Einstein published his ideas and became a pivotal element in shifting the way we think about physics - from the Newtonian model to the Quantum - in turn this changed the way we think about the world and allowed us to develop new ways of engaging with the world. We are at a similar juncture. The development of computational technologies allows us to think about astronomical volumes of data and to make meaning of that data. The mindshift that occurs is that “the machine is our friend”. The computer, like all machines, extends our capabilities. As a consequence the types of thinking now required in industry are those that get away from thinking like a computer and shift towards creative engagement with possibilities. Logical thinking is still necessary but it starts to be driven by imagination. Computational thinking and data science change the way we think about defining and solving problems. The age of creativity - which increasingly extends its impact from arts applications to business, scientific, technological, entrepreneurship, political, and other contexts.

1. Creativity via Big
Datafrom Big Data to Computational Thinking to Creative Problem-solving
Kim Flintoff
Academic Engagement Developer
Curtin Teaching and Learning

2. I
acknowledge
the
Nyungar
Wadjuk
people
as
the
tradi8onal
owners
of
country
on
which
Cur8n’s
Bentley
campus
sits.
I
wish
to
acknowledge
their
con8nuing
connec8on
to
land,
sea
and
community
and
I
pay
my
respects
to
them
and
their
culture;
and
to
elders
past,
present
and
future.

3. Abstract
Einstein published his ideas and became a pivotal element in shifting the way we think about physics
- from the Newtonian model to the Quantum - in turn this changed the way we think about the world
and allowed us to develop new ways of engaging with the world.
We are at a similar juncture. The development of computational technologies allows us to think
about “astronomical” volumes of data and to make meaning of that data.
The mindshift that occurs is that “the machine is our friend”. The computer, like all machines,
extends our capabilities. As a consequence the types of thinking now required in industry are those
that get away from thinking like a computer and shift towards creative engagement with possibilities.
Logical thinking is still necessary but it starts to be driven by imagination.
Computational thinking and data science change the way we think about defining and solving
problems.
The age of creativity - which increasingly extends its impact from arts applications to business,
scientific, technological, entrepreneurship, political, and other contexts.
02
Einstein Schrödinger
Gödel Bohr
http://tiny.cc/data-kf
Square Kilometre Array / Murchison Widefield Array

4. Presentation Timeline
Making time for discussion
02.00
Cloud computing
05.00
Big Data
05.00
Internet of
Everything
07.00
Analytics and
Visualisation
5.00
Teaching and
Learning
05.00
Data
Management
15.00
Q & A
03

5. 04
Innovating learning for Curtin centres
upon building a highly media rich,
interactive and personalised learning
experience for all our learners. To
facilitate this, CTL are working on a
number of internationally leading
projects and programs.
History
Curtin Teaching and Learning
Strategic Innovations in Learning Engagement

6. 01
“ New technologies have resulted in
unprecedented global competition and
enabled learning to be delivered effectively
on a much larger scale. “
05
Our Challenge
Transforming Teaching and Learning
students have
unprecedented
choice
technology has
removed geographic
boundaries
employers expect
job ready leaders

7. 0106
Your presenter
Kim Flintoff
Mr. Kim Flintoff
@kimbowa
+KimFlintoff
facebook.com/kimbowa
Academic Engagement Developer
Strategic Innovations in Learning Engagement
Teacher, researcher, scholar
Current work focusses include games and
gamification in learning contexts, new platforms
for collaborative global learning, challenge-based
engagement, sustainability education, learning
by making, trasnmedia approaches to learning
engagement, microcredentialling and badging
approaches, computational learning, learning
analytics and other big data strategies in the
higher education sector.
k.flintoff@curtin.edu.au

8. 0107
What is “the cloud”
and where is it?
Mr. Kim Flintoff
@kimbowa
+KimFlintoff
facebook.com/kimbowa
In many ways, the cloud is everywhere.
“The cloud” is a metaphor for a seemingly
amorphorous network of computers.
The types of computers vary and have many
purposes - processing, storage, service delivery,
servers, etc.
The great benefit of “the cloud” is that it enables
you to access and store the tools and
information you need from anywhere in the
world that is connected.
For most of us “the cloud” is the internet.
k.flintoff@curtin.edu.au
The Beginners Guide to the Cloud - http://mashable.com/2013/08/26/what-is-the-cloud/

