1. Enabling Creative Context Engineering
within Augmented Spaces
Carl Smith
Learning Technology Research Institute (LTRI)
London Metropolitan University
London Metropolitan University Learning Technology Research Institute

2. Research: Augmenting Learning Contexts
 A core research area at LTRI is to understand the
contextual factors which influence and affect learning.
The first wave of mobile learning was communication,
the second was content and now we have entered the
third, which is context.
MAR is about context because it is inherently about
who you are, where you are, what you are doing, and
what is around you.
Well designed MAR should enable the creation of
situations and concepts that could not have been
realised before by uniting the strengths, features
and possibilities of both the physical and the
virtual space.
London Metropolitan University Learning Technology Research Institute

3. LTRI: Augmenting Learning Contexts
Learning requires the possibility to transform your
point of view and re-program your perspective.
Replacing imagination with computer animation?
Leverage computers instead of catering to them
(natural interaction)
Build daydreaming back in....
Use technology to create ‘post digital’ context
engines.
London Metropolitan University Learning Technology Research Institute

4. Definition of Context Engineering
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5. Technology can be invented; human
nature is something we're stuck with.
A tool addresses human needs by
amplifying human capabilities.
“Pictures Under Glass is an interaction
paradigm of permanent numbness and
yet, it's the star player in every Vision Of
The Future.”
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6. London Metropolitan University Learning Technology Research Institute

7. Technology Narrative
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8. Ancient Technology: Body Mnemonics
‘the body space is a very
individual culturally defined
construct, and thus can
provide a highly personalised
and meaningful interface.”
(Ängeslevä, J. 2003)
London Metropolitan University Learning Technology Research Institute

9. Hacking Reality
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10. Another Context Engine: Inception App
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11. Fractured View = Reduction in Learning?
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12. Initial Case Studies – Procedural
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13. Case Studies –Declarative - Content / Interface/
Interaction
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14. Labelling is not real knowledge? Feynman
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15. The label allowed the object to be seen
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16. Instead of having to learn it you can just see it
London Metropolitan University Learning Technology Research Institute

17. Macroscopic Learning
A map of Manhattan named “Here
& There.” places the viewer
simultaneously above the city
and in it and allows them to plot
a path between them.
The projection connects the
viewer's local environment to
remote destinations normally out of
sight.
“A macroscope is something that
helps us see what the aggregation
of many small actions looks like
when added together.” John
Thackera
London Metropolitan University Learning Technology Research Institute

18. A revolution in spatial literacy: Access to
new spaces: Implications for what can be
known
London Metropolitan University Learning Technology Research Institute

19. London Metropolitan University Learning Technology Research Institute

20. To see across as opposed to from
AR methodologies can be used to
fundamentally expand the range of available
ways of seeing.
The AR methodologies formulated during this
research allow users to work simultaneously
from the macroscopic and microscopic view.
This enables them to shift their pov and rapidly
reframe their understanding.
Not centred on the technology but the
navigational shift that results when the world
itself becomes the interface.
New emphasis on spatial literacy is required.
London Metropolitan University Learning Technology Research Institute

21. Conclusion – Surveillance vs Imagination
The danger of Augmented Reality applications lies
in rationalising spaces using tags, categories, and
ratings. This documentation and digitisation of
elements of our world is a form of surveillance.
We need to reactivate the imagination as a faculty
through which to experience our surroundings
and explore the meaning of spaces through
personal narration, rather than objective
knowledge systems.
carl.smith@londonmet.ac.uk
London Metropolitan University Learning Technology Research Institute