It is about promoting distributed cognitive learning behaviors with ecological design in MOOCs

1. Promo%ng
Distributed
Cogni%on
at
MOOC
Ecosystems
Kai
Pata
and
Emanuele
Bardone
Tallinn
University
Human
Computer
Interac%on
Conference
2014,
Crete,
Iraclion

2. MOOCs
promote
distributed
cogni.on
based
learning
behaviors
Ecological
learning
design
may
facilitate
distributed
cogni%ve
learning
in
MOOCs

3. I.
Connec%vist
MOOC
as
a
learning
ecosystem
• Users
provide
learning
services
to
each
other
at
MOOCs
as
produsers
thereby
crea%ng
the
abundance
of
ecosystem
“species”
• Individual
as
well
as
crowd
knowledge
in
MOOCs
is
operated
by
as
well
as
incorporated
into
the
different
learning
services
Example
learning
services::
Peer
comments
to
blog
posts
–
kind
scaffolding
service
User-­‐created
ar3fact
as
a
learning
resource
–
kind
of
knowledge
provision
service
Socially
annotated
and
aggregated
contents
–
a
kind
of
scaffolding
service

4. Communi%es
of
learning
services
in
MOOC
learning
ecosystems
• are
temporary
coali.ons
deno%ng
the
services
and
actors
at
present
in
the
learning
design
• that
can
successively
change
during
the
life%me
of
a
design
product
usage
• Currently
available
learning
services
in
certain
learning
moment
the
MOOC
ecosystem
compete
with
each
other
or
may
form
alliances,
some
services
increase
in
numbers
while
others
perish

5. blog
posts,
videos,
wiki
pages
forums,
blog
comment,
skype
sessions
blog
comment,
badges
facebook
and
twiOer
walls
Red
–
facilitators,
experts
Green
-­‐
learners
Successive
learning
service
communi%es
in
MOOC

6. Learning
flows
in
MOOCs
• The
main
form
of
ecosystem
existence
is
through
trophic
networks
of
species
that
transform
energy
and
maOer
composing
and
decomposing
energy
rich
products,
thus
enabling
the
one-­‐
direc%onal
trophic
flow
through
the
ecosystem.
• In
MOOC
learning
ecosystems
the
relevant
concept
to
trophic
flow
is
a
learning
flow.
• User
a?en.on
to
available
services
fuels
the
knowledge
flows
through
the
services,
which
defines
the
produc.vity
of
learning
ecosystems.

7. The
network
structure
of
MOOCs
• The
permeability
of
MOOC
learning
ecosystem
to
learning
flows
will
depend
on
the
connec.ons
between
services
that
pass
learning
flows
and
the
emerging
side-­‐paths
and
hubs
in
this
network
that
can
redirect
the
flows.
• There
are
always
relevant
goals,
resources
and
required
support
available
in
MOOCs
that
may
replace
in
the
learning
ecosystem
purpose
niches
some
of
the
missing
services
and
allow
the
con%nuous
learning
flows.

8. Purpose
niches
of
learning
services
Red
–
facilitators,
experts
Green
-­‐
learners

9. Pruning
homogenous
communi%es
at
usual
elearning
courses
• Maintaining
homogenous
communi%es
such
as
ideal
teacher-­‐planned
sets
of
learning
services
needs
constant
care
• few
learning
services
prescribe
limited
learning
paths
in
order
to
maximize
the
produc%ve
learning
flows
for
medium
learners
that
don’t
exist.

10. Succession
of
wild
communi%es
in
open
informal
learning
seYngs
The
natural
learner-­‐created
communi%es,
are
based
on
the
richness
of
constantly
changing
learning
services
that
can
replace
themselves
in
the
trophic
networks,
that
guarantees
beOer
self-­‐regula%on
but
also
the
succession
of
the
service-­‐community
in
%me.

11. Maintaining
semi-­‐natural
communi%es
in
MOOCs
In
the
learning
ecosystems
that
inhabit
semi-­‐natural
communi.es
where
both
the
teacher-­‐
and
learner-­‐created
learning
services
could
co-­‐exist,
the
former
could
be
used
to
maintain
the
richness
of
wild
services
and
keep
it
in
a
state
where
succession
is
under
control.

