Presentation is loading. Please wait.

Presentation is loading. Please wait.

May 18, 2010IAT 3341 IAT 334 Interface Design Chris Shaw ______________________________________________________________________________________ SCHOOL.

Similar presentations

Presentation on theme: "May 18, 2010IAT 3341 IAT 334 Interface Design Chris Shaw ______________________________________________________________________________________ SCHOOL."— Presentation transcript:

1 May 18, 2010IAT 3341 IAT 334 Interface Design Chris Shaw ______________________________________________________________________________________ SCHOOL OF INTERACTIVE ARTS + TECHNOLOGY [SIAT] | WWW.SIAT.SFU.CA

2 May 18, 2010IAT 3342 Exam Materials  Slides  Shneiderman & Plaisant Chapters 1-8  Programming materials –Supplemantary: Glassner Book Chapters 1-5, Chapters 10.2, 13.1-13.6 –On Sakai: Password: GlassnerIAT334

3 May 18, 2010IAT 3343 Why We Are Here  Look at human factors that affect software design and development  Central Topic: User interface design

4 May 18, 2010IAT 3344 HCI  What happens when a human and a computer get together to perform a task –Task Write a document Plan a budget Design a presentation Play a video game –Not a task.. Goof off (obviously)

5 May 18, 2010IAT 3345 Why is this important?  Computers (in one way or another) affect every person in society –Increasing % use computers in work, at home in the road…  Product success depends on ease of use

6 May 18, 2010IAT 3346 Course Aims  Consciousness raising for you –Eg. Don Norman “The Design of Everyday Things” –Doors Handles afford various opening method  Design critic

7 May 18, 2010IAT 3347 Goals of HCI (Shneiderman & Plaisant Chap1)  Allow users to carry out tasks –Safely –Effectively –Efficiently –Enjoyably

8 May 18, 2010IAT 334 Goals of System Engineering Functionality Tasks and sub-tasks to be carried out Reliability Maintaining trust in the system Standardization, integration, consistency and portability Schedules and budgets Adhering to timelines and expense Human factors principles and testing reduces costs

9 May 18, 2010IAT 3349 Usability  Five Measurable Goals of UI Design  Combination of –Ease of learning –High speed of user task performance –Low user error rate –Subjective user satisfaction –User retention over time

10 May 18, 2010IAT 334 Life-critical systems: air traffic control, emergency, power utilities etc. high reliability, error-free performance, lengthy training for systems, subjective satisfaction less of an issue Industrial and commercial uses: banking, inventory management, airline and hotel reservations, etc. low costs is critical over reliability, ease of learning, errors calculated against costs, subjective satisfaction of modest importance Interests in Human Factors in Design

11 Sept14, 2009IAT 334 Office, home, entertainment: productivity and entertainment applications ease of learning, low error rates, subjective satisfaction are paramount since use is discretionary and competition is fierce. Range of types of users from novice to expert. Exploratory, creative, and cooperative: web-based, decision- making, design-support, collaborative work, etc. users knowledgeable in domain but vary in computer skills, direct- manipulation using familiar routines and gestures work best, difficult systems to design and evaluate. Interests in Human Factors in Design

12 May 18, 2010IAT 334 Accommodating Human Diversity Physical Abilities and Workplaces Cognitive and Perceptual Abilities Personality Differences Cultural and International Diversity Users with Disabilities Elderly Users

13 May 18, 2010IAT 33413 Key Historical Event  Design of the first Mac 1983-1984  “The computer for the rest of us”

14 May 18, 2010IAT 33414 Improving Interfaces  Know the User! –Physical abilities –Cognitive abilities –Personality differences –Skill differences –Cultural diversity –Motivation –Special needs

15 May 18, 2010IAT 33415 Two Crucial Errors  Assume all users are alike  Assume all users are like the designer

16 Another Crucial Error  Have the user design it!  Users bring vital knowledge to design: –They know a lot about the problem –They know a lot about the current tools –They typically know very little about design May 18, 2010IAT 33416

17 May 18, 2010IAT 33417 UI Design/Develop Process  Analyze user’s goals  Create design alternatives  Analyze designs  Implement prototype  Test  Refine Design Evaluate Implement

18 May 18, 2010IAT 33418 Evaluation  Things we can measure –Time to learn –Speed of performance –Rate of errors by user –Retention over time –Subjective satisfaction

19 May 18, 2010IAT 33419 Interfaces in the World  VCR  Mouse  Phone  Copier  Car  Airline reservation  Air traffic control

