Toward Personalised Gamification
for Learning Environments
Baptