystroke level model: sums up times for keystroking, pointing, homing, drawing, thinking and waiting
General models that explain human behaviour with machines
Syntactic/semantic model (Shneiderman)
Stages of interaction (Norman)
all of psychology!

36. Syntactic/semantic model of user knowledge
A high level model of interaction, developed by Ben Shneiderman
Action
Object
Task
Computer
Semantic
Syntactic

37. 1. Syntactic knowledge
The rules or combinations of commands and signals
seen as device-dependent details of how to use system
examples:
backspace key delete previous character
tab move to next field in a form
right mouse button context menu
grep <word> <file> find word in a file
control-shift-K search messages (thunderbird)

38. 1. Syntactic knowledge (continued)
User problems with syntactic knowledge
syntactic details differ between (and within!) systems
little consistency –> arbitrary
hard to learn
easily forgotten
Syntactic

39. 2. Semantic knowledge: Computer concepts
The meaning behind computer concepts
People learn them by
meaningful learning
demonstrations
explanations of features
trial by error
models, analogies
relatively stable in memory
high level concepts
logical structure
cognitive model produced
usually transferable across computer systems
but not always
But: prefer to concentrate on task, not computer knowledge
Action
Object
Computer

40. 3. Semantic knowledge: task concepts
Action
Object
Task
The meaning behind the task concepts
is independent of the computer
Similar mechanism to computer concepts
Examples
how to write a business plan
format concerns
stylistic concerns
paragraph structure, etc.
creating a budget

41. What Syntactic/Semantic Model reveals
Mapping between the 3 items is key
Task semantics to computer semantics to computer syntax
task semantics: write document
computer semantics: open a file, use editor, save it to disk
computer syntax: select menu items, key strokes for formatting,...
Bad mapping: using latex to write document
aside from task semantics, must also know semantics/syntax of:
text editor
latex
Unix compiling and printing sequence (to typeset and print)
Good mapping: trashcan to throw away files
must know mouse syntax of selecting and dragging
computer semantics almost analogous to task semantics

42. Guideline from syntactic/semantic model
Reduce burden to task-oriented user of learning separate computer semantics and syntax
computer semantics
Use metaphors
hide unnecessary information
computer syntax
A little learning should go a long way...
As simple as possible and uniformly applicable
Generic commands
Syntax consistent between systems

43. Four Stages of an Interaction
(a simplified version of Norman’s 7 stages)
1. Form intention
2. Select an action
3. Execute the action
4. Evaluate the outcome

44. The four stages when performing a task
Physical activity
Execution
Action
Specification
Intention
Goals
Evaluation
Interpretation
Perception
Mental activity
expectation

45. Example task: improve document’s formatting
intention-1
intention-2
intention-3
action
specification
evaluate-1
evaluate-2
evaluate-3
interpretation
intention-4
evaluate-4
look better
block para
.pp->.sp
execution
perception
get formatted
output
printer

46. Image by MIT OpenCourseWare.

47. Gulf of Execution Gulf: Good system: gulf of execution Physical System
Do actions provided by system correspond to the intentions of the user?
Gulf:
amount of effort exerted to transform intentions into selected and executed actions
Good system:
direct mappings between Intention and selections
Goals
Physical
System
gulf of
execution

48. Gulf of Evaluation Gulf: Good system: Physical System Goals gulf of
Can feedback be interpreted in terms of intentions and expectations?
Gulf:
amount of effort exerted to interpret feedback
Good system:
feedback easily interpreted as task expectations
Physical
System
Goals
gulf of
evaluation

49. Bridging the Gulfs Physical Goals System action specifications
interface
mechanism
intentions
execution bridge
Physical
System
Goals
interpretations
evaluations
interface
display
evaluation bridge