20 May 18, 2010IAT 33420 History of HCI ______________________________________________________________________________________ SCHOOL OF INTERACTIVE ARTS + TECHNOLOGY [SIAT] | WWW.SIAT.SFU.CA

21 May 18, 2010IAT 33421 Ivan Sutherland  SketchPad - ‘63 PhD thesis at MIT –Hierarchy - pictures & subpictures –Master picture with instances –Constraints –Icons –Copying –Light pen as input device –Recursive operations

22 May 18, 2010IAT 33422 Douglas Engelbart  Invented the mouse  Landmark system/demo: –hierarchical hypertext, multimedia, mouse, high-res display, windows, shared files, electronic messaging, CSCW, teleconferencing, … 

23 May 18, 2010IAT 334 The Mouse source: & Doug Engelbart’s mouse - 1963-64

24 May 18, 2010IAT 33424 Alan Kay  Dynabook - Notebook sized computer loaded with multimedia and can store everything  Personal Computing  Desktop Interface

25 May 18, 2010IAT 33425 PCs with GUIs  Xerox PARC - mid 1970’s –Alto –Local processor, Bitmap display, Mouse –Precursor to modern GUI –LAN - Ethernet

26 May 18, 2010IAT 334 Menus source: Bill Atkinson’s Polaroids of the first pull-down menu prototype - circa 1979

27 May 18, 2010IAT 33427 Xerox Star - ‘81  First commercial PC designed for “business professionals” –Desktop metaphor, pointing, WYSIWYG  First system based on usability engineering

28 Windows 95 May 18, 2010IAT 33428

29 Handhelds  Portable computing + phone  Newton, Palm, Blackberry, iPhone May 18, 2010IAT 33429

30 May 18, 2010IAT 33430 Human Capabilities  Want to improve user performance  Know the user! –Senses –Information processing systems

31 May 18, 2010IAT 33431 Senses  Sight, hearing, touch important for current HCI –smell, taste ???

32 May 18, 2010IAT 33432 Sight  Visual System workings  Color - color blindness: 8% males, 1% females  Much done by context & grouping (words, optical illusions, …)

33 May 18, 2010IAT 33433 Hearing  Often taken for granted how good it is –Pitch - frequency –Loudness - amplitude –Timbre - type of sound (instrument)  Sensitive to range 20Hz - 22000Hz  Limited spatially, good temporal performance

34 May 18, 2010IAT 33434 Touch  Three main sensations handled by different types of receptors: –Pressure (normal) –Intense pressure (heat/pain) –Temperature (hot/cold)  Where important?

35 May 18, 2010IAT 33435 Models of Human Performance  Predictive  Quantitative –Time to perform –Time to learn –Number and type of errors –Time to recover from errors  Approximations

36 May 18, 2010IAT 33436 Basic HCI  Model Human Processor –A simple model of human cognition –Card, Moran, Newell 1983  Components: –Senses –Sensory store –Short-term memory –Long-term memory –Cognition

37 May 18, 2010IAT 33437 Information Processing  Usually serial action –Respond to buzzer by pressing button  Usually parallel recognition Driving, reading signs, listening to radio

38 May 18, 2010IAT 33438 Model Human Processor Basics  Parameters –Processors cycle time of 50-200ms –Memories have type, capacity, decay time  Types –Visual –Auditory –Tactile –Taste, smell, proprioception, etc

39 May 18, 2010IAT 33439 Model Picture Closeup

40 May 18, 2010IAT 33440 Perceptual Processor  Continually “grabs data” from the sensory system  Cycle time: 100ms [50 - 200] ms  Passes data to Image Store in unrecognized form –“Array of Pixels” (or whatever it is) from eyes –“Sound Intensities” from ears

41 May 18, 2010IAT 33441 Sensory Store  The “input buffer” of the senses  Stores most recent input unrecognized  Storage time and capacity varies by type –Visual: NominalRange Capacity:17letters of text[7 - 17] letters Decay Time:200ms [70 - 1000] ms –Audio: Capacity:5 letters of text [4.4-6.6] letters Decay Time: 1500 ms[900 - 3500] ms

42 May 18, 2010IAT 33442 Memory  Three “types” –Short-term memory Conscious thought, calculations –Intermediate Storing intermediate results, future plans –Long-term Permanent, remember everything ever happened to us

43 May 18, 2010IAT 33443 Memory: Sort Term  Short Term (Working) Memory (WM) –Gets basic recognition from Sensory Store “Stop sign” vs. “red octagon w/white marks” –7 +/- 2 “chunks” 4048946328 vs. 404-894-6328 –WM: NominalRange Capacity:7 chunks[5 - 9] chunks Decay Time:7 seconds [5 - 226] seconds Access Time:70ms[25 - 170] ms

