An Ontology Engineering Approach to Gamify Collaborative Learning Scenarios

1. An
Ontology
Engineering
Approach
to
Gamify
Collabora7ve
Learning
Scenarios
Geiser
Chalco1,
Dilvan
A.
Moreira1,
Riichiro
Mizoguchi2,
and
Seiji
Isotani1
20th
Interna@onal
Conference
on
Collabora@on
and
Technology,
2014
1University
of
São
Paulo,
Brazil.
geiser@usp.br, {dilvan, sisotani}@icmc.usp.br
2Japan
Advanced
Ins@tute
of
Science
and
Technology,
Japan.
mizo@jaist.ac.jp

2. • Introduc@on:
– Concept
of
Gamifica@on
– Problem:
Gamifica@on
in
CL
Scenarios
• Approach:
Ontological
Engineering
– Ontological
Structure
to
Describe
Gamified
CL
Scenarios
• Applica@on
of
Ontological
Structure
• Conclusions
and
Future
Research
Outline
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
2

3. Games
are
part
of
our
life
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
3

4. Games
are
part
of
our
life
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
4
Source:
Entertainment
SoUware
Associa@on's
(2014)
&
Huffingtonpost
(2014)

5. Games
are
part
of
our
life
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
5
Source:
Entertainment
SoUware
Associa@on's
(2014)
&
Huffingtonpost
(2014)

6. Why
does
everyone
enjoy
playing
games?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
6
Engagement
Sa@sfac@on
of
psychological
needs
Solve
problems

7. Why
does
everyone
enjoy
playing
games?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
7
Engagement
Sa@sfac@on
of
psychological
needs
Solve
problems
Games
are
problem-­‐solving
ac7vi7es
(finding
a
way
to
destroy
the
other)
(feeling
successful)

8. Why
does
everyone
enjoy
playing
games?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
8
Engagement
Sa@sfac@on
of
psychological
needs
Solve
problems
Games
are
problem-­‐solving
ac7vi7es
(finding
a
way
to
destroy
the
other)
(feeling
successful)
Games
are
problem-­‐solving
ac7vi7es
approached
with
a
playful
a@tude
(voluntary)
Game
Elements
(endogenous)

9. Why
does
everyone
enjoy
playing
games?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
9
Engagement
Sa@sfac@on
of
psychological
needs
Solve
problems
Games
are
problem-­‐solving
ac7vi7es
(finding
a
way
to
destroy
the
other)
(feeling
successful)
Games
are
problem-­‐solving
ac7vi7es
approached
with
a
playful
a@tude
(voluntary)
Game
Elements
(endogenous)
must
probably
solve
more
problems
to
gain
points
and
to
feel
more
successful
Leaderboards

10. Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
10

11. Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
11

12. Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
12

13. Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
13

14. Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
14

15. What
is
Gamifica@on?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
15
The
use
of
game
design
elements
in
non-­‐game
contexts
(Deterding
et
al.
2011)
Playful
Design
Pervasive
Games
Serious
Games
Gamifica@on

16. What
is
Gamifica@on?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
16
The
use
of
game
design
elements
in
non-­‐game
contexts
(Deterding
et
al.
2011)
Playful
Design
Pervasive
Games
Serious
Games
Gamifica@on
Gaming
Playing
-­‐
Playfulness
Rule-­‐base
systems
that
are
design
to
be
playful

17. What
is
Gamifica@on?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
17
The
use
of
game
design
elements
in
non-­‐game
contexts
(Deterding
et
al.
2011)
Playful
Design
Pervasive
Games
Serious
Games
Gamifica@on
Gaming
Playing
-­‐
Playfulness
Rule-­‐base
systems
that
are
design
to
be
playful
Elements
Whole
How
to
use
game
elements
in
non-­‐
game
applica@on

18. What
is
Gamifica@on?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
18
The
use
of
game
design
elements
in
non-­‐game
contexts
(Deterding
et
al.
2011)
Playful
Design
Pervasive
Games
Serious
Games
Gamifica@on
Gaming
Playing
-­‐
Playfulness
Rule-­‐base
systems
that
are
design
to
be
playful
Elements
Whole
How
to
use
game
elements
in
non-­‐
game
applica@on
Design
of:
• Game
interface
• Game
mechanics
• …

19. Does
Gamifica@on
really
work?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
19

20. Does
Gamifica@on
really
work?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
20

21. Does
Gamifica@on
really
work?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
21
Many
uses
of
gamifica@on
are
incorrect
or
poorly
designed
(Webb,
2013)

22. Does
Gamifica@on
really
work?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
22
Many
uses
of
gamifica@on
are
incorrect
or
poorly
designed
(Webb,
2013)
Reason:
misconcep@on
about
what
mo7vates
a
person
to
con@nue
using
a
gamified
applica@on

23. Does
Gamifica@on
really
work?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
23
Many
uses
of
gamifica@on
are
incorrect
or
poorly
designed
(Webb,
2013)
Reason:
misconcep@on
about
what
mo@vates
a
person
to
con@nue
using
a
game
or
gamified
applica@on

24. Does
Gamifica@on
really
work?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
24
Many
uses
of
gamifica@on
are
incorrect
or
poorly
designed
(Webb,
2013)
Reason:
misconcep@on
about
what
mo@vates
a
person
to
con@nue
using
a
game
or
gamified
applica@on

25. Does
Gamifica@on
really
work?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
25
Many
uses
of
gamifica@on
are
incorrect
or
poorly
designed
(Webb,
2013)
Reason:
misconcep@on
about
what
mo@vates
a
person
to
con@nue
using
a
game
or
gamified
applica@on
(Hamari,
et
al.
2014)
Results
Nro
Studies
All
tests
posi@ve
2
Posi7ve
results
in
part
of
the
tests
13
Only
descrip@ve
7

26. Does
Gamifica@on
really
work?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
26
Many
uses
of
gamifica@on
are
incorrect
or
poorly
designed
(Webb,
2013)
Reason:
misconcep@on
about
what
mo@vates
a
person
to
con@nue
using
a
game
or
gamified
applica@on
(Hamari,
et
al.
2014)
Results
Nro
Studies
All
tests
posi@ve
2
Posi7ve
results
in
part
of
the
tests
13
Only
descrip@ve
7
Context
is
an
essencial

