5. TERENCE
in
a
nutshell
TERENCE
is
a
collabora/ve
FP7
project
‣ for
Technology
Enhanced
Learning
(TEL)
‣ for
children
with
specific
text
comprehension
problems
and
their
educators
‣ for
developing
and
adap/ve
learning
system
that
recommends
its
learners
the
adequate
learning
material,
made
of
digital
6. TERENCE
in
a
nutshell
TERENCE
is
a
collabora/ve
FP7
project
‣ for
Technology
Enhanced
Learning
(TEL)
‣ for
children
with
specific
text
comprehension
problems
and
their
educators
‣ for
developing
and
adap/ve
learning
system
that
recommends
its
learners
the
adequate
learning
material,
made
of
digital
‣ books
of
stories
7. TERENCE
in
a
nutshell
TERENCE
is
a
collabora/ve
FP7
project
‣ for
Technology
Enhanced
Learning
(TEL)
‣ for
children
with
specific
text
comprehension
problems
and
their
educators
‣ for
developing
and
adap/ve
learning
system
that
recommends
its
learners
the
adequate
learning
material,
made
of
digital
Who runs fast?
‣ books
of
stories
‣ and
smart
games
for
reasoning
about
stories
8. TERENCE
in
a
nutshell
TERENCE
is
a
collabora/ve
FP7
project
‣ for
Technology
Enhanced
Learning
(TEL)
‣ for
children
with
specific
text
comprehension
problems
and
their
educators
‣ for
developing
and
adap/ve
learning
system
that
recommends
its
learners
the
adequate
learning
material,
made
of
digital
‣ How
do
we
design
the
TERENCE
learning
material
and
overall
system
so
as
to
be
Who runs fast?
‣ books
of
stories
‣ and
smart
games
for
reasoning
about
stories
9. TERENCE
in
a
nutshell
TERENCE
is
a
collabora/ve
FP7
project
‣ for
Technology
Enhanced
Learning
(TEL)
‣ for
children
with
specific
text
comprehension
problems
and
their
educators
‣ for
developing
and
adap/ve
learning
system
that
recommends
its
learners
the
adequate
learning
material,
made
of
digital
‣ How
do
we
design
the
TERENCE
learning
material
and
overall
system
so
as
to
be
Who runs fast?
‣ books
of
stories
‣ and
smart
games
for
reasoning
about
stories
‣ usable
by
its
users
10. TERENCE
in
a
nutshell
TERENCE
is
a
collabora/ve
FP7
project
‣ for
Technology
Enhanced
Learning
(TEL)
‣ for
children
with
specific
text
comprehension
problems
and
their
educators
‣ for
developing
and
adap/ve
learning
system
that
recommends
its
learners
the
adequate
learning
material,
made
of
digital
‣ How
do
we
design
the
TERENCE
learning
material
and
overall
system
so
as
to
be
Who runs fast?
‣ books
of
stories
‣ and
smart
games
for
reasoning
about
stories
‣ and
effec>ve
for
them?
‣ usable
by
its
users
11. Data
for
context
of
use
from
children
start
no
release
yesok?
gather data
specify requirements
design
develop
evaluation
12. Data
for
context
of
use
from
children
start
no
release
yesok?
gather data
specify requirements
design
develop
evaluation
282
learners
in
Italy
226
learners
in
UK
30
school
educators
10
domain
experts
13. Data
for
context
of
use
from
children
start
no
release
yesok?
gather data
specify requirements
design
develop
evaluation
282
learners
in
Italy
226
learners
in
UK
30
school
educators
10
domain
experts
how
to
do
that
with
so
many
young
learners
at
school?
15. Challenges
in
collecGng
data
from
children
Reliability
of
collected
data:
‣ children
might
become
anxious
at
the
thought
of
taking
a
test
(Rubin
1995)
and
hence
not
express
their
true
selves,
‣ thus
direct
methods
should
be
avoided
(Druin
2010)
16. Challenges
in
collecGng
data
from
children
Reliability
of
collected
data:
‣ children
might
become
anxious
at
the
thought
of
taking
a
test
(Rubin
1995)
and
hence
not
express
their
true
selves,
‣ thus
direct
methods
should
be
avoided
(Druin
2010)
Drop-‐outs
easily
occur
‘cause
for
children
(Chiasson
and
Gutwin
2005)
‣ “mo>va>on
and
engagement
are
[...]