44 May 18, 2010IAT 33444 Memory: Long Term  Long Term Memory (LTM) –“Unlimited” size –Slower access time (100ms) –Little decay –Episodic & Semantic  Why learn about memory? –Know what’s behind many HCI techniques –Predict what users will understand

45 May 18, 2010IAT 33445 LT Memory Structure  Episodic memory –Events & experiences in serial form  Semantic memory –Structured record of facts, concepts & skills

46 May 18, 2010IAT 33446 Read the colors of the words Black Red Orange Yellow Blue

47 May 18, 2010IAT 33447 MHP Operation  Recognize-Act Cycle –On each cycle, contents in WM initiate actions associatively linked to them in LTM –Actions modify contents of WM  Discrimination Principle –Retrieval is determined by candidates that exist in memory relative to retrieval cues –Interference by strongly activated chunks

48 May 18, 2010IAT 33448 Perception  Stimuli that occur within one PP cycle fuse into a single concept –movies (frame rate) Frame rate > 1 / Tp = 1/(100 msec/frame) = 10 f/sec –morse code listening rate  Perceptual causality –two distinct stimuli can fuse if the first event appears to cause the other –events must occur in the same cycle

49 May 18, 2010IAT 33449 Operation  Variable Cognitive Processor Rate –Cognitive Processor cycle time Tc is shorter with greater effort –Induced by increased task demands/information –Decreases with practice

50 May 18, 2010IAT 33450 Operation: Target finding  Task: Move hand to target area  Fitts Law –A series of microcorrections Correction takes Tp + Tc + Tm –Time Tpos to move hand to target width W which is distance D: Tpos = a + b log 2 (d/w + 1.0) –Movement time depends on relative precision

51 Jan 13, 2011IAT 33451 IAT 334 Interface Design Task Analysis ______________________________________________________________________________________ SCHOOL OF INTERACTIVE ARTS + TECHNOLOGY [SIAT] | WWW.SIAT.SFU.CA

52 Jan 13, 2011IAT 33452 Task Conformance  Task coverage –Can system do all tasks of interest?  Task adequacy –Can user do tasks? –Does system match real-world tasks?

53 Jan 13, 2011IAT 33453 Task Analysis  Analyzing how people do their jobs –Go to their environment –Learn about, analyze and describe their tasks  Examine users’ tasks to better understand what they need from interface and how they will use it

54 Task Analysis  Gather data about what users need to do or accomplish …then…  Represent data for interpretation and use in design decisions Jan 13, 2011IAT 33454

55 Information to be Gathered  Information about users  Description of environment –where the tasks will be performed  Major goals of the job –what will result in a successful end state?  User preferences & needs –before they even start: coffee, pen, notebook, log sheets… Jan 13, 2011IAT 33455

56 Jan 13, 2011IAT 33456 Task Analysis  Broad Focus  Observe users of current system(s)  Generate requirements –Hierarchical task analysis –Knowledge-based task analysis –Entity-Relationship model

57 Data Gathering Techniques 1. Observation 2. Interviews & Contextual Inquiry 3. Ethnography also… 4. Surveys & Questionnaires 5. Focus Groups & Expert Debriefing 6. Competitive Product Review 7. Documentation mining 8. Data logging Jan 13, 2011IAT 33457

58 Information to be Gathered  Tasks & Subtasks: –Physical –Cognitive –Communication  Conditions under which these tasks are done  Results/outcomes of tasks  Requirements to perform task: –Information –Communication with others –Equipment Jan 13, 2011IAT 33458

59 1. Observation  Watch users do what they do –Typically from a distance  Record with videotape –May require coding video later  Take lots of notes, sketches  Focus on specific task-relevant behaviors in notes, but later convert to abstract subtasks Jan 13, 2011IAT 33459

60 2. Interviews  Engage the user more than just watching  Structured interviews –Efficient, but requires training  Unstructured –Inefficient, but requires no training  Semi-structured –Good balance –Often appropriate Jan 13, 2011IAT 33460

61 3. Ethnography  Deeply contextual inquiry –“Wallow in the data”  “Live among” the users  Understanding the full complexity of behavior, in its complete social context  Note: Techniques based in sociology and anthropology--the study of humans Jan 13, 2011IAT 33461

62 4. Surveys & Questionnaires  Subjective answers in a quantitative format –What does this mean?  Questions: –Exploratory vs. confirmatory –Open-ended vs. categorical (exhaustive) –NB: If you ask it, use it. If you won’t/can’t use it, don’t ask it. Jan 13, 2011IAT 33462

