Special thanks to hd mabuse and all the CESAR Team.

1. EduardoOliveira
www.eduoliveira.com
eduardo.oliveira@unimelb.edu.au
talkingabout
HCDprocess@UniMelb

2. What is Usability?

3. You arrive at the hotel and the receptionist gives you the
key to the apartment 755.Which button you press?

11. BASIC UI RULES01
240 x 320 44 x 44
240 x 400 50 x 50
480 x 800 96 x 96
Icon Shadow Recommendations
Icon Size Guide by Resolution (shadow included)
The tray icon can be designed freely within the defined size constraints.
Minimum Touch Area : 35 x 35 pixels
Photoshop effect //
35
35
Clickable elements must be designed to secure at least the minimum touch area in order to be clicked.
1-5. COMMON GUIDE
1-5-3. Tray Icon, Depth 1 Widget Guide
Tray icon guide

12. Product Design
!
AND
!
CITY/URBAN/SPACES Design

13. 1010
Play Street Detour New York City ca. 1916-1920.
Image Credit: New York City Municipal Archives

14. REMIX YOUR STREET: STRATEGIES
15
Parklets promote a low-cost, easily implementable approach to
public space improvement through projects that energize and
reinvent the public realm. They help address the desire and need
for increased public open space and wider sidewalks.
San Francisco Pavement to Parks Website
2
3
1. Mobile Parklet, San Francisco, CA. Credit: CMG Landscape Architects
2. Devil’s Tooth Parklet, San Francisco, CA. Image Credit: Jordan Lewis
3. Hot Tub Parklet, Vancouver, BC. Image Credit: Paul Krueger
4. Mission Hill Parklet, Boston, MA. Image Credit: Courtney Sacco
4

15. 7
. . . PEOPLE CAN PLAY
IN THE STREETS?
. . . PEOPLE AND
THE ENVIRONMENT
ARE HEALTHIER?
Image Credits:
1. Paul Krueger
2. Chris Gahl/Visit Indy
3. Donald Gunn
4. Portland State University

16. REMIX YOUR STREET: STRATEGIES
21
Open streets initiatives temporarily close streets to automobile traffic,
so that people may use them for walking, bicycling, dancing, playing,
and socializing.
Openstreetproject.org
1. Alki Ave Summer Street Event,
Seattle, WA. Image Credit: Patrick
Robinson, West Seattle Herald
2. Beach Street Party, North
Adams, MA. Image Credit: Gillian
Jones/North Adams Transcript
3. Phinney Ridge, Summer Street,
Seattle, WA. Image Credit: SDOT2 3

17. REMIX YOUR STREET: STRATEGIES
35
1. Madison Square Plaza, New York, NY. Credit: NYCDOT
2-3. Before and After, Pearl Street Triangle, Brooklyn, NY.
Credit: NYCDOT
A 2012 New York City Department of Transportation study found that
retail sales increased by 172% after a parking triangle on Pearl Street
in Brooklyn was converted into a pedestrian plaza.
Gehl Architects Website
2 3

18. IBMVideo

19. Usability is a quality attribute that assesses how easy
user interfaces are to use.The word "usability" also
refers to methods for improving ease-of-use during the
design process.
!
Jakob Nielsen, 2003.

20. Usability is defined by 5 quality components:
!
Learnability: How easy is it for users to accomplish basic
tasks the first time they encounter the design?
Efficiency: Once users have learned the design, how
quickly can they perform tasks?
Memorability:When users return to the design after a
period of not using it, how easily can they reestablish
proficiency?
Errors: How many errors do users make, how severe are
these errors, and how easily can they recover from the
errors?
Satisfaction: How pleasant is it to use the design?

21. A key one is utility, which refers to the design's
functionality: Does it do what users need?

22. User Centred Design (UCD)

23. [UCD video]

24. [TokyoVideo]
[Connecting]
[LasVegas Experience]

25. [Why The Best CEO's Invest in Customer Experience]

26. "We are not actually experts in specific areas.We are
experts in the process of how things are designed”.
Tom Kelley

27. [video]

28. What are we going to do?

29. We will have fun with
HCD process. We will
try to DESIGN
Melbourne CBD
GROUND based on
pedestrians experience!

30. phase 1
[without process]

31. small activity
!
UniMelb
!
partial process

32. Task 1 – Mapping the campus: Each pair of
students should explore and design routes in
The University of Melbourne based on
provided start and end points and based on
their own experiences and needs.