important”
‣ “children
[need]
to
see
the
results
of
their
ac>ons
immediately”
17. Challenges
in
collecGng
data
from
children
Reliability
of
collected
data:
‣ children
might
become
anxious
at
the
thought
of
taking
a
test
(Rubin
1995)
and
hence
not
express
their
true
selves,
‣ thus
direct
methods
should
be
avoided
(Druin
2010)
Drop-‐outs
easily
occur
‘cause
for
children
(Chiasson
and
Gutwin
2005)
‣ “mo>va>on
and
engagement
are
[...]
important”
‣ “children
[need]
to
see
the
results
of
their
ac>ons
immediately”
School/environment
constraints:
ac>vi>es
should
‣ involve
an
en>re
class,
‣ respect
school
>me-‐tables,
e.g.,
each
session
should
last
no
longer
than
2
hours
19. What
we
did:
we
gamified
data
gathering
GamificaGon
is
the
usage
of
game-‐play
elements
in
a
non-‐game
context
for
engaging
and
mo>va>ng
users,
e.g.,
in
ac>vi>es
20. What
we
did:
we
gamified
data
gathering
Reliability
of
collected
data
‣ can
be
achieved
if
children
get
engaged
in
diverse
progressive
challenges
for
diverse
skills
GamificaGon
is
the
usage
of
game-‐play
elements
in
a
non-‐game
context
for
engaging
and
mo>va>ng
users,
e.g.,
in
ac>vi>es
21. What
we
did:
we
gamified
data
gathering
Reliability
of
collected
data
‣ can
be
achieved
if
children
get
engaged
in
diverse
progressive
challenges
for
diverse
skills
GamificaGon
is
the
usage
of
game-‐play
elements
in
a
non-‐game
context
for
engaging
and
mo>va>ng
users,
e.g.,
in
ac>vi>es
Drop-‐outs
‣ can
be
avoided
via
>mely
usable
feedback
and
engagement
22. What
we
did:
we
gamified
data
gathering
Reliability
of
collected
data
‣ can
be
achieved
if
children
get
engaged
in
diverse
progressive
challenges
for
diverse
skills
GamificaGon
is
the
usage
of
game-‐play
elements
in
a
non-‐game
context
for
engaging
and
mo>va>ng
users,
e.g.,
in
ac>vi>es
Drop-‐outs
‣ can
be
avoided
via
>mely
usable
feedback
and
engagement
School/environment
constraints
require
we
‣ involve
all
children
in
social
ac>vi>es,
‣ a
linear
planning/storyline
and
engagement
for
mee>ng
>me-‐tables
23. What
we
did:
we
gamified
data
gathering
Reliability
of
collected
data
‣ can
be
achieved
if
children
get
engaged
in
diverse
progressive
challenges
for
diverse
skills
GamificaGon
is
the
usage
of
game-‐play
elements
in
a
non-‐game
context
for
engaging
and
mo>va>ng
users,
e.g.,
in
ac>vi>es
Drop-‐outs
‣ can
be
avoided
via
>mely
usable
feedback
and
engagement
School/environment
constraints
require
we
‣ involve
all
children
in
social
ac>vi>es,
‣ a
linear
planning/storyline
and
engagement
for
mee>ng
>me-‐tables
24. What
we
did:
we
gamified
data
gathering
Reliability
of
collected
data
‣ can
be
achieved
if
children
get
engaged
in
diverse
progressive
challenges
for
diverse
skills
GamificaGon
is
the
usage
of
game-‐play
elements
in
a
non-‐game
context
for
engaging
and
mo>va>ng
users,
e.g.,
in
ac>vi>es
‣ But
which
gamifica9on
‘model’,
i.e.,
what
of
game-‐play
can
ensure
us
we
really
engage
our
learners
in
our
data
collec9on?