12. Mutualisms
• The
mutualisms
such
as
symbiosis
(mutual
benefit
of
using
resources
and
living
spaces)
are
one
way
how
in
natural
ecosystems
species
get
the
compe%%ve
premise.
• Mutualisms
between
different
types
of
learning
services
are
very
important
also
in
MOOC
learning
designs.
Socially
annotated
and
aggregated
contents
e.g.
tagcloud
–
a
kind
of
crowd
based
scaffolding
service
Socially
annota3ng
resources
–
a
kind
resource
provision
service
Tag-­‐based
user
profile
forma3on
Knowledge
provision
based
on
user
profile

13. Communica%on
• In
natural
ecosystems
there
is
communica.on
between
the
individual
species
as
well
as
the
cross-­‐species
communica%on
that
has
influence
on
trophic
circula%ons
(for
example
certain
signals
from
species
may
be
read
by
other
members
of
the
species
or
across
species
to
get
advantage
in
finding
food
or
escaping
for
predators).
• Communica%on
intensifies
the
learning
flows
within
the
learning
ecosystem.
• The
learning
services
in
learning
ecosystem
must
be
aware
of
each
other
and
able
to
communicate
in
order
to
orchestrate
their
ac%on.
• Communica%on
(direct
and
indirect
through
signals
and
traces
le]
in
the
environment)
can
be
used
for
swarming
for
learning
in
learning
ecosystems

14. II.
Distributed
cogni%on
at
MOOCs
• Connec%vist
MOOCs
have
a
similarity
to
natural
ecosystems
also
at
a
distributed
cogni%on
level
• Produsers
form
a
.ghtly
coupled
system
with
MOOCs
ecosystem
of
learning
services
created
by
all
produsers,
and
the
laOer
simultaneously
evolves
and
serves
as
one’s
partner
or
cogni%ve
ally
in
the
struggle
to
control
the
ac%vity
• Learning
services
created
by
many
at
MOOCs
enable
this
par.ally
external
locus
of
control

15. Learning
behaviors
related
with
distributed
cogni%on
uptake
of
cultural
paOerns
Cogni%ve
niche
forma%on
Cultural
niche
forma%on
Ecological
encultura%on
personal
paOern
cultural
paOern
amplifica%on
forma%on
of
paOern
networks
cultural
paOern
appropria%on
chance
amplifica%on
%nkering
Epistemic
Distributed
Cogni%on
Collec%ve
Distributed
Cogni%on
Chance-­‐seeking
PaOern
appropria%on
Encultura%on
of
paOerns

16. Which
learning
to
promote
in
MOOCs?
• We
highlight
produc3ve
learning
behaviors*
related
with
distributed
cogni%on
–
learning
as
chance-­‐
seeking,
pa?ern
appropria.on
and
ecological
encultura.on
• The
chance-­‐seekers
create
cogni%ve
niches
that
may
extend
or
shiF
the
cultural
pa?ern
niches
evolving
the
ecosystem,
• whereas
paOern
appropria%on
ac%vity
validates
cultural
pa?ern
niches
and
stabilizes
the
ecosystem
• *Produc.vity
of
the
learning
ecosystem
is
its
ability
to
accumulate
informa%on
to
knowledge
in
%me
–
meaning
how
much
users
can
be
engaged
in
certain
%me
period
by
the
learning
services
into
the
produc%ve
learning
flow.

17. Ecological
design
of
MOOCs
that
triggers
distributed
cogni%ve
learning
• The
design
approach
employed
in
MOOC
ecosystems
to
promote
produc.ve
loops
of
pa?ern
appropria.on,
chance-­‐seeking
and
ecological
encultura.on
is
twofold.
• On
the
one
hand
the
connec%vist
MOOCs
should
be
built
so
that
they
facilitate
the
self-­‐organisa.on
of
learning
ecosystems,
which
promotes
environmental
unan.cipatedness
for
chance-­‐seekers.
• On
the
other
hand,
for
promo.ng
pa?ern
appropria.on
and
increasing
ecological
encultura.on
different
means
of
learning-­‐analy.cs
should
be
used
that
make
paOerns
in
the
shared
cultural
niche
visible
for
learners.

18. Visualizing
learning
service
niches
in
MOOC
ecosystems
Mul%dimensional
space

19. The
ecological
learning
design
• The
ecological
learning
design
is
the
meta-­‐
design
process
where
par%cipatory
cultures
use
ecosystem
principles
for
enculturing
for
themselves
responsive
learning
ecosystems
that
maximize
for
each
of
them
possibili.es
for
flow
experiences
promoted
by
the
learning
flows
of
the
crowd
(actualizing
pa?erns)
or
provide
them
opportuni.es
for
discovering
chances.