63 5. Focus Groups  Structured Interview with groups of individuals –3 to 10 persons –Use several different groups with different roles or perspectives –Manage the interaction Avoid few people dominating the discussion  Focus on preferences and views, not performance  Relatively low cost, quick way to learn a lot  Audio or video record, with permission Jan 13, 2011IAT 33463

64 6. Competitive Products  Looking for both good and bad ideas –Functionality –UI style  Why are they successful or unsuccessful?  What does successful really mean? –(Note: Successful does not equal usable) Jan 13, 2011IAT 33464

65 7. Document Mining  Documentation –Often contains description of how the tasks should be done –Standards docs –Manuals –Histories –Best Practices Jan 13, 2011IAT 33465

66 8. Data Logging  Automatically tracking: –Keystroke/mouse clicks –Timers –Logs of transactions –Physical location/movement trackers Cell phones GPS Jan 13, 2011IAT 33466

67 Now that you have observed…  You have piles of notes, hours of video, surveys up to here…  How can you digest and represent the data, to turn it into information? Jan 13, 2011IAT 33467

68 Describe Tasks 1. Task Outlines 2. Narratives 3. Hierarchies & Network Diagrams –Hierarchical Task Analysis (HTA) –Entity-Relationship Diagrams 4. Flow Charts 5. Card Sorting Jan 13, 2011IAT 33468

69 1. Task Outline Using a lawnmower to cut grass Step 1. Examine lawn a.Make sure grass is dry b.Look for objects laying in the grass Step 2. Inspect lawnmower a.Check components for tightness 1)Check that grass bag handle is securely fastened to the grass bag support 2)Make sure grass bag connector is securely fastened to bag adaptor 3)Make sure that deck cover is in place 4)Check for any loose parts (such as oil caps) 5)Check to make sure blade is attached securely b.Check engine oil level 1)Remove oil fill cap and dipstick 2)Wipe dipstick 3)Replace dipstick completely in lawnmower 4)Remove dipstick 5)Check that oil is past the level line on dipstick Jan 13, 2011IAT 33469

70 2. Narratives  Describe tasks in sentences  Often expanded version of task outline  More effective for communicating general idea of task  Not effective for details  Not effective for branching tasks  Not effective for parallel tasks Jan 13, 2011IAT 33470

71 3. Hierarchies & Networks  Hierarchical Task Analysis (HTA) –Graphical notation & decomposition of tasks –Tasks as sets of actions –Tasks organized into plans (describes sequence)  Network / Entity-Relationship Diagrams –Objects/people with links to related objects –Links described functionally and in terms of strength Jan 13, 2011IAT 33471

72 4. Flow Charts  Flow Chart of Task Steps –Combines Entity-relationship (network) with sequential flow, branching, parallel tasks. –Includes actions, decisions, logic, by all elements of the system –Abstracted –Mature, well-known, good tools Jan 13, 2011IAT 33472

73 Jan 13, 2011IAT 33473 5. Knowledge-based Analysis  List all objects and actions involved in a task, then build a taxonomy of them  Often times, work with domain expert to get help

74 Summary: Data Gathering Techniques 1. Observation 2. Interviews & Contextual Inquiry 3. Ethnography also… 4. Surveys & Questionnaires 5. Focus Groups & Expert Debriefing 6. Competitive Product Review 7. Documentation mining 8. Data logging Jan 13, 2011IAT 33474

75 Summary: Describe Tasks 1. Task Outlines 2. Narratives 3. Hierarchies & Network Diagrams –Hierarchical Task Analysis (HTA) –Entity-Relationship Diagrams 4. Flow Charts 5. Card Sorting Jan 13, 2011IAT 33475

76 Jan 20, 2011IAT 33476 UI Design Principles  Categories –Learnability support for learning for users of all levels –Flexibility support for multiple ways of doing tasks –Robustness support for recovery  Always think about exceptions, suitability

77 Jan 20, 2011IAT 33477 Learnability Principles  Predictability  Synthesizability  Familiarity  Generalizability  Consistency

78 Jan 20, 2011IAT 33478 Predictability  I think that this action will do…  Operation visibility - can see avail actions –e.g. menus vs. command shell –grayed menu items

79 Jan 20, 2011IAT 33479 Synthesizability  From the resulting system state, My previous action did… –compare in command prompt vs UI –same feedback needed for all users, all apps?

80 Jan 20, 2011IAT 33480 Familiarity  Does UI task relate real-world task or domain knowledge? –to anything user is familiar with? –Use of metaphors pitfalls –Are there limitations on familiarity?