27. Does
Gamifica@on
really
work?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
27
Many
uses
of
gamifica@on
are
incorrect
or
poorly
designed
(Webb,
2013)
Reason:
misconcep@on
about
what
mo@vates
a
person
to
con@nue
using
a
game
or
gamified
applica@on
(Hamari,
et
al.
2014)
Results
Nro
Studies
All
tests
posi@ve
2
Posi7ve
results
in
part
of
the
tests
13
Only
descrip@ve
7
Context
is
an
essencial

28. Does
Gamifica@on
really
work?
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
28
Many
uses
of
gamifica@on
are
incorrect
or
poorly
designed
(Webb,
2013)
Reason:
misconcep@on
about
what
mo@vates
a
person
to
con@nue
using
a
game
or
gamified
applica@on
(Hamari,
et
al.
2014)
Results
Nro
Studies
All
tests
posi@ve
2
Posi7ve
results
in
part
of
the
tests
13
Only
descrip@ve
7
Context
is
an
essencial

29. Problem:
Gamifica@on
in
CL
Scenarios
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
Instruc@onal
Designer
CSCL
Script
(IMS-­‐LD)
CL
Ac@vi@es
(interac@ons)
CL
Scenario
LA
LB
LC
29

30. Problem:
Gamifica@on
in
CL
Scenarios
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
Instruc@onal
Designer
CSCL
Script
(IMS-­‐LD)
CL
Ac@vi@es
(interac@ons)
CL
Scenario
LA
LB
LC
demo7va7on
• Neglect
his
personal
skills
to
complete
a
task
as
it
was
requested
• Sense
of
obliga@on
imposes
by
the
script
30

31. Problem:
Gamifica@on
in
CL
Scenarios
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
Instruc@onal
Designer
CSCL
Script
(IMS-­‐LD)
CL
Ac@vi@es
(interac@ons)
CL
Scenario
LA
LB
LC
nega@ve
aitudes
degrade
dynamics
nega7ve
learning
outcomes
+
demo7va7on
• Neglect
his
personal
skills
to
complete
a
task
as
it
was
requested
• Sense
of
obliga@on
imposes
by
the
script
31

32. Problem:
Gamifica@on
in
CL
Scenarios
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
Instruc@onal
Designer
CSCL
Script
(IMS-­‐LD)
CL
Ac@vi@es
(interac@ons)
CL
Scenario
LA
LB
LC
nega@ve
aitudes
degrade
dynamics
nega7ve
learning
outcomes
+
demo7va7on
• Neglect
his
personal
skills
to
complete
a
task
as
it
was
requested
• Sense
of
obliga@on
imposes
by
the
script
Efficient+
Beneficial
+
32

33. Problem:
Gamifica@on
in
CL
Scenarios
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
Instruc@onal
Designer
CSCL
Script
(IMS-­‐LD)
CL
Ac@vi@es
(interac@ons)
CL
Scenario
LA
LB
LC
nega@ve
aitudes
degrade
dynamics
nega7ve
learning
outcomes
+
demo7va7on
• Neglect
his
personal
skills
to
complete
a
task
as
it
was
requested
• Sense
of
obliga@on
imposes
by
the
script
Efficient+
Beneficial
+
33

34. Problem:
Gamifica@on
in
CL
Scenarios
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
Instruc@onal
Designer
CSCL
Script
(IMS-­‐LD)
CL
Ac@vi@es
(interac@ons)
CL
Scenario
LA
LB
LC
nega@ve
aitudes
degrade
dynamics
nega7ve
learning
outcomes
+
demo7va7on
• Neglect
his
personal
skills
to
complete
a
task
as
it
was
requested
• Sense
of
obliga@on
imposes
by
the
script
Efficient+
Beneficial
+
I
don’t
want
to
game
points…
I
want
to
34

35. Problem:
Gamifica@on
in
CL
Scenarios
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
Instruc@onal
Designer
CSCL
Script
(IMS-­‐LD)
CL
Ac@vi@es
(interac@ons)
CL
Scenario
LA
LB
LC
nega@ve
aitudes
degrade
dynamics
nega7ve
learning
outcomes
+
demo7va7on
• Neglect
his
personal
skills
to
complete
a
task
as
it
was
requested
• Sense
of
obliga@on
imposes
by
the
script
Efficient+
Beneficial
+
I
don’t
want
to
game
points…
I
want
to
Make
social
connec@on
35

36. Problem:
Gamifica@on
in
CL
Scenarios
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
Instruc@onal
Designer
CSCL
Script
(IMS-­‐LD)
CL
Ac@vi@es
(interac@ons)
CL
Scenario
LA
LB
LC
nega@ve
aitudes
degrade
dynamics
nega7ve
learning
outcomes
+
demo7va7on
• Neglect
his
personal
skills
to
complete
a
task
as
it
was
requested
• Sense
of
obliga@on
imposes
by
the
script
Efficient+
Beneficial
+
I
don’t
want
to
game
points…
I
want
to
Make
social
connec@on
Explore
new
challenges
36

37. Problem:
Gamifica@on
in
CL
Scenarios
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
Instruc@onal
Designer
CSCL
Script
(IMS-­‐LD)
CL
Ac@vi@es
(interac@ons)
CL
Scenario
LA
LB
LC
nega@ve
aitudes
degrade
dynamics
nega7ve
learning
outcomes
+
demo7va7on
• Neglect
his
personal
skills
to
complete
a
task
as
it
was
requested
• Sense
of
obliga@on
imposes
by
the
script
Efficient+
Beneficial
+
I
don’t
want
to
game
points…
I
want
to
Make
social
connec@on
Explore
new
challenges
WIN!
37

38. Problem:
Gamifica@on
in
CL
Scenarios
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
Instruc@onal
Designer
CSCL
Script
(IMS-­‐LD)
CL
Ac@vi@es
(interac@ons)
CL
Scenario
LA
LB
LC
nega@ve
aitudes
degrade
dynamics
nega7ve
learning
outcomes
+
demo7va7on
• Neglect
his
personal
skills
to
complete
a
task
as
it
was
requested
• Sense
of
obliga@on
imposes
by
the
script
Efficient+
Beneficial
+
I
don’t
want
to
game
points…
I
want
to
Make
social
connec@on
Explore
new
challenges
WIN!
38