Drop-‐outs
‣ can
be
avoided
via
>mely
usable
feedback
and
engagement
School/environment
constraints
require
we
‣ involve
all
children
in
social
ac>vi>es,
‣ a
linear
planning/storyline
and
engagement
for
mee>ng
>me-‐tables
26. The
“video
game
uses
and
gratifications”
model
(Sherry
&
Lucas
2003)
says
that
different
players
engage
in
games
for
different
gratifications:
competition
challenge
diversion
arousal
fantasy
social
interaction
Gamification: diverse views
27. Flows
are
engaging
activities
(e.g.,
games)
with
a
balance
between
challenges
and
skills,
and
for
(Kiili
2005)
are
realised
in
games
via:
balanced
challenges
and
skills
timely
usable
feedback
clear
goals
immersive
storylines
intrinsic
rewards
The
“video
game
uses
and
gratifications”
model
(Sherry
&
Lucas
2003)
says
that
different
players
engage
in
games
for
different
gratifications:
competition
challenge
diversion
arousal
fantasy
social
interaction
Gamification: diverse views
28. The
motivational
model
(Przybylski
et
al.
2010)
explains
engagement
in
games
in
relation
to
the
satisfaction
of
universal
basic
needs:
autonomy
competence
relatedness
needs
Flows
are
engaging
activities
(e.g.,
games)
with
a
balance
between
challenges
and
skills,
and
for
(Kiili
2005)
are
realised
in
games
via:
balanced
challenges
and
skills
timely
usable
feedback
clear
goals
immersive
storylines
intrinsic
rewards
The
“video
game
uses
and
gratifications”
model
(Sherry
&
Lucas
2003)
says
that
different
players
engage
in
games
for
different
gratifications:
competition
challenge
diversion
arousal
fantasy
social
interaction
Gamification: diverse views
29. Which
are
the
preferred
avatars?Which
are
the
preferred
avatars?
Goals: describe
children’s
preferred
avatars
Moves: cards
with
game
consoles
are
in
a
box;
in
turn,
each
player
picks
up
the
cards
of
the
consoles
the
player
uses
and
describes
her/his
preferred
avatars
for
the
consoles
Feedback: a
moderator
assists,
and
provides
children
with
support
if
necessary
Gamified
data
gathering
1
30. Which
are
the
preferred
avatars?Which
are
the
preferred
avatars?
Autonomy: children
are
free
to
par/cipate,
to
say
what
they
wish
Relatedness: each
learner
feels
part
of
the
class
by
telling
about
their
own
experiences
Competence: verbal
skills
Gamified
data
gathering
1
31. Which
are
the
preferred
acGviGes?Which
are
the
preferred
acGviGes?
Goals: describe
children’s
preferred
extracurricular
ac>vi>es
Moves: each
learner
received
a
paper
sheet
with
s>ckers
represen>ng
ac>vi>es
(e.g.,
going
on
the
internet)
and
a
blank
sheet
with
3
empty
circles
represen>ng
morning,
aYernoon
and
evening.
Learners
have
to
paste
s>ckers
into
the
per>nent
circles
or
draw
ac>vi>es.
Feedback: a
moderator
assists,
and
supports
children
if
necessary
Gamified
data
gathering
2
32. Which
are
the
preferred
acGviGes?Which
are
the
preferred
acGviGes?
Autonomy: children
are
free
to
par>cipate
or
not,
to
a[ach
what
they
wish
Relatedness: each
learner
feels
part
of
the
class
by
showing
the
class
their
own
choices
Competence: non-‐verbal
skills
Gamified
data
gathering
2
33. Morale: game over
Pros:
– reliable
and
dependable
data
for
creating
fine-‐grained
learner
profiles
as
triangulated
with
data
from
domain
experts
or
referent
adults
– gamifica>on
of
data
gathering
with
learners
was
engaging
for
children
and
their
teachers
to
the
point
that
– schools
par>cipated
in
the
prosecu>on
of
TERENCE
ac>vi>es
(“let’s
play
again”
effect)
– there
were
no
drop-‐outs
– school
constraints
were
respected
34. Morale: game over
Pros:
– reliable
and
dependable
data
for
creating
fine-‐grained
learner
profiles
as
triangulated
with
data
from
domain
experts
or
referent
adults
– gamifica>on
of
data
gathering
with
learners
was
engaging
for
children
and
their
teachers
to
the
point
that
– schools
par>cipated
in
the
prosecu>on
of
TERENCE
ac>vi>es
(“let’s
play
again”
effect)
– there
were
no
drop-‐outs
– school
constraints
were
respected
Contras:
– considerable
resources
and
personnel
for
construc>ng
data
gathering
material
and
specifying
protocols/storyline
– the
method
leads
to
collec>ng
poorly
structured
huge
diversified
data
which
requires
considerable
analysis
>mes