81 Jan 20, 2011IAT 33481 Generalizability  Does knowledge of one UI apply to others? –Cut and paste in many apps  Does knowledge of one aspect of a UI apply to rest of the UI? –File browsers in MacOS/ Windows  Aid: UI Developers guidelines

82 Jan 20, 2011IAT 33482 Consistency  Similar ways of doing tasks –interacting –output –screen layout  Is this always desirable for all systems, all users?

83 Jan 20, 2011IAT 33483 Flexibility Principles  Dialog Initiative  Multithreading  Task migratibility  Substitutivity  Customizability

84 Jan 20, 2011IAT 33484 Dialog Initiative  System pre-emptive –system does all prompts, user responds sometimes necessary Eg. Bank machine  User pre-emptive –user initiates actions more flexible

85 Jan 20, 2011IAT 33485 Multithreading  Two types –Concurrent input to multiple tasks simultaneously –Interleaved many tasks, but input to one task at a time

86 Jan 20, 2011IAT 33486 Task migratability  Ability to move performance of task to entity (machine or person) that can do it better –Eg. Autopilot –Spellchecking –When is this good? Bad?

87 Jan 20, 2011IAT 33487 Substitutivity  Flexibility in details of operations –Allow user to choose suitable interaction methods –Allow different ways to perform actions specify data configure –Allow different ways of presenting output to suit task, user

88 Jan 20, 2011IAT 33488 Customizability  Ability to modify interface –By user - adaptability –By system - adaptivity

89 Jan 20, 2011IAT 33489 Robustness Principles  Observability  Recoverability  Responsiveness  Task Conformance

90 Jan 20, 2011IAT 33490 Observability  Can user determine internal state of system from observable state? –Browsability explore current state (without changing it) –Reachability navigate through observable states –Persistence how long does observable state persist?

91 Jan 20, 2011IAT 33491 Recoverability  Ability to continue to a goal after recognizing error Difficulty of Recovery procedure should relate to difficulty of original task –Forward Recoverability ability to fix when we can’t undo? –Backward Recoverability undo previous error(s)

92 Jan 20, 2011IAT 33492 Responsiveness  Rate of communication between user and system –Response time time for system to respond in some way to user action(s) –Stability principle response time, rate should be consistent –As computers have gotten better, required computer response has gotten shorter

93 Jan 20, 2011IAT 33493 Task Conformance  Task coverage –can system do all tasks of interest?  Task adequacy –Can user do tasks? –Does system match real-world tasks?

94 Feb 3, 2011IAT 33494 IAT 334 Interface Design User Centered Design Metaphor Models Practice ______________________________________________________________________________________ SCHOOL OF INTERACTIVE ARTS + TECHNOLOGY [SIAT] | WWW.SIAT.SFU.CA

95 Feb 3, 2011IAT 33495 Agenda  User Centered Design -- Overall Process  Design –Metaphors –Mental Models –Idea generation  Design principles  Displaying your designs –Storyboards –Lo-Fi –Wizard of Oz –Visual Basic, Flash, etc

96 Feb 3, 2011IAT 33496 User-Centered Design  User-centered design process –Analysis of user needs –Prototype –Informal feedback –Iterate on design –Final application –Formal feedback

97 Feb 3, 2011IAT 33497 Analysis of User Needs  Techniques: –Surveys –Card-sorting tasks –Interviews –Focus groups Look at competing products –Ethnography Participant observation

98 Feb 3, 2011IAT 33498 Prototyping  Storyboards  Paper simulations of application  Wizard of Oz experiment  Prototyping tools  Cheap!

99 Feb 3, 2011IAT 33499 Informal Feedback  Present prototype to users  Do a quick questionnaire  Observe the user struggle with your lousy design

100 Feb 3, 2011IAT 334100 Iterate on Design  Redesign system –in light of initial user impressions –pay attention to common complaints  Be prepared to abandon bad ideas!!  It’s just an idea, not a measure of your worth!

101 Feb 3, 2011IAT 334101 Idea Creation  Ideas come from –Imagination –Analogy –Observation of current practice –Observation of current systems  Borrow from other fields –Animation –Theatre –Information displays –Architecture –... How do we create and develop new interface ideas and designs?

102 Feb 3, 2011IAT 334102 Interface Metaphors  Metaphor - Application of name or descriptive term to another object which is not literally applicable –Use: Natural transfer - apply existing knowledge to new, abstract tasks –Problem: May introduce incorrect mental model

103 Feb 3, 2011IAT 334103 Mental Models  What models of the world are the users using?  Two Classes:  Functional model –“Press the accelerator once, then turn the key”  Structural model –OK, why do we do that?