39. Problem:
Gamifica@on
in
CL
Scenarios
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
Instruc@onal
Designer
CSCL
Script
(IMS-­‐LD)
CL
Ac@vi@es
(interac@ons)
CL
Scenario
LA
LB
LC
nega@ve
aitudes
degrade
dynamics
nega7ve
learning
outcomes
+
demo7va7on
• Neglect
his
personal
skills
to
complete
a
task
as
it
was
requested
• Sense
of
obliga@on
imposes
by
the
script
Efficient+
Beneficial
+
I
don’t
want
to
game
points…
I
want
to
Make
social
connec@on
Explore
new
challenges
WIN!
Tests
39

40. Problem:
Gamifica@on
in
CL
Scenarios
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
Instruc@onal
Designer
CSCL
Script
(IMS-­‐LD)
CL
Ac@vi@es
(interac@ons)
CL
Scenario
LA
LB
LC
nega@ve
aitudes
degrade
dynamics
nega7ve
learning
outcomes
+
demo7va7on
• Neglect
his
personal
skills
to
complete
a
task
as
it
was
requested
• Sense
of
obliga@on
imposes
by
the
script
Efficient+
Beneficial
+
I
don’t
want
to
game
points…
I
want
to
Make
social
connec@on
Explore
new
challenges
WIN!
Tests
40

41. Problem:
Gamifica@on
in
CL
Scenarios
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
Instruc@onal
Designer
CSCL
Script
(IMS-­‐LD)
CL
Ac@vi@es
(interac@ons)
CL
Scenario
LA
LB
LC
nega@ve
aitudes
degrade
dynamics
nega7ve
learning
outcomes
+
demo7va7on
• Neglect
his
personal
skills
to
complete
a
task
as
it
was
requested
• Sense
of
obliga@on
imposes
by
the
script
Efficient+
Beneficial
+
I
don’t
want
to
game
points…
I
want
to
Make
social
connec@on
Explore
new
challenges
WIN!
Tests
Context
and
needs
of
learners
change
41

42. Approach:
Ontological
Engineering
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
42
Ontologies
(Structures)
Knowledge
Bases
(Models)
Best
Prac7ces
and
Theories
of
Gamifica7on
Describe
informa@on
Support
for
the
development
of
Instr.
designer/
teacher/researcher
Ø design
gamified
CL
scenarios
Ø evaluate
the
prac@ces
and
theories
Ø es@mate
and
calculate
the
benefits
Ontology-­‐aware
systems

43. From
CL
Scenario
To
Gamified
CL
Scenario
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
43
Gamifed
CL
Scenario
CL
Scenario
Y<=I-­‐goal
I-­‐goal
W(A)-­‐goal
Learning
Strategy
*
Learner
I-­‐role
Learner
You-­‐role
I-­‐goal
CL
process
*
G
W(L)-­‐goal
Common
goal
*
Interact
Parern
Teaching-­‐learning
process
*

44. From
CL
Scenario
To
Gamified
CL
Scenario
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
44
Gamifed
CL
Scenario
Modeling
of Learner's
Development
Learner
Growth
Model
(Isotani
&
Mizoguchi,
2007)
CL
Scenario
Y<=I-­‐goal
I-­‐goal
W(A)-­‐goal
Learning
Strategy
*
Learner
I-­‐role
Learner
You-­‐role
I-­‐goal
CL
process
*
G
W(L)-­‐goal
Common
goal
*
Interact
Parern
Teaching-­‐learning
process
*

45. From
CL
Scenario
To
Gamified
CL
Scenario
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
45
Gamifed
CL
Scenario
Modeling
of Learner's
Development
Learner
Growth
Model
(Isotani
&
Mizoguchi,
2007)
Formation
of Effective
Groups
Learners
Effec@ve
Groups
(Isotani
et
al.,
2009)
CL
Scenario
Y<=I-­‐goal
I-­‐goal
W(A)-­‐goal
Learning
Strategy
*
Learner
I-­‐role
Learner
You-­‐role
I-­‐goal
CL
process
*
G
W(L)-­‐goal
Common
goal
*
Interact
Parern
Teaching-­‐learning
process
*

46. From
CL
Scenario
To
Gamified
CL
Scenario
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
46
Gamifed
CL
Scenario
Modeling
of Learner's
Development
Learner
Growth
Model
(Isotani
&
Mizoguchi,
2007)
Formation
of Effective
Groups
Learners
Effec@ve
Groups
(Isotani
et
al.,
2009)
Design of
CL Scenarios
LA LB
Tutor Tutee
ü Learning
Strategies
ü Learning
Goals
ü Group
Goals
ü Roles
(Isotani
et
al.,
2013)
CL
Scenario
Y<=I-­‐goal
I-­‐goal
W(A)-­‐goal
Learning
Strategy
*
Learner
I-­‐role
Learner
You-­‐role
I-­‐goal
CL
process
*
G
W(L)-­‐goal
Common
goal
*
Interact
Parern
Teaching-­‐learning
process
*

47. From
CL
Scenario
To
Gamified
CL
Scenario
47
Sept.
9,
2014
Modeling
of Learner's
Development
Formation
of Effective
Groups
Design of
CL Scenarios
Apply
Gamification
CL
Scenario
Y<=I-­‐goal
I-­‐goal
W(A)-­‐goal
Learning
Strategy
*
Learner
I-­‐role
Learner
You-­‐role
I-­‐goal
CL
process
*
G
W(L)-­‐goal
Common
goal
*
Interact
Parern
Teaching-­‐learning
process
*
LA LB
Tutor Tutee
“the
use
of
game
design
elements
in
non-­‐game
…”
Gamifed
CL
Scenario
An
Ontology
to
Gamify
CL
Scenarios
Unlockable
System
Point
System
Badge
System

48. From
CL
Scenario
To
Gamified
CL
Scenario
48
Sept.
9,
2014
Modeling
of Learner's
Development
Formation
of Effective
Groups
Design of
CL Scenarios
Apply
Gamification
CL
Scenario
Y<=I-­‐goal
I-­‐goal
W(A)-­‐goal
Learning
Strategy
*
Learner
I-­‐role
Learner
You-­‐role
I-­‐goal
CL
process
*
G
W(L)-­‐goal
Common
goal
*
Interact
Parern
Teaching-­‐learning
process
*
LA LB
Tutor Tutee
“the
use
of
game
design
elements
in
non-­‐game
…”
• What
game
mechanics
must
be
used
to
mo7vate
the
learners?
Gamifed
CL
Scenario
Only:
design
of
game
mechanics
An
Ontology
to
Gamify
CL
Scenarios
Unlockable
System
Point
System
Badge
System