9. 0108
What is “data”
and where is it?
Is any collection of things that you intend to make
meaning from. It might come in the form of
numbers, words, pictures, stories, colours, sounds,
measurements, observations, descriptions.
Without context its has limited value or meaning.
Big data in many cases refers to the ability to create
this meaning from available data sources
Data can be structured, semi-structured or
unstructured.
Information - is data that has a known context, has
been processed in some way and can be applied to
some form of problem-solving or meaning-making.
k.flintoff@curtin.edu.au
What is Data - https://youtu.be/EMHP-q4GEDc

10. 0109
Types of data
Qualitative and quantitative
Qualitative and quantitative data - simple
distinction is things that can be expressed
in numbers (quantitative) and those that
are not (qualitative) - but qualitative data
can be expressed numerically and
quantitative data is based upon
qualitative judgements
Data can be structured, semi-structured
or unstructured.
Types of Data - http://www.socialresearchmethods.net/kb/datatype.php
Q. What quantitative
data could I generate
about this?
Q. What qualitative
data could I generate
about this?
Q. Can data tell me if I will enjoy it?
Time to serve, bacteria count, degree of similarity between item served and item advertised, verbal exchanges around the product, attention to detail….

11. 0110
Managing data
Security, databases, metadata
Types of Data - http://www.socialresearchmethods.net/kb/datatype.php
Database - a structured organisation of a
collection of data.
Metadata - labelling data to make it more
manageable (search terms, keywords,
descriptions, labels, categories, etc)
Data cleansing - ensuring the accuracy of
data

12. 0111
Big data
What is it, and where does it come from?
Photo credit: - https://flic.kr/p/da8jMn
Big data is a term normally used to
describe data collections that are so large
or so complex that they require computer
assisted analysis in order to present the
material in a human accessible form.
The term is being applied to the complex
process of collecting, managing, analysing,
representing and developing insights.
1. Portentous
2. Perverse
3. Personal
4. Productive
5. Partial
6. Practices
7. Predictive
8. Political
9. Provocative
10. Privacy
11. Polyvalent
12. Polymorphous
13. Playful
13 Ps of Big Data
13 “P”s of Big Data - https://simplysociology.wordpress.com/2015/05/11/the-thirteen-ps-of-big-data/
Portentous, Perverse, Personal, Productive, Partial, Practices, Predictive, Political, Provocative, Privacy, Polyvalent, Polymorphous, Playful
Deborah Lupton
5 “V”s of Big Data - http://www.ats.avnet.com/na/en-us/news/Pages/The-5-Vs-of-Big-Data.aspx
Volume, Velocity, Variety, Veracity, Value

13. 0112
Big data
How do we get it, what do we do with it.
Photo credit: - https://www.flickr.com/photos/keoni101/7069578953/in/photostream/ (Image by Keoni Cabral CC 2.0)
Estimates suggest that the vast majority of data is unstructured.
Human activity generates data.
Sources of human data - behaviour, answering questions, biological data, measurements,
wearable technology, online behaviour, interaction with devices, machines, etc. spending,
buying, games, etc…
Other types of data - anything we count, record, measure, etc
What examples can the group suggest?

14. 0113
Big data and business
Its happening now
Further reading: Secure Development of Internet of Things Products for Education
http://www.educause.edu/blogs/vvogel/secure-development-internet-things-products-education
Three main areas:
• decision making capabilities
• business intelligence - discovery and insights
• automation
and can be applied across many business functions:
• marketing
• market research
• design
• planning
• manufacturing
• invention
• research and development
• customer service
Ian Blevin referred to business intelligence, data and decision making over a 3 year cycle. Big data may drive shifts to even more adaptive and responsive
approaches… supply chain, demand, etc.
Businesses will increasingly have access to open data repositories. Business solutions will be subject to Creative Commons licensing.
http://pennystocks.la/internet-in-real-time/

15. 0114
Big data and business
Its happening now
Source: The Internet in Real-Time - http://pennystocks.la/internet-in-real-time/
Businesses will increasingly have access to open data repositories. Business solutions will be subject to Creative Commons licensing.
http://pennystocks.la/internet-in-real-time/
Kobalt, the London-based startup that has built big-data technology to track and collect digital music royalties from across multiple streaming platforms,
is turning up the volume on its business. The company has quietly acquired and redesigned one of the main collection agencies in the U.S. — the American
Mechanical Rights Agency. http://techcrunch.com/2015/06/08/kobalt-quietly-acquired-amra-to-launch-its-own-global-collection-group-for-digital-music/