104 Feb 3, 2011IAT 334104 Another example...  Functional model –“Go north on King George, Cross the Pattullo, Turn left at 10 th Ave, Turn right at Kingsway, go 4.5km”  Structural model –What location??

105 Feb 3, 2011IAT 334105 Idea Creation  Methods for creating and developing interface ideas –Turn off your natural critique mechanism! –?

106 Feb 3, 2011IAT 334106 Idea Creation Methods  1. Consider new use for object  2. Adapt object to be like something else  3. Modify object for a new purpose

107 Feb 3, 2011IAT 334107 Idea Creation Methods  4. Magnify - add to object  5. Minimize - subtract from object  6. Substitute something similar

108 Feb 3, 2011IAT 334108 Idea Creation Methods  7. Rearrange aspects of object  8. Change the point of view  9. Combine data into an ensemble

109 Feb 3, 2011IAT 334109 Guidelines for Design  1. Provide a good conceptual model –User has mental model of how things work –Build design that allows user to predict effects of actions  2. Make things visible –Visible affordances, mappings, constraints –Remind person of what can be done and how to do it

110 Feb 3, 2011IAT 334110 Design Principles  1. Use simple and natural dialog in user’s language –Match user’s task in a natural way –Avoid jargon, techno-speak –Present exactly info that user needs Less is more!

111 Feb 3, 2011IAT 334111 Design Principles  Here are 10 more detailed principles to follow about what to design and why

112 Feb 3, 2011IAT 334112 Design Principles  2. Strive for consistency –Sequences, actions, commands, layout, terminology –Makes more predictable –Dialog boxes all having same “closure” options

113 Feb 3, 2011IAT 334113 Design Principles  3. Provide informative feedback –Continuously inform user about what is occurring –Most important on frequent, substantive actions % in file –How to deal with delays? Special cursors % Done graphs

114 Feb 3, 2011IAT 334114 Design Principles  4. Minimize user’s memory load –Recognition is better than recall Make visible! –Describe required input format, include example and default Date: _ _ - _ _ - _ _ (DD-MM-YY) –Use small # of generally applicable cmds

115 Feb 3, 2011IAT 334115 Design Principles  5. Permit easy reversal of actions –Undo! –Reduces anxiety, encourages experimentation

116 Feb 3, 2011IAT 334116 Design Principles  6. Provide clearly marked exits –Don’t want the user to feel trapped –Examples Cancel button on dialogs Quit any time Interrupt/resume on lengthy operations

117 Feb 3, 2011IAT 334117 Design Principles  7. Provide shortcuts –Enable frequent users to perform often-used operations quickly Keyboard & mouse –Abbreviations –Menu shortcuts –Function keys –Command completion –Double click vs. menu selection Navigation between windows/forms Reuse –Provide a history system

118 Feb 3, 2011IAT 334118 Design Principles  8. Support internal locus of control –Put user in charge, not computer –Can be major source of anxiety

119 Feb 3, 2011IAT 334119 Design Principles  9. Handle errors smoothly and positively –“That Filename already exists” vs. –“Rename failed”  10. Provide useful help and documentation

120 Dialog Design Categories of Dialogs

121 Feb 10, 2011IAT 334121 Agenda  Dialog design –Command Language –WIMP - Window, Icon, Menu, Pointer –Direct manipulation –Speech/Natural language –Gesture, pen, multi-touch, VR…

122 Feb 10, 2011IAT 334122 Command Languages  Earliest UI interaction paradigms  Examples –MS-DOS shell –UNIX shell

123 Feb 10, 2011IAT 334123 CL Attributes  Work primarily by recall, not recognition  Heavy memory load  Little or nothing is visible so…  Poor choice for novices but...

124 Feb 10, 2011IAT 334124 CL Attributes  Specify commands to operate on current data collection  User only controls initiation  Single thread of control  Some other display area needed

125 Feb 10, 2011IAT 334125 CL Design Goals  Consistency –Syntax, order  Good naming and abbreviations  Doing your homework in design can help alleviate some of the negatives

126 Feb 10, 2011IAT 334126 Consistency  Provide a consistent syntax –In general: Have options and arguments expressed the same way everywhere –UNIX fails here because commands were developed by lots of different people at different organizations No guidelines provided

127 Feb 10, 2011IAT 334127 Dialog Order  English: SVO subject verb object  CL: S assumed (you) Is VO or OV better? % rm file % file rm  V dO iO vs. V iO dO % print file thePrinter % lpr -PthePrinter file