49. LA LB
Mo@va@on
and
Game
Mechanics
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
49
Mo@va@on
is
the
process
used
to
allocate
energy
to
maximize
the
sa7sfac7on
of
needs
(Pritchard
&
Ashwood,
2008).
Behavior
Needs Satisfaction

50. LA LB
Mo@va@on
and
Game
Mechanics
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
50
Mo@va@on
is
the
process
used
to
allocate
energy
to
maximize
the
sa7sfac7on
of
needs
(Pritchard
&
Ashwood,
2008).
Behavior
Needs Satisfaction
Game
elements

51. LA LB
Mo@va@on
and
Game
Mechanics
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
51
Mo@va@on
is
the
process
used
to
allocate
energy
to
maximize
the
sa7sfac7on
of
needs
(Pritchard
&
Ashwood,
2008).
Behavior
Needs Satisfaction
Game
elements
change
or
intensify
his
needs

52. LA LB
Mo@va@on
and
Game
Mechanics
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
52
Mo@va@on
is
the
process
used
to
allocate
energy
to
maximize
the
sa7sfac7on
of
needs
(Pritchard
&
Ashwood,
2008).
Behavior
Needs Satisfaction
Game
elements
change
or
intensify
his
needs
The
proper
combina@on
of
different
game
elements
provides
an
adequate
environment
for
all
learners.

53. LA LB
Mo@va@on
and
Game
Mechanics
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
53
Mo@va@on
is
the
process
used
to
allocate
energy
to
maximize
the
sa7sfac7on
of
needs
(Pritchard
&
Ashwood,
2008).
Behavior
Needs Satisfaction
Game
elements
change
or
intensify
his
needs
The
proper
combina@on
of
different
game
elements
provides
an
adequate
environment
for
all
learners.
• Game
mechanics(GM):
inputs
(CL
scenario)
-­‐>
output
(gaming)
Game
mechanics

54. LA LB
Mo@va@on
and
Game
Mechanics
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
54
Mo@va@on
is
the
process
used
to
allocate
energy
to
maximize
the
sa7sfac7on
of
needs
(Pritchard
&
Ashwood,
2008).
Behavior
Needs Satisfaction
Game
elements
change
or
intensify
his
needs
The
proper
combina@on
of
different
game
elements
provides
an
adequate
environment
for
all
learners.
• Game
mechanics(GM):
inputs
(CL
scenario)
-­‐>
output
(gaming)
Game
mechanics
Point
System

55. LA LB
Mo@va@on
and
Game
Mechanics
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
55
Mo@va@on
is
the
process
used
to
allocate
energy
to
maximize
the
sa7sfac7on
of
needs
(Pritchard
&
Ashwood,
2008).
Behavior
Needs Satisfaction
Game
elements
change
or
intensify
his
needs
The
proper
combina@on
of
different
game
elements
provides
an
adequate
environment
for
all
learners.
• Game
mechanics(GM):
inputs
(CL
scenario)
-­‐>
output
(gaming)
Game
mechanics
Point
System
Social
Connec@on

56. LA LB
Mo@va@on
and
Game
Mechanics
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
56
Mo@va@on
is
the
process
used
to
allocate
energy
to
maximize
the
sa7sfac7on
of
needs
(Pritchard
&
Ashwood,
2008).
Behavior
Needs Satisfaction
Game
elements
change
or
intensify
his
needs
The
proper
combina@on
of
different
game
elements
provides
an
adequate
environment
for
all
learners.
• Game
mechanics(GM):
inputs
(CL
scenario)
-­‐>
output
(gaming)
Game
mechanics
Point
System
Social
Connec@on
demonstrate
mastery
relatedness

57. LA LB
Mo@va@on
and
Game
Mechanics
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
57
Mo@va@on
is
the
process
used
to
allocate
energy
to
maximize
the
sa7sfac7on
of
needs
(Pritchard
&
Ashwood,
2008).
Behavior
Needs Satisfaction
Game
elements
change
or
intensify
his
needs
The
proper
combina@on
of
different
game
elements
provides
an
adequate
environment
for
all
learners.
• Game
mechanics(GM):
inputs
(CL
scenario)
-­‐>
output
(gaming)
Game
mechanics
Point
System
Social
Connec@on
demonstrate
mastery
relatedness
Every
GM
is
Customized
(ind.needs)
-­‐>
Increase
his
liking
for
CL
Ac@vi@es
Internaliza@on
of
mo@va@on

58. I-­‐mot
goal:
Individual
mo@va@onal
goal
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
58
Behavior
Needs Satisfaction
Game
elements
Ind. motivational goal
Internaliza@on
of
mo@va@on
Sa@sfac@on
of
needs
*
An
individual
mo7va7onal
goal
represents
the
expected
changes
on
the
mind
of
a
learner
using
game
mechanics.
Game
mechanics

59. I-­‐mot
goal:
Individual
mo@va@onal
goal
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
59
Behavior
Needs Satisfaction
Game
elements
Ind. motivational goal
Internaliza@on
of
mo@va@on
Sa@sfac@on
of
needs
*
An
individual
mo7va7onal
goal
represents
the
expected
changes
on
the
mind
of
a
learner
using
game
mechanics.
• Amo@va@on
-­‐>
External
Reg.
• (External
Mot.
-­‐>
Intrinsic
Mot.)
• External
Reg.
-­‐>
Introjected
Reg.
• Introjected
Reg.
-­‐>
Iden@fied
Reg.
• Iden@fied
Reg.
-­‐>
Integrated
Reg.
• Integrated
Reg.
-­‐>
Intrinsic
Reg.
Self-­‐determina@on
Theory
(Deci
&
Ryan,
2010)
Game
mechanics