16. 0115
Open access data
Re-use real world data for learning
Activity
Using one of the sources
listed here locate data sets
that might be useful in the
context of your teaching.
https://researchdata.ands.org.au/
http://www.data.gov/http://www.data.gov/
http://datacatalog.worldbank.org/
http://www.opendataresearch.org/emergingimpacts
http://blog.visual.ly/data-sources/

17. 0116
Big data in education
sometimes called “learning analytics”
Tin Can (Experience) API - http://tincanapi.com/overview/

18. 0117
The Internet of Things
the world of connected everything
Governance and Recordkeeping Around the World Newsletter (April 2015)
http://www.bac-lac.gc.ca/eng/services/government-information-resources/information-management/Documents/april-2015.pdf
“Approximately 14 billion objects
(things) are connected to the
Internet and is growing. We are now
entering a new phase in how these
objects are used and what will be
their impact. The IoT brings with it
enormous opportunities, to both the
private and public sectors, in all
areas including the management of
information throughout its lifecycle.”
18
6 connected things per human by 2020 - http://images.info.polycom.com/Web/PolycomInc/%7Bb218e958-d861-449d-9262-fe694a5eab98%7D_bb-annualreport2012.pdf

19. 0118
The Internet of Things
what might it look like?
What is the Internet of Things (Infographic) - http://www.visualcapitalist.com/what-is-internet-things/
“Thingful® is a search engine for the Internet of
Things, providing a unique geographical index of
connected objects around the world, including
energy, radiation, weather, and air quality devices
as well as seismographs, iBeacons, ships, aircraft
and even animal trackers. Thingful’s powerful
search capabilities enable people to find devices,
datasets and realtime data sources by geolocation
across many popular Internet of Things networks,
and presents them using a proprietary patent-
pending geospatial device data search ranking
methodology, ThingRank®.”

20. 0119
The Internet of Things
Becomes searchable
What is the Internet of Things (Infographic) - http://www.visualcapitalist.com/what-is-internet-things/
“Shodan is the world's first search engine for
Internet-connected devices.”

21. 0120
The Internet of Things
Cisco Internet of Everything (IoE) Innovation Centre (CIIC)
What is the Internet of Things (Infographic) - http://www.visualcapitalist.com/what-is-internet-things/
“Curtin University will host the Western Australian
hub of the Cisco Internet of Everything (IoE)
Innovation Centre (CIIC)”
Cisco IoE Innovation Centre Australia helps local
and global organisations improve business
outcomes. As an innovation centre and workplace
for customers, partners, startups, universities and
open communities, we're doing this in three ways:
• Demonstrating IoE in action to solve business
and public sector problems
• Engaging in rapid solution and product
prototyping
• Research and investments in local resources,
including companies and people
CIIC - http://news.curtin.edu.au/media-releases/cisco-internet-everything-innovation-centre-launched-curtin/
$77Bn disclosed deals relating to IoT in Q1 2015 - http://www.eweek.com/small-business/internet-of-things-cloud-drive-tech-deals-in-q1.html*

22. 0121
Data mining
Making sense of big data
Photo credit: -https://www.flickr.com/photos/franganillo/3678747186/ (CC Jorge Franganillo)
Data mining is the process of looking for patterns
and relationships within and across data
collections. Normally by applying some form of
computerised manipulation.
Analytics - a visual expression of a particular
arrangement and analysis of data.
Data can tell you what has happened but can only
be used to guess what will happen - this is called
predictive analytics.
Open Data
“Open data and content can be freely used,
modified, and shared by anyone for any
purpose” (http://opendefinition.org/)

23. 0122
Photo credit: We are Anonymous - https://www.flickr.com/photos/equinoxefr/6856903841/
Key questions
Who is allowed to collect data?
What can they do with it?
What limits should be in place?
Who owns data?
What data should be public domain?
At what point does tracking become stalking?
At what point does data hoarding become a
restrictive practice?
Ethics and data collection
Ethics, security and privacy
Links
Online privacy: 'Big
data' is watching, and
building your digital
profile’ [news]
Ethical uses of big data
and web analytics
[video]
Social, Cultural and
Ethical Dimensions of
“Big Data” [video]