34. phase 2
[with process]

35. big activity
!
Melbourne CBD
!
full process

36. Task 2 – Designing Melbourne CBD
GROUND: Each group of students (teams of
four) should DEFINE and DESIGN Melbourne
CBD GROUND based on pedestrians
movement/experience/walkability/…

37. UX Researchers 2 profiles Urban Designers
user research
user requirements
ideation
prototyping
(wireframes)
user tests
!
ui research
ui conception
ideation
prototyping
(mock-ups)
ui [3d models]
students will work as both profiles in Task 2

38. Studies(and(
Research( Idea0on(
Evalua0on( Prototyping(
1( 2(
3(4(
USER>CENTERED(DESIGN(
innovation
process
[overview]

39. 1"
]"
Iden(fy"users"and"inves(gates"
how"the"product"can"be"used"
and"in"which"circumstances."
Studies"and"Research"

40. 2"
Problems"and"opportuni2es"
iden2fied"by"research"inspires"
solu2ons,"which"is"the"goal"of"
this"phase."
Idea2on"

41. 3"
By"building"prototypes"it"is"
possible"to"iden2fy"limits"and"
restric2ons"as"well"as"the"poten2al"
of"the"generated"solu2ons."
Prototyping"

42. 4"
The"last"step"is"a"valida.on"(in"the"
lab"or"in"the"field)"of"the"prototyped"
concepts"with"the"users."
Evalua.on"

43. some [REAL] cases

44. smartphones
!
Samsung Smart Apps [desktop]

45. car + mobile devices

47. health

49. taximov

50. tv interface
!
television menu redesign

52. ux + big data

53. big data
field
research

54. big data
field
research

55. massive volume of
data
deep dive into questions
big data
field
research

56. massive volume of
data
deep dive into questions
What? Why?
big data
field
research

57. massive volume of
data
deep dive into questions
What? Why?
big data
field
research
Find

58. massive volume of
data
deep dive into questions
What? Why?
big data
field
research
Find
Investigate

59. massive volume of
data
deep dive into questions
What? Why?
big data
field
research
Understand
Investigate
Find

60. massive volume of
data
deep dive into questions
What? Why?
big data
field
research
Understand
Investigate
Find

61. How we do this?
Collect Data
Represent Data Interpret Data

63. How can we… DESIGNMELBOURNE
CBD GROUNDbased on PEDESTRIANS
EXPERIENCE [movement/mobility/needs]?

64. Because we are designing for
people…
!
5 MENTs [at least] are needed!

65. 1 =MENT

66. DiscontentMENT

67. 5 =MENT

68. EngageMENT
EmpowerMENT
TreatMENT
CommitMENT
MoveMENT

69. +1?

70. InvolveMENT
I Love Melbourne

71. !
CITIZENS as active
participants
in the [creative] process

72. Empowerment
("more upload and less download", Claudio Marinho)

73. RESEARCH Phase

74. Research comprises "creative work undertaken on a systematic basis in order to
increase the stock of knowledge, including knowledge of man, culture and society,
and the use of this stock of knowledge to devise new applications."(Wikipedia)

76. • Quantitative research
• Designed to generate accurate and reliable measures that
allow statistical analysis
• Appropriate to measure both opinions, attitudes, behaviors
and preferences
• Ex: elections: quantify the preference of the electorate
• Qualitative research
• Has no statistical basis
• Analyzes profoundly non-measurable data - feelings,
sensations, perceptions, thoughts, intentions, past behavior,
understanding reasons, meanings and motivations - from a
certain group of individuals in relation to a specific problem.
• Involves the development and refinement of new ideas.
• Extract reasoning, new discoveries, ideas and interpretations
Qualitative vs Quantitative

77. Qualitative vs Quantitative
!
!
Example: Election
Theory: Based on the history of elections in Melbourne
Hypothesis: If Elena's President popularity in Melbourne is large, then the
chance of the mayor’s with the same political side be elected is great
Public Target: the voting population in various parts of the city
Data collection: objective questions "Which candidate Mr/Miss vote for?"
!
Fragmentation of complex relationships in different variables allow the
researcher to isolate and test other effects.
And if leaving Elena’s politics side, who wins?
Interpretation of the data
Quantitative research

78. !
!
Are generally open
Originate in the context of the researcher
Style and interest also influence
Can describe states or processes
Assumptions can be confirmed or discovered
Qualitative research - Questions
Qualitative vs Quantitative