60. I-­‐mot
goal:
Individual
mo@va@onal
goal
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
60
Behavior
Needs Satisfaction
Game
elements
Ind. motivational goal
Internaliza@on
of
mo@va@on
Sa@sfac@on
of
needs
*
An
individual
mo7va7onal
goal
represents
the
expected
changes
on
the
mind
of
a
learner
using
game
mechanics.
• Sa@sfac@on
of
Autonomy
• Sa@sfac@on
of
Relatedness
• Sa@sfac@on
of
Competence
• Sa@sfac@on
of
Purpose
• Sa@sfac@on
of
Mastery
• Amo@va@on
-­‐>
External
Reg.
• (External
Mot.
-­‐>
Intrinsic
Mot.)
• External
Reg.
-­‐>
Introjected
Reg.
• Introjected
Reg.
-­‐>
Iden@fied
Reg.
• Iden@fied
Reg.
-­‐>
Integrated
Reg.
• Integrated
Reg.
-­‐>
Intrinsic
Reg.
Self-­‐determina@on
Theory
(Deci
&
Ryan,
2010)
Self-­‐determina@on
Theory
(Deci
&
Ryan,
2010)
Pink
Dan
(2011)
Competence
Relatedness
Autonomy
Purpose
Autonomy
Mastery
Game
mechanics

61. Player
Role:
Playing
style
(Ind.
Pers.
Trait)
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
61
Behavior
Needs Satisfaction
Game
elements
Game
mechanics
Ind. motivation goal
Playing styles
(Ind. traits) Models
of:
• 7
Player
Types
(Laws,
2002)
• 4
Player
Types
(Bartle,
2004)
• 8
Player
Types
(Marczewski,
2013)
…

62. Player
Role:
Playing
style
(Ind.
Pers.
Trait)
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
62
Behavior
Needs Satisfaction
Game
elements
Game
mechanics
Ind. motivation goal
Playing styles
(Ind. traits) Models
of:
• 7
Player
Types
(Laws,
2002)
• 4
Player
Types
(Bartle,
2004)
• 8
Player
Types
(Marczewski,
2013)
…
The
playing
styles
are
individual
personality
traits
that
define
the
preferences
of
a
person
when
he/she
is
playing
a
game.

63. Player
Role:
Playing
style
(Ind.
Pers.
Trait)
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
63
Behavior
Needs Satisfaction
Game
elements
Game
mechanics
Ind. motivation goal
Playing styles
(Ind. traits) Models
of:
• 7
Player
Types
(Laws,
2002)
• 4
Player
Types
(Bartle,
2004)
• 8
Player
Types
(Marczewski,
2013)
…
The
playing
styles
are
individual
personality
traits
that
define
the
preferences
of
a
person
when
he/she
is
playing
a
game.
user-­‐orienta5on
(interac5ng
with
others)
system-­‐orienta5on
(exploring
the
game)
Interac5on-­‐orienta5on
(interac5ng
inside)
act-­‐orienta5on
(having
influence
outside)
(Socializer)
(Explorer)
(Achiever)
(Killer)
(Bartle,
2004)
4
Player
Types

64. Player
Role:
Models
of
player
types
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
64
Behavior
Needs Satisfaction
Game
elements
Game
mechanics
Ind. motivation goal
Playing styles
(Ind. traits)
LA LB
Player
Role
Mo@va@on
stage
Necessary
condi@on
*
Psychological
need
Necessary
condi@on
*
Playing
style
Desired
condi@on
*
Player
Role
A
Player
Role
defines
the
necessary
and
desired
condi7ons
that
a
learner
must
have
to
play
a
player
type.

65. Y<=I-­‐mot
goal:
Mo@va@onal
strategy
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
65
Behavior
Needs Satisfaction
Game
elements
Game
mechanics
Ind. motivation goal
Playing styles
(Ind. traits)
LA LB
Player
Role
The
Y<=I-­‐mot
goal
is
the
mo7va7onal
strategy
that
will
be
used
by
game
elements
to
enhance
the
learning
strategy
employed
by
a
learner
in
focus.
Motivational
Strategy
Y<=I-­‐mot
goal
Enhance
(learning
strategy)

66. Y<=I-­‐mot
goal:
Mo@va@onal
strategy
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
66
Behavior
Needs Satisfaction
Game
elements
Game
mechanics
Ind. motivation goal
Playing styles
(Ind. traits)
LA LB
Player
Role
The
Y<=I-­‐mot
goal
is
the
mo7va7onal
strategy
that
will
be
used
by
game
elements
to
enhance
the
learning
strategy
employed
by
a
learner
in
focus.
Motivational
Strategy
Y<=I-­‐mot
goal
Enhance
(learning
strategy)
influence
the
design
of

67. Y<=I-­‐mot
goal:
Mo@va@onal
strategy
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
67
Behavior
Needs Satisfaction
Game
elements
Game
mechanics
Ind. motivation goal
Playing styles
(Ind. traits)
LA LB
Player
Role
The
Y<=I-­‐mot
goal
is
the
mo7va7onal
strategy
that
will
be
used
by
game
elements
to
enhance
the
learning
strategy
employed
by
a
learner
in
focus.
Motivational
Strategy
Y<=I-­‐mot
goal
Enhance
(learning
strategy)
Learner
I-­‐player
role
influence
the
design
of

68. Y<=I-­‐mot
goal:
Mo@va@onal
strategy
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
68
Behavior
Needs Satisfaction
Game
elements
Game
mechanics
Ind. motivation goal
Playing styles
(Ind. traits)
LA LB
Player
Role
The
Y<=I-­‐mot
goal
is
the
mo7va7onal
strategy
that
will
be
used
by
game
elements
to
enhance
the
learning
strategy
employed
by
a
learner
in
focus.
Motivational
Strategy
Y<=I-­‐mot
goal
Enhance
(learning
strategy)
Learner
You-­‐player
role
Learner
I-­‐player
role
influence
the
design
of

69. Y<=I-­‐mot
goal:
Mo@va@onal
strategy
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
69
Behavior
Needs Satisfaction
Game
elements
Game
mechanics
Ind. motivation goal
Playing styles
(Ind. traits)
LA LB
Player
Role
The
Y<=I-­‐mot
goal
is
the
mo7va7onal
strategy
that
will
be
used
by
game
elements
to
enhance
the
learning
strategy
employed
by
a
learner
in
focus.
Motivational
Strategy
Y<=I-­‐mot
goal
Enhance
(learning
strategy)
Learner
You-­‐player
role
Learner
I-­‐player
role
I-­‐mot
goal
I-­‐mot
goal
*
influence
the
design
of