24. 0123
Ethics, security and privacy
Ethics, security and privacy
Photo credit: -https://www.flickr.com/photos/21218849@N03/3120339082/
Q. Responsibilities
of knowing?
If I analyse your data
and it suggests that
you are at some sort
of risk - what is my
responsibility to
inform you?
Eg: Key updates to the eBay Privacy Notice:
• eBay and PayPal data sharing: An entirely new sub-section under Disclosure to cover the authorised data sharing between eBay and PayPal.
Tim Cook:
“Like many of you, we at Apple reject the idea that our customers should have to make tradeoffs between privacy and security,” Cook opened. “We can, and
we must provide both in equal measure. We believe that people have a fundamental right to privacy. The American people demand it, the constitution
demands it, morality demands it.”
http://techcrunch.com/2015/06/02/apples-tim-cook-delivers-blistering-speech-on-encryption-privacy/

25. 0124
Ethics, security and privacy
Ethics, security and privacy
Photo credits: - ASIO - http://www.abc.net.au/news/image/4630312-3x2-940x627.jpg
GCHQ - http://en.wikipedia.org/wiki/Government_Communications_Headquarters#/media/File:GCHQ-aerial.jpg
Who can collect, keep, share, use
your data?
After ethical data collection it is
essential to consider data security.
How do you protect against:
Corruption - maintain data integrity
Manipulation - control uses
Access - gate keeping
Currently they refer to the amount of data held by these agencies in Yottabytes - but they are preparing for Brontobytes - 10
27
-
1,000,000,000,000,000,000,000,000,000

26. 0125
Privacy
Privacy is largely an ACCESS issue.
Photo credit: o5com - https://www.flickr.com/photos/o5com/5107015769/in/photostream/
Personally Identifying
Information - a lot of
big data is de-identified
(especially in formal
research contexts) - but
if the business goal is
some form of
personalisation then
privacy becomes a
matter of controlling
access.

27. 0126
Data visualisation
Communicating the meaning of your data visually.
Visualisation Examples: http://savedelete.com/design/data-visualization-examples/176982/
Data visualisation examples:
• Charts,
• graphs,
• maps
• Infographics
• Interactive displays
• Adaptive display
• Dynamic display
Many tools are applied to his kind of work:
Rapid Miner
Tableau
22 Free tools article
30+ Free Tools
Storytelling with Data Visualisation: http://blog.kurtosys.com/storytelling-data-visualization/
27

28. 0127
Data visualisation
Handling data physically - 3D printing
Visualisation Examples: http://savedelete.com/design/data-visualization-examples/176982/
Data visualisation examples:
• Charts,
• graphs,
• maps
• Infographics
• Interactive displays
• Adaptive display
• Dynamic display
and more recently by using manufacturing
technologies like 3D printing.
Visualising data (Brendan Dawes): http://www.forbes.com/sites/michaelhumphrey/2015/02/19/making-data-souvenirs-via-3d-printing-a-chat-with-brendan-dawes/

29. 0128
Computational Thinking
Thinking logically, thinking with a structure.
Photo credit: http://en.wikipedia.org/wiki/Computational_complexity_theory
“ Computational Thinking is the thought
processes involved in formulating problems
and their solutions so that the solutions are
represented in a form that can be effectively
carried out by an information-processing
agent. “
Cuny, Snyder, Wing

30. 0129
Computational Thinking
Bringing it into work and learning
Photo credit: https://www.behance.net/gallery/5798457/ISTE-Computational-Thinking-Poster
Scaffolding design thinking, computational
thinking and creative problem-solving
(innovation)
• Challenge based approaches
• Defining problems
• Collaborative solutions
• Authentic- Real world application - use
global challenges as an example.
• Rapid iteration (modelling/prototyping/
testing)
• Novel juxtaposition
• Bluesky speculation

31. 0130
Computational Thinking
Applying it to challenge based learning
Photo credit: http://challenge.curtin.edu.au
Welcome to Curtin Challenge, where you can
develop your skills, build your networks, and
shape your future. Challenge is a fun and
interactive way to learn, and is just one of the
many ways Curtin University is transforming
your University experience.
Curtin Challenge is a platform where you can
explore different themes of interest, to
achieve your personal and professional goals.
Challenges allow you to develop your skills,
build your networks, and shape your future
while earning badges and achievements.