79. Formulating Questions
!
Selecting Plans and Methods
!
Data Collection
!
Evaluating and Reformulating Questions
!
Data Analysis
!
Formulation of Findings
Research Process

80. Focusing on what we want to know
!
Simple, clear and concise sentences (enable proper
interpretation)
Neutral issues (not induce a response)
Positive affirmations (avoid reverse logic)
Maintain focus (on compound questions)
Guide to possible content extraction
Caution and common sense!
Research Questions

81. How to access information?
[video]

82. Research Dynamic
!
[AQUARIUM]
[max 15’]
!
[two interviewees/volunteers]
Main Objective: find out about the culture/food/
behaviour and the country of the interviewee

83. Research Dynamic
!
[Brainstorm]
[time: 8’]
!
[What questions can you do to discover/identify what
is GROUND for Melbourne CBD pedestrians?]

84. Research Dynamic
!
[Define your Research Method (in teams)]
[max 20’]

85. Data Analysis

86. 1. Recording of Data
!
2. Data Edition (Transcript - great accuracy means
large absorption of energy and time)
codes: [text],TEXT, (1.8), (.), >text<, <text>,
@@@, XXXX,…
!
3. Construction of the "new" reality
Data Analysis

87. Data Analysis

88. Open Codification
!
Methods of coding
!
Line by line
Sentence by sentence
Paragraph by paragraph
Data Analysis

89. FULL EXAMPLE - Part 1
!
Interviewees Profile
!
Bob Marley, 37 years old
Computer Science student, single, loves music and soccer. Everyday
uses Tram to go to UniMelb. Likes CBD to have some food and to
meet up with friends.
- 25 pages of transcription
John Lennon, 42 years old
Bank manager, full schedule of meetings and passionate for
technologies. Is always in CBD because works on there. Everyday
Lennon have lunch on CBD, …
- 13 pages of transcription
Data Analysis

90. FULL EXAMPLE - Part 2
!
Categorising discovered codes
!
Routine
Describes activities related to the routine of interviewee
Use of Smartphones
Describes activities related to the use of smartphones
Use of Computer
Describes the activities related to computer use
Personal Costs
Relative to spending on goods and services
Games
Concerning electronic games comments
Data Analysis

91. FULL EXAMPLE - Part 2
!
Categorising discovered codes
!
EXAMPLE:
!
Subcategory Code References
Workout Every day I go to Gym at night 4
I love running 2
Entertainment I am always listening to musics 1
Interacting with smart phone 6
Childrens watch DVD in the car 1
Routine
Data Analysis

92. FULL EXAMPLE - Part 2
!
Categorising discovered codes
!
EXAMPLE:
!
Use of Smartphones
Subcategory Code References
Messages Sending messages to girlfriend 1
Using Whatsapp app to send message 5
Sends / receives messages via cell phone during work
meetings
3
Calls Uses different resources (Bluetooth / USB cable) to
receive calls in the car while driving
1
Audio / Video ... 1
... 1
... 1
... 3
... 3
... 2
... 1
Data Analysis

93. MSD IntrinsicGround/Studio Docs/HCD/IDEO_HCD_ToolKit.pdf

94. Task 2 – Designing Melbourne CBD GROUND:
Each group of students (teams of four) should
DEFINE and DESIGN Melbourne CBD GROUND
based on pedestrians movement/experience/
walkability/…
!
1. Map your route between provided Start and End
point
1.1 Try to identify, while mapping, people/lanes/
streets/ indoor and outdoor spaces/grounds/
shortcuts on your path
2. Apply your research methods with citizens on your
path
2.1 Apply in different location, with different
people. Try to identify the way people use
Melbourne CBD Ground.
3. OUTPUT: Present your mapped route together
with your research analysis (interviewees profile,
places, codes and categories from your research
data). Prepare your data to be presented next class
in 10 minutes. This will be used as INPUT for
IDEATION phase.
*** REMEMBER: our objective is to DESIGN Melbourne CBD GROUND ***

95. 1 1
legend'
Start'point' End'point'
1
1
2
2
3
3
4
4
Time: 30 mins to map the route + 1h-2h collecting data

96. EduardoOliveira
www.eduoliveira.com
eduardo.oliveira@unimelb.edu.au
talkingabout
HCDprocess@UniMelb