Keynote delivered at the Emerging Technologies in Authentic Learning Contexts Conference (Cape Town, South Africa), drawing links between my research on digital learning, emerging technologies, learner experiences, and the changing higher education landscape.

1. Emerging
Technologies
in
Authen2c
Learning
Contexts
Conference
September
2015,
Cape
Town,
South
Africa
Digital Learning, Emerging Technologies,
Abundant Data, and Pedagogies of Care!
George Veletsianos, PhD!
!
Canada Research Chair in Innovative Learning & Technology!
Associate Professor!
!
School of Education and Technology!
Royal Roads University!
Victoria, British Columbia, Canada!

6. Research
Focus
Learner,
instructor,
&
scholar
experiences
Emerging
technologies
&
emerging
prac2ces
Digital
educa2on;
online
networks
To
design
excep2onal,
empowering,
&
equitable
learning
experiences

7. Key
takeaways
• The
EdTech
industry.
A
remedy?
• Big
Data,
Analy2cs,
and
experimental/Quant
approaches.
Capable
of
explaining
what,
how,
and
why
learning
happens?
• Educa2on.
A
product
to
be
managed,
automated,
and
delivered?
• Edech
is
founded
on
technodeterminis2c
thinking
• How
is
all
this
supposed
to
foster
contexts
of
care?

8. A
worldwide
economic
downturn
Globaliza2on
and
compe22on
à
interna2onaliza2on
policies
Increased
demand
for
educa2on
Curtailment
of
public
funding
Pressures
for
accountability
Impact
of
emerging
technologies
Higher
Educa2on
Trends
and
Pressures
Automa2on
à
Work?
Priva2za2on

9. The
rise
of
“EdTech
as
a
remedy”

10. The
rise
of
“EdTech
as
a
remedy”
“Whether the practice is called
outsourcing, contracting out, or
privatizing, the impact is the
same. Food services, health
care, the bookstore…endless
array of activities that
universities used to manage…”
Kirp,
.L
(2003).
Shakespeare,
Einstein,
and
the
Bo3om
Line:
The
Marke9ng
of
Higher
Educa9on.
Cambridge,
MA:
Harvard
University
Press

11. The
rise
of
“EdTech
as
a
remedy”
Online program
management services

12. What
are
some
of
the
most
problema2c
assump2ons
of
EdTech?

13. “What
6.9
million
clicks
tell
us
about
how
to
fix
online
educa2on”
(Conner-­‐Simons,
2014)
“We
can
see
everything
the
students
do”
(Chu,
2013)
Assump2on
#1:
Massive
data
sets
will
tell
us
all
that
we
need
to
know
about
learning
and
teaching

14. Assump2on
#1:
Massive
data
sets
will
tell
us
all
that
we
need
to
know
about
learning
and
teaching
Results
from
a
2013-­‐2015
analysis
of
the
MOOC
literature:
“Automated
collec2on
of
secondary
data
(e.g.,
trace
data)
was
used
most
frequently
(73.2%
of
papers
used
this
method).
The
second
most
popular
data
collec2on
method
was
ques2onnaires/
surveys,
which
were
used
in
55.7%
of
papers….Interviews
(13.7%),
secondary
data
collected
by
humans
(13.7%),
tests
(8.7%),
observa2ons
(4.9%),
focus
groups
(4.4%),
and
other
(2.7%).”

15. Assump2on
#1:
Massive
data
sets
will
tell
us
all
that
we
need
to
know
about
learning
and
teaching

16. What
aspects
of
digital
learning
cannot
be
fully
understood
and
improved
using
data
trails?

17. What
aspects
of
digital
learning
are
invisible
to
algorithms,
mining,
and
analy2cs?

18. A.
Why
do
learners
par2cipate
in
digital
learning
environments
in
the
ways
that
they
do?

19. B.
How
do
learners
overcome
challenges
in
digital
learning
environments?

20. Embedded
in
seemingly
innocuous
descrip2ons
like
“managing
scale”
and
“crea2ng
efficiencies”
Assump2on
#2:
Educa2on
is
a
product
to
be
packaged,
automated,
&
delivered

21. Assump2on
#2:
Educa2on
is
a
product
to
be
packaged,
automated,
&
delivered

22. Assump2on
#2:
Educa2on
is
a
product
to
be
packaged,
automated,
&
delivered

23. Assump2on
#3:
Techno-­‐determinism
It’s not that automated methods are
undesirable “…it is rather that the terms
on which they are proposed are driven
by a productivity-oriented solutionism
which has been critiqued for decades
now”
(Bayne, 2015)

24. Assump2on
#3:
Techno-­‐determinism
The Silicon Valley flavor of EdTech à a naïve belief in
determinism
Void of the most basic foundations of Educational
Technology as a field of practice.

25. Assump2on
#3:
Techno-­‐determinism
Emerging
Technologies
and
Emerging
Prac2ces
are
defined
by
the
contexts
in
which
they
occur.

26. Assump2on
#3:
Techno-­‐determinism
Emerging
Technologies
and
Emerging
Prac2ces
are
defined
by
the
contexts
in
which
they
occur.
They
share
four
characteris2cs
1.
Not
defined
by
newness
2.
Coming
into
being
3.
Not-­‐yetness
4.
Unfulfilled
but
promising
poten2al

27. To
what
end?
The Silicon Valley flavor of EdTech
What
needs
does
this
EdTech
serve?
Does
this
EdTech
create
a
context
of
care?
Does
this
EdTech
foster
pedagogies
of
care?

28. Pedagogies
of
Care
Care.
A
core
element
of
pedagogy
(Noddings,
2003)

29. To
what
end?
What
would
an
African
flavor
of
EdTech
look
like?
What
should
home
grown
solu2ons
look
like
&
what
issues
do
they
need
to
address?

30. To
what
end?

31. Thank
you!
Research
available
at:
hnp://www.veletsianos/
publica2ons
This
presenta2on:
www.slideshare.com/veletsianos
Contact:
veletsianos@gmail.com
@veletsianos
on
Twiner