128 Dialog Order  Technical issues dictate the choice:  V iO dO % lpr -PthePrinter file  The command must parse the arguments –So the command comes first  Flags control how to act on the file –Want to parse all flags before checking files –e.g. -o outputFile Feb 10, 2011IAT 334128

129 Feb 10, 2011IAT 334129 Syntax  Pick a consistent syntax strategy –Simple command list eg., vi minimize keystrokes –Commands plus arguments realistic, can provide keyword parameters % cp from=foo to=bar –Commands plus options plus arguments what you usually see

130 Feb 10, 2011IAT 334130 Terminology  Keep terminology consistent –Same concept expressed with same options –Useful to provide symmetric (congruent) pairings forward/backward next/prev control/meta

131 Feb 10, 2011IAT 334131 WIMP  Focus: Menus, Buttons, Forms  Predominant interface paradigm now (with some direct manipulation added)  Advantages: –?

132 Recognition  Recognition is easier than recall! –Recall has one cue –Recognition has the recall cue + the presence of the prompting word/icon Feb 10, 2011IAT 334132

133 Feb 10, 2011IAT 334133 Menus  Key advantages: –1 keystroke or mouse operation vs. many –No memorization of commands –Limited input set

134 Feb 10, 2011IAT 334134 Menus  Many different types –pop-up –pull-down –radio buttons –pie buttons –hierarchies

135 Feb 10, 2011IAT 334135 Menu Items  Organization strategies –Create groups of logically similar items –Cover all possibilities –Ensure that items are non-overlapping –Keep wording concise, understandable

136 Feb 10, 2011IAT 334136 Presentation Sequence  Use natural if available –Time e.g. Breakfast, Lunch, Dinner –Numeric ordering e.g. Point sizes for font –Size Canada-> BC -> Surrey

137 Feb 10, 2011IAT 334137 Presentation Sequence  Choices –Alphabetical –Group related items –Frequently used first –Most important first –Conventional order (MTWRF)  Don’t change the order on the fly!

138 Feb 10, 2011IAT 334138 Direct Manipulation  Continuous visibility of the objects and actions of interest  Rapid, incremental actions  Reversibility of all actions to encourage experimentation  Syntactic correctness of all actions—every action is syntactically legal  Replacement of command language syntax by direct manipulation of object of interest

139 Feb 10, 2011IAT 334139 Direct Manipulation  Examples –WYSIWYG editors and word processors –VISICALC - 1 st electronic spreadsheet –CAD –Desktop metaphor –Video games

140 DM Syntax  Typical DM syntax is postfix  DirectObjects first, Verb second –In this case, the command completes the utterance  Enables separate selection syntax  Indirect objects typically specified before direct objects –e.g. brush size before painting in Photoshop Feb 10, 2011IAT 334140

141 Feb 10, 2011IAT 334141 DM Essence  Representation of reality that can be manipulated  The user is able to apply intellect directly to the task  Don’t have to name things, just touch them  The tool itself seems to disappear

142 Direct Manipulation is Locality  DM Relies on a primary geometric organization  Items located nearby are frequently edited together –The words in a sentence –A column of numbers in a spreadsheet  Less related -> Less local -> Less DM! Feb 10, 2011IAT 334142

143 User Modeling Predicting thoughts and actions GOMS

144 Feb 24, 2011IAT 334144 Agenda  User modeling –Fitt’s Law –GOMS

145 Feb 24, 2011IAT 334145 User Modeling  Idea: If we can build a model of how a user works, then we can predict how s/he will interact with the interface –Predictive modeling  Many different modeling techniques exist

146 User Modeling – 2 types  Stimulus-Response –Hick’s law –Practice law –Fitt’s law  Cognitive – human as interperter/predictor – based on Model Human Processor (MHP) –Key-stroke Level Model Low-level, simple –GOMS (and similar) Models Higher-level (Goals, Operations, Methods, Selections) Not discussed here Feb 24, 2011IAT 334146

147 Power Law of Practice  T n = T 1 n -a –T n to complete the nth trial is T 1 on the first trial times n to the power -a; a is about.4, between.2 and.6 –Skilled behavior - Stimulus-Response and routine cognitive actions Typing speed improvement Learning to use mouse Pushing buttons in response to stimuli NOT learning Feb 24, 2011IAT 334147

148 Hick’s Law  Decision time to choose among n equally likely alternatives –T = I c log 2 (n+1) –I c ~ 150 msec Feb 24, 2011IAT 334148

149 Fitts’ Law  Models movement times for selection (reaching) tasks in one dimension  Basic idea: Movement time for a selection task –Increases as distance to target increases –Decreases as size of target increases Feb 24, 2011IAT 334149