70. I-­‐gameplay:
Gameplay
Strategy
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
70
Gameplay
Behavior
Needs Satisfaction
Game
elements
Game
mechanics
Ind. motivation goal
Playing styles
(Ind. traits)
Player
Role
Motivational
Strategy
LA LB
The
gameplay
strategy
is
the
ra@onal
arrangement
among
player
roles,
mo7va7onal
strategies
and
game
mechanics.
I-­‐gameplay
P-­‐Player
Role
Primary
focus
1
Y<=I-­‐mot
goal
S<=P-­‐mot
goal
1
Game
mechanics
What
use
*

71. I-­‐gameplay:
Gameplay
Strategy
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
71
Gameplay
Behavior
Needs Satisfaction
Game
elements
Game
mechanics
Ind. motivation goal
Playing styles
(Ind. traits)
Player
Role
Motivational
Strategy
LA LB
The
gameplay
strategy
is
the
ra@onal
arrangement
among
player
roles,
mo7va7onal
strategies
and
game
mechanics.
I-­‐gameplay
P-­‐Player
Role
Primary
focus
1
Y<=I-­‐mot
goal
S<=P-­‐mot
goal
1
Game
mechanics
What
use
*
Models
of
Player
Types
classify
&
decide

72. From
CL
Scenario
To
Gamified
CL
Scenario
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
72
CL
Scenario
Y<=I-­‐goal
W(A)-­‐goal
Learning
Strategy
*
CL
process
*
Y<=I-­‐goal
Learning
Strategy
*
Gamified
CL
Scenario
is
a
I-­‐mot
goal
Y<=I-­‐mot
goal
Mo@va@onal
Strategy
*
Learner
I-­‐player
role
Learner
You-­‐player
role
I-­‐mot
goal
*
G
Gameplay
strategy
I-­‐gameplay
*
Game
mechanics
What
use
*

73. From
CL
Scenario
To
Gamified
CL
Scenario
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
73
Enhance
CL
Scenario
Y<=I-­‐goal
W(A)-­‐goal
Learning
Strategy
*
CL
process
*
Y<=I-­‐goal
Learning
Strategy
*
Gamified
CL
Scenario
is
a
I-­‐mot
goal
Y<=I-­‐mot
goal
Mo@va@onal
Strategy
*
Learner
I-­‐player
role
Learner
You-­‐player
role
I-­‐mot
goal
*
G
Gameplay
strategy
I-­‐gameplay
*
Game
mechanics
What
use
*

74. From
CL
Scenario
To
Gamified
CL
Scenario
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
74
Enhance
CL
Scenario
Y<=I-­‐goal
W(A)-­‐goal
Learning
Strategy
*
CL
process
*
Y<=I-­‐goal
Learning
Strategy
*
Gamified
CL
Scenario
Player
Role
Mo@va@on
stage
Necessary
condi@on
*
Psychological
need
Necessary
condi@on
*
Playing
style
Desired
condi@on
*
is
a
I-­‐mot
goal
Y<=I-­‐mot
goal
Mo@va@onal
Strategy
*
Learner
I-­‐player
role
Learner
You-­‐player
role
I-­‐mot
goal
*
G
Gameplay
strategy
I-­‐gameplay
*
Game
mechanics
What
use
*

75. From
CL
Scenario
To
Gamified
CL
Scenario
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
75
Enhance
CL
Scenario
Y<=I-­‐goal
W(A)-­‐goal
Learning
Strategy
*
CL
process
*
Y<=I-­‐goal
Learning
Strategy
*
Gamified
CL
Scenario
Player
Role
Mo@va@on
stage
Necessary
condi@on
*
Psychological
need
Necessary
condi@on
*
Playing
style
Desired
condi@on
*
is
a
I-­‐mot
goal
Y<=I-­‐mot
goal
Mo@va@onal
Strategy
*
Learner
I-­‐player
role
Learner
You-­‐player
role
I-­‐mot
goal
*
G
Gameplay
strategy
I-­‐gameplay
*
Game
mechanics
What
use
*
the
proper
player
types
and
game
mechanics
for
each
learner
Applica@on
LA LB

76. Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
76
Applica@on
of
Ontological
Structure
(Socializer)
(Killer)
(Explorer)
Player
Types
(Bartle,
2004)
(Achiever)

77. Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
77
Player
Role
Mo@va@on
stage
Necessary
condi@on
*
Psychological
need
Necessary
condi@on
*
Playing
style
Desired
condi@on
*
Enhance
Y<=I-­‐goal
Learning
Strategy
*
Gamified
CL
Scenario
I-­‐mot
goal
Y<=I-­‐mot
goal
Mo@va@onal
Strategy
*
Learner
I-­‐player
role
Learner
You-­‐player
role
I-­‐mot
goal
*
G
Gameplay
strategy
I-­‐gameplay
*
Game
mechanics
What
use
*

78. Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
78
Player
Role
Mo@va@on
stage
Necessary
condi@on
*
Psychological
need
Necessary
condi@on
*
Playing
style
Desired
condi@on
*
Enhance
Y<=I-­‐goal
Learning
Strategy
*
Gamified
CL
Scenario
I-­‐mot
goal
Y<=I-­‐mot
goal
Mo@va@onal
Strategy
*
Learner
I-­‐player
role
Learner
You-­‐player
role
I-­‐mot
goal
*
G
Gameplay
strategy
I-­‐gameplay
*
Game
mechanics
What
use
*

79. Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
79
Applica@on
N1:
mastery
N2:
relatedness
N3:
autonomy
LA LB
psychological
needs
N2
N1
I1:
system-­‐orienta@on
I2:
ac@ng-­‐orienta@on
I3:
interac@ng-­‐orienta@on
(1)
Select
the
scenarios
that
sa@sfy
the
learners’
needs
by
looking
the
ind.
mot.
goal

80. Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
80
Applica@on
N1:
mastery
N2:
relatedness
N3:
autonomy
LA LB
psychological
needs
N2
N1
I1:
system-­‐orienta@on
I2:
ac@ng-­‐orienta@on
I3:
interac@ng-­‐orienta@on
sa7sfies

81. Sept.
9,
2014
N1:
mastery
N2:
relatedness
N3:
autonomy
I1:
system-­‐orienta@on
I2:
ac@ng-­‐orienta@on
I3:
interac@ng-­‐orienta@on
An
Ontology
to
Gamify
CL
Scenarios
81
Applica@on
LA LB
psychological
needs
N2
N1
(2)
Checking
the
necessary
condi@ons
to
play
a
player
type,
and
seing
the
priority
using
the
desired
condi@ons

