Presentación para Diplomado de Arquitectura de información y experiencia de usuarios.

1. Nuevas tendencias UX #daiux2016

2. agenda.
IOT
Proyecciones e interacciones
Data Driven
Apps
Casos

3. IOT Internet of Things

4. “El internet de las cosas (IOT) es una red global
de computadores, sensores y actuadores
conectados a través de protocolos de internet”
Pfister-

5. ¿Qué es internet de las cosas y qué no?

7. Desafíos de la UX para IOT

8. UX en el servicio
*Spotify

9. Tangibilidad

14. 6.4 Billion devices = 6.4 Billion on interfaces
¿Quién las va a diseñar?

18. ¿Diseño industrial otra vez?

20. Proyecciones e interacciones Video + interacción

27. Estamos transformando a las audiencias en
tatuadores, Directores de Tv y operadores logísticos?

29. Data Driven Análisis y ejecución

32. Video

33. Apps Still alive?

36. E-Commerce Day 2016 Chile
“La visión no fue
mobile first,
fue Mobile ONLY”
www.simple.ripley.cl

37. ¿Cuáles Apps usamos hoy?

38. Hacen muy pocas cosas, pero muy bien

46. Casos Now is for real

48. Intro
On my way to work, I saw an interesting
ad for a concert.
Snapped a picture of it to remind myself,
which I forgot (obviously).
Got a rude reminder of the event when I
saw pictures of that concert the day
after on Facebook :(
What a bummer!
Extending your
default photo cloud
to turn photos into
calendar events,
naturally expanding
current user
behaviours.
OURVISION

49. The hack
Take a picture Sync
External
Cloud
Is an
actionable
photo?
No
Yes
Add to
calendar
Tesseract
Scan
Process to
text
Identify key
elements

50. Take a picture of a poster "Friday Jazz in Southbank Centre at 5:30 on June 10th" and the
event will be created on your calendar with the correct date and time.
Unique Selling Point
It is in your default camera app already,
not another icon on your desktop!
It runs automatically in the background.
Create powerful connections from images to reminders / alerts.
Other services
Default camera app on your phone
Google Calendar
Google Now
IFTTT

51. Social layer
Privacy, spurious events/alerts
Business layer
Analytics dashboard (with location data
it tells you which poster gets the most
exposure) Attendance forecasting
Next steps
Eventual.ly is a glue - IFTTT for events.
Eventual.ly is a framework for
event managers and developers.
Ultimate goalToday
“Eventually is an automated
solution for users, extracting
information from images”
Next steps
Future

54. Gustavo Soto Mino / PCP / MSc HCI+e

58. Use Your Words: Designing One-
time Pairing Codes to Improve
User Experience
Gustavo Soto Mino
@gusoto

59. PairingProcess
CODE
Device 01 Device 02
ACCESS
GRANTED
Device 01
Transcription Correct code
copy-and-confirm

60. MAIN
REQUEST
This request considered a few distinctive elements related
with the
INPUT CODE
send
Security of the process
Elements of the user
experience
Avoid collisions

61. Physical level Cognitive level Perceptual level Social level
Elements of the experience

62. Combinations
Condition Characters Example Composition Combinations
Digits 9 characters 874 325 023 Digits from 0 - 9 1,000,000,000
Words
3 words of three
letters
pin win dog 800 English words 512,000,000
Alphanumeric 5 characters Rt 4Ka
Letters from A-Z
(Uppercase and
lowercase) Minus
IOL,iol) + Digits
550,731,776

63. Experiment
SMARTPHONE [User´s smartphones]
DIGITSALPHANUMERICWORDS
LAPTOP
DIGITSALPHANUMERICWORDS

64. What was measured?
ENTRY SPEED ERRORS WORKLOAD MEMORABILITY PREFERENCES

65. RESULTS

66. Mean entry time for each condition by device
Timeinmilliseconds
80.0
107.5
135.0
162.5
190.0
Digits Alphanumeric Words
Laptop Smatphone
ENTRY
SPEED
The entry time in both devices
(smartphone and laptop) was the fastest
when using the words-condition.
Users are more efficient when typing
elements that they know or are somehow
familiar with (Salthouse, 1986).
Using one kind of character will improve the
memorability of the users, creating a more
efficient experience (Schraagen & van
Dongen, 2005)
EFFICIENCY

67. ERROR
RATE
Mean error rate for each condition by device
Errorpercentage
1.00
1.75
2.50
3.25
4.00
Digits Alphanumeric Words
Laptop Smatphone
Regarding the efficacy, the experiment
observed that the error rate between
conditions and devices was not significant
in statistical terms.
EFFICACY
According to Gallagher & Byrne’s model
(2007), the alphanumeric-condition would
present the largest amount of errors, due to the
added complexity of changing between
screens
It is possible to conclude that the use of mixed
characters (lowercase with uppercase or digits)
will impact not only in the time, but also in the
amount of errors of the users.

68. TLX
WORKLOAD
Digits on Laptop
Alphanum. on Laptop
Words on Laptop
Digits on Smartphone
Alphanum on Smartphone
Words on Smartphone
0.0 300.0 600.0 900.0 1200.0
Frustration Effort Performance
Mental Physical Temporal

69. TLX
WORKLOAD
NASA TLX frustration scores by condition
Frustrationscale
score
0.0
50.0
100.0
150.0
200.0
Digits Alphanumeric Words
Laptop Smartphone
NASA TLX Effort scores by condition
Effortscalescore
0.00
55.00
110.00
165.00
220.00
Digits Alphanumeric Words
Observing the global results of the data
from the TLX, there is a consistent
perception from the users that the words-
condition is the condition that requires the
least effort to use, and presents the lowest
levels of frustration in both devices. This
means that users feel less pressure and
feel less mentally challenged, creating a
simpler interaction with the codes.

70. MEMORABILITY
Median amount of glances to the screen
by condition
Nofglances
0.0
10.5
21.0
31.5
42.0
Digits Alphanumeric Words
The results show that in the words-
condition the users looked at the screen
1.33 times per code, while the
alphanumeric-condition presented 1.81
times per code and the digits-condition
2.02 times per code.

71. User preferences
0
5
10
15
20
Smartphone Laptop Pairing Process
Words Digits Alphanumeric
USERS
PREFERENCES
The users’ preference about the most easy
to use code was 85% in the words-
condition on Laptop and 80% in the words-
condition on Smartphone. When users were
asked about not only the ease, but also the
security factors, they selected the words-
condition above the others, but only in a
total of 75%.

72. The design recommendation for the implementation is to use a three-word
based passcode. The experiment showed consistent results in efficiency, user
preference and workload, and promising results in error rate and memorability.
3words