150 Fitts: Index of Difficulty  ID - Index of difficulty  ID is an information theoretic quantity –Based on work of Shannon – larger target => more information (less uncertainty) Feb 24, 2011IAT 334150 ID = log 2 (d/w + 1.0) bits result width (tolerance) of target distance to move

151 Design implications  Menu item size  Icon size  Put frequenlty used icons together  Scroll bar target size and placement –Up / down scroll arrows together or at top and bottom of scroll bar Feb 24, 2011IAT 334151

152 Feb 24, 2011IAT 334152 GOMS  One of the most widely known  Assumptions –Know sequence of operations for a task –Expert will be carrying them out  Goals, Operators, Methods, Selection Rules

153 Feb 24, 2011IAT 334153 GOMS Procedure  Walk through sequence of steps  Assign each an approximate time duration -> Know overall performance time  (Can be tedious)

154 Feb 24, 2011IAT 334154 Limitations  GOMS is not for –Tasks where steps are not well understood –Inexperienced users  Why?  Good example: Move a sentence in a document to previous paragraph

155 Feb 24, 2011IAT 334155 Goal  End state trying to achieve  Then decompose into subgoals Moved sentence Select sentence Cut sentence Paste sentence Move to new spot Place it

156 Feb 24, 2011IAT 334156 Operators  Basic actions available for performing a task (lowest level actions)  Examples: move mouse pointer, drag, press key, read dialog box, …

157 Feb 24, 2011IAT 334157 Methods  Sequence of operators (procedures) for accomplishing a goal (may be multiple)  Example: Select sentence –Move mouse pointer to first word –Depress button –Drag to last word –Release

158 Feb 24, 2011IAT 334158 Selection Rules  Invoked when there is a choice of a method  Example: Could cut sentence either by menu pulldown or by ctrl-x

159 Feb 24, 2011IAT 334159 Further Analysis  GOMS is often combined with a keystroke level analysis –Assigns times to different operators –Plus: Rules for adding M’s (mental preparations) in certain spots

160 Feb 24, 2011IAT 334160 Example 1. Select sentence Reach for mouseH0.40 Point to first wordP1.10 Click button downK0.60 Drag to last wordP1.20 ReleaseK0.60 3.90 secs 2. Cut sentence Press, hold ^Point to menu Press and release ‘x’orPress and hold mouse Release ^Move to “cut” Release 3.... Move Sentence

161 Keystroke-Level Model  Simplified GOMS  KSLM - developed by Card, Moran & Newell, see their book –The Psychology of Human-Computer Interaction, Card, Moran and Newell, Erlbaum, 1983  Skilled users performing routine tasks  Assigns times to basic human operations - experimentally verified  Based on MHP - Model Human Processor Feb 24, 2011IAT 334161

162 Feb 24, 2011IAT 334162 User Profiles  Attributes: –attitude, motivation, reading level, typing skill, education, system experience, task experience, computer literacy, frequency of use, training, color-blindness, handedness, gender,…  Novice, intermediate, expert

163 Feb 24, 2011IAT 334163 Motivation  User –Low motivation, discretionary use –Low motivation, mandatory –High motivation, due to fear –High motivation, due to interest  Design goal –Ease of learning –Control, power –Ease of learning, robustness, control –Power, ease of use

164 Feb 24, 2011IAT 334164 Knowledge & Experience  Experience  tasksystem –lowlow –highhigh –lowhigh –highlow  Design goals –Many syntactic and semantic prompts –Efficient commands, concise syntax –Semantic help facilities –Lots of syntactic prompting

165 Feb 24, 2011IAT 334165 Job & Task Implications  Frequency of use –High - Ease of use –Low - Ease of learning & remembering  Task implications –High - Ease of use –Low - Ease of learning  System use –Mandatory - Ease of using –Discretionary - Ease of learning

166 Feb 24, 2011IAT 334166 Modeling Problems  1. Terminology - example –High frequency use experts - cmd language –Infrequent novices - menus  What’s “frequent”, “novice”?

167 Feb 24, 2011IAT 334167 Modeling Problems (contd.)  2. Dependent on “grain of analysis” employed –Can break down getting a cup of coffee into 7, 20, or 50 tasks –That affects number of rules and their types

168 Feb 24, 2011IAT 334168 Modeling Problems (contd.)  3. Does not involve user per se –Don’t inform designer of what user wants  4. Time-consuming and lengthy

Download ppt "May 18, 2010IAT 3341 IAT 334 Interface Design Chris Shaw ______________________________________________________________________________________ SCHOOL."

Similar presentations

Ads by Google