82. Sept.
9,
2014
N1:
mastery
N2:
relatedness
N3:
autonomy
I1:
system-­‐orienta@on
I2:
ac@ng-­‐orienta@on
I3:
interac@ng-­‐orienta@on
An
Ontology
to
Gamify
CL
Scenarios
82
Applica@on
LA LB
psychological
needs
N2
N1
ok
more
priority
ok
ok
ind.
pers.
traits
I2
I1
sa7sfies

83. Sept.
9,
2014
N1:
mastery
N2:
relatedness
N3:
autonomy
I1:
system-­‐orienta@on
I2:
ac@ng-­‐orienta@on
I3:
interac@ng-­‐orienta@on
(3)
Seing
the
player
type
if
no
one
constraint
is
violated
in
the
mot.
strategy
An
Ontology
to
Gamify
CL
Scenarios
83
Applica@on
LA LB
more
priority

84. Sept.
9,
2014
N1:
mastery
N2:
relatedness
N3:
autonomy
I1:
system-­‐orienta@on
I2:
ac@ng-­‐orienta@on
I3:
interac@ng-­‐orienta@on
An
Ontology
to
Gamify
CL
Scenarios
84
Applica@on
LA LB
more
priority

85. Sept.
9,
2014
N1:
mastery
N2:
relatedness
N3:
autonomy
I1:
system-­‐orienta@on
I2:
ac@ng-­‐orienta@on
I3:
interac@ng-­‐orienta@on
(4)
Seing
the
proper
game
mechanics
using
the
structure
gameplay
An
Ontology
to
Gamify
CL
Scenarios
85
Applica@on
LA LB
more
priority

86. N1:
mastery
N2:
relatedness
N3:
autonomy
I1:
system-­‐orienta@on
I2:
ac@ng-­‐orienta@on
I3:
interac@ng-­‐orienta@on
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
86
Applica@on
LA LB
psychological
needs
N3
N1

87. N1:
mastery
N2:
relatedness
N3:
autonomy
I1:
system-­‐orienta@on
I2:
ac@ng-­‐orienta@on
I3:
interac@ng-­‐orienta@on
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
87
Applica@on
LA LB
ok
more
priority
ok
ok
ind.
pers.
traits
I3
I1
psychological
needs
N3
N1

88. N1:
mastery
N2:
relatedness
N3:
autonomy
I1:
system-­‐orienta@on
I2:
ac@ng-­‐orienta@on
I3:
interac@ng-­‐orienta@on
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
88
Applica@on
LA LB
more
priority

89. Conclusions
and
Future
Research
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
89
• We
proposed
an
ontology
engineering
approach
to
overcome
the
difficul@es
to
apply
gamifica@on
in
CL
scenarios;
• We
made
the
connec@on
among
psychological
needs,
playing
styles
and
game
mechanics
to
define
our
ontology;
• We
shown
an
example
of
applica@on
using
the
current
version
of
our
approach;
Gameplay
Behavior
Needs Satisfaction
Game
elements
Game
mechanics
Ind. motivation goal
Playing styles
(Ind. traits)
Player
Role
Motivational
Strategy

90. Conclusions
and
Future
Research
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
90
• We
proposed
an
ontology
engineering
approach
to
overcome
the
difficul@es
to
apply
gamifica@on
in
CL
scenarios;
• We
made
the
connec@on
among
psychological
needs,
playing
styles
and
game
mechanics
to
define
our
ontology;
• We
shown
an
example
of
applica@on
using
the
current
version
of
our
approach;
Gameplay
Behavior
Needs Satisfaction
Game
elements
Game
mechanics
Ind. motivation goal
Playing styles
(Ind. traits)
Player
Role
Motivational
Strategy
Affective states
Game
dynamics
Game
interfaces
• Future
works:
We
will
complete
the
modeling
of
Gamified
CL
Scenarios,
including:
• Design
of
game
dynamics
• Design
of
game
interfaces
• Design
of
game
models
• …

91. • Challco,
G.
C.,
Moreira,
D.,
Mizoguchi,
R.,
&
Isotani,
S.
(2014,
January).
Towards
an
Ontology
for
Gamifying
Collabora@ve
Learning
Scenarios.
In
Intelligent
Tutoring
Systems
(pp.
404-­‐409).
Springer
Interna@onal
Publishing.
• Schell,
J.
(2008).
The
Art
of
Game
Design:
A
book
of
lenses.
CRC
Press.
• Deterding,
S.,
Dixon,
D.,
Khaled,
R.,
&
Nacke,
L.
(2011,
September).
From
game
design
elements
to
gamefulness:
defining
gamifica@on.
In
Proceedings
of
the
15th
Interna5onal
Academic
MindTrek
Conference:
Envisioning
Future
Media
Environments
(pp.
9-­‐15).
ACM.
• Webb,
E.
N.
(2013).
Gamifica@on:
When
It
Works,
When
It
Doesn’t.
In
Design,
User
Experience,
and
Usability.
Health,
Learning,
Playing,
Cultural,
and
Cross-­‐
Cultural
User
Experience
(pp.
608–614).
Springer.
• Hamari,
J.,
Koivisto,
J.,
&
Sarsa,
H.
(2014,
January).
Does
Gamifica@on
Work?
-­‐
A
Literature
Review
of
Empirical
Studies
on
Gamifica@on.
In
System
Sciences
(HICSS),
2014
47th
Hawaii
Interna5onal
Conference
on
(pp.
3025-­‐3034).
IEEE.
• Isotani,
S.,
&
Mizoguchi,
R.
(2007).
Deployment
of
ontologies
for
an
effec@ve
design
of
collabora@ve
learning
scenarios.
In
Groupware:
Design,
Implementa@on,
and
Use
(pp.
223–238).
Springer.
References
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
91