32. 0131
Computational Thinking
Applying it to challenge based learning
Photo credit: https://www.apple.com/au/education/docs/CBL_Classroom_Guide_Jan_2011.pdf
Challenge Based Learning
mirrors the 21st century
workplace. To stay true to its
intent, make sure participants:
• Work in collaborative groups
• Use technology commonly used in
daily life
• Tackle real-world problems using a
multidisciplinary approach
• Share the results with the world

33. 0132
Computational Pedagogy
from literacy to fluency; from using to making; from watching to creating
Coding
Transform learning
Fluencies
Hacking
Making

34. 0133
Computational Pedagogy
Bringing it into work and learning
Download report: http://www.nap.edu/catalog/13170/report-of-a-workshop-on-the-pedagogical-aspects-of-computational-thinking
In 2008, the Computer and Information
Science and Engineering Directorate of
the National Science Foundation asked
the National Research Council (NRC) to
conduct two workshops to explore the
nature of computational thinking and its
cognitive and educational implications.
The first workshop focused on the scope
and nature of computational thinking and
on articulating what "computational
thinking for everyone" might mean. A
report of that workshop was released in
January 2010.

35. 0134
Learning by making
from consuming to creating
Resource: Makerspace Playbook (MakerEd) http://makered.org/wp-content/uploads/2014/09/Makerspace-Playbook-Feb-2013.pdf
“ This playbook will help you establish a
wonderful new resource in your school,
neighborhood, or wider local community. It
shares the knowledge and experience from
the Makerspace team as well as from those
who have already started Makerspaces. “

36. 0135
Bluesky Learning
Innovation is creative problem-solving
Photo Credit: "Newton Blue Sky". Licensed under CC BY 2.5 via Wikipedia -
http://en.wikipedia.org/wiki/File:Newton_Blue_Sky.jpg#/media/File:Newton_Blue_Sky.jpg
“Gentleness, Virtue, Wisdom, and Endurance,
These are the seals of that most firm assurance
Which bars the pit over Destruction's strength;
And if, with infirm hand, Eternity,
Mother of many acts and hours, should free
The serpent that would clasp her with his length;
These are the spells by which to reassume
An empire o'er the disentangled doom.
To suffer woes which Hope thinks infinite;
To forgive wrongs darker than death or night;
To defy Power, which seems omnipotent;
To love, and bear; to hope till Hope creates
From its own wreck the thing it contemplates;
Neither to change, nor falter, nor repent;
This, like thy glory, Titan, is to be
Good, great and joyous, beautiful and free;
This is alone Life, Joy, Empire, and Victory.”
― Percy Bysshe Shelley, Prometheus Unbound

37. 0136
SMART Learning
Adapting educational contexts to the era of big data
From David Gibson - https://prezi.com/ynemeqygnohl/theta-2015 (used with permission)
Synchronous
Multiply Connected
Asynchronous
ROI
Transformed
Ubiquitous technology
Networked
Integrated Systems
Multiply (adverb)

38. Let computers compute . The age of the right brain.
http://www.nytimes.com/2008/04/06/technology/06unbox.html
Big data needs more creative types:
37
“The data artist blends engineering
and statistical know-how with
intuition and novel problem-solving
abilities to uncover insights and
create value from data.
“Data Scientist” is a fine job title for
those who navigate terabytes of
information in search of patterns
and relevance, connecting dots to
create value and competitive
advantage.”
Creativity is the future of work
The dawn of the creative economy
Big data needs more creative types:
http://www.forbes.com/sites/teradata/2015/01/30/big-data-needs-more-creative-types/
Developing capacity as data artists might be the key to business success.
The “adjacent possible” may redirect business intelligence to transformation.
The ‘adjacent possible” - Stuart Kauffman

39. DiscussionVerbal data exchange
Q
&
A

40. 0139
Main takeaways
If you remember nothing else, remember these.
• Understand how to work with data
• Collaborate at every opportunity
• Strive for authenticity
• Critically engage with the changes
• Take in the long view
• Actively engage with complexity
Conclusion
Start with
familiar data
Start with
available
tools
Start sooner
rather than
later
Start with
unlimited
thinking
EDUCAUSE identified five domains of core functionality for the NGDLE:
1 Interoperability and Integration
2 Personalization
3 Analytics, Advising, and Learning Assessment
4 Collaboration
5 Accessibility and Universal Design

41. Good ByeSee you next time, have a nice day
Big Data, Computation and the Internet of Things
http://www.scoop.it/t/big-data-computation-and-internet-of-things