92. • Isotani,
S.,
Inaba,
A.,
Ikeda,
M.,
&
Mizoguchi,
R.
(2009).
An
ontology
engineering
approach
to
the
realiza@on
of
theory-­‐driven
group
forma@on.
Interna@onal
Journal
of
Computer-­‐Supported
Collabora@ve
Learning,
4(4),
445–478.
• Isotani,
S.,
Mizoguchi,
R.,
Isotani,
S.,
Capeli,
O.
M.,
Isotani,
N.,
De
Albuquerque,
A.
R.,
...
&
Jaques,
P.
(2013).
A
Seman@c
Web-­‐based
authoring
tool
to
facilitate
the
planning
of
collabora@ve
learning
scenarios
compliant
with
learning
theories.
Computers
&
Educa5on,
63,
267-­‐284.
• Pritchard,
R.,
&
Ashwood,
E.
(2008).
Managing
mo5va5on:
A
manager's
guide
to
diagnosing
and
improving
mo5va5on.
Psychology
Press.
• Deci,
E.
L.,
&
Ryan,
R.
M.
(2010).
Self-­‐Determina5on.
John
Wiley
&
Sons,
Inc..
• Pink,
D.
H.
(2011).
Drive:
The
surprising
truth
about
what
mo5vates
us.
Penguin..
• Laws,
R.
D.
(2002).
Robin's
Laws
of
good
game
mastering.
Steve
Jackson
Games.
• Bartle,
R.
A.
(2004).
Designing
virtual
worlds.
New
Riders
• Marczewski,
A.
(2013).
Gamifica5on:
a
simple
introduc5on.
Andrzej
Marczewski.
References
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
92

93. Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
93
References
Logo
3

94. Ontological
Structure
for
CL
Scenarios
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
94
CL
Scenario
Y<=I-­‐goal
I-­‐goal
W(A)-­‐goal
Learning
Strategy
*
Learner
I-­‐role
Learner
You-­‐role
I-­‐goal
CL
process
*
G
W(L)-­‐goal
Common
goal
*
Interact
Parern
Teaching-­‐learning
process
*
I-Role
(Role Concept)
Learning Strategy
(Context)
depend on
Learner
(Potential Player)
playing
I-Role-1 Geiser
(Role-playing thing)
Learning by
Teaching Tutor
(Role-Holder)
Tutor-1
The
model
of
roles
(Mizoguchi
et
al.,
2007)
proposes
the
division
of
Role
in:
• Role
Concept
• Poten@al
Player
• Role-­‐playing
thing
• Role
Holder

95. I-­‐mot
goal:
Internaliza@on
of
mo@va@on
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
95
Behavior
Needs Satisfaction
Game
elements
Game
mechanics
Ind. motivation goal
Self-­‐determina@on
Theory
(Deci
&
Ryan,
2010)
…
from
…
to
LA LB
I-­‐mot
goal
Internaliza@on
of
mo@va@on
Ini@al
stage
Goal
stage
Mo@va@on
stage
Mo@va@on
stage
is
a
is
a
Sa@sfac@on
of
need
*

96. I-­‐mot
goal:
Sa@sfac@on
of
needs
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
96
Behavior
Needs Satisfaction
Game
elements
Game
mechanics
Ind. motivation goal
Self-­‐determina@on
Theory
(Deci
&
Ryan,
2010)
LA LB
I-­‐mot
goal
Internaliza@on
of
mo@va@on
is
a
is
a
*
Ini@al
stage
without
need
Psychological
need
Goal
stage
Sa@sfac@on
of
need
Purpose
Autonomy
Mastery
Competence
Relatedness
Autonomy
Pink
Dan
(2011)

97. Applica@on
of
Ontological
Structure
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
97
Y<=I-­‐goal
I-­‐mot
goal
Y<=I-­‐mot
goal
Learning
Strategy
*
Mo@va@on
Strategy
*
Learner
I-­‐player
role
Learner
You-­‐player
role
I-­‐mot
goal
*
G
Applica@on
N1:
mastery
N2:
relatedness
N3:
autonomy
Gameplay
strategy
I-­‐gameplay
*
Game
mechanics
What
use
*
Enhance
Gamified
CL
Scenario
LA LB
(2)
checking
the
necessary
condi@ons
to
play
the
player
roles
and
seing
the
priority
of
scenarios
employing
the
desired
condi@ons
psychological
needs
N2
N1
Can
play
ind.
pers.
traits
I2
I1
Set
priority
I1:
interact-­‐orienta@on
I2:
user-­‐orienta@on
I3:
system-­‐orienta@on
Can
play
Set
priority
psychological
needs
ind.
pers.
traits
I3
I1
N3
N1

98. Applica@on
of
Ontological
Structure
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
98
Y<=I-­‐goal
I-­‐mot
goal
Y<=I-­‐mot
goal
Learning
Strategy
*
Mo@va@on
Strategy
*
Learner
I-­‐player
role
Learner
You-­‐player
role
I-­‐mot
goal
*
G
Applica@on
S1:
Scenario
for
socializa@on
S2:
Scenario
for
achievement
S3:
Scenario
for
explora@on
Gameplay
strategy
I-­‐gameplay
*
Game
mechanics
What
use
*
Enhance
Gamified
CL
Scenario
LA LB
(3)
checking
the
constraint
for
all
learners,
and
seing
the
player
type
if
no
one
constraint
is
violated
in
the
selected
scenarios
Can
play
Set
player
role
S1
à
S2
S3
à
S2
priority
stack
for
LA
priority
stack
for
LB
Selected
scenarios

99. Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
99
more
priority
less
priority
more
priority
less
priority
ok
ok
ok
ok
ok
ok
ok
ok
ok
L(A)
L(A)
L(B)
L(B)
L(B)
can’t
play
the
socializer
role

100. Applica@on
of
Ontological
Structure
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
100
Y<=I-­‐goal
I-­‐mot
goal
Y<=I-­‐mot
goal
Learning
Strategy
*
Mo@va@on
Strategy
*
Learner
I-­‐player
role
Learner
You-­‐player
role
I-­‐mot
goal
*
G
Applica@on
S1:
Scenario
for
socializa@on
S2:
Scenario
for
achievement
S3:
Scenario
for
explora@on
Gameplay
strategy
I-­‐gameplay
*
Game
mechanics
What
use
*
Enhance
Gamified
CL
Scenario
LA LB
S1
à
S2
S3
à
S2
priority
stack
for
LA
priority
stack
for
LB
achiever
explorer
Se@ng
(4)
seing
the
proper
game
mechanics
for
all
learners
using
the
selected
scenarios
and
player
types

101. • Mizoguchi,
R.,
Sunagawa,
E.,
Kozaki,
K.,
and
Kitamura,
Y.
(2007).
The
model
of
roles
within
an
ontology
development
tool:
Hozo.
Applied
Ontology,
2(2):159–
179.
References
Sept.
9,
2014
An
Ontology
to
Gamify
CL
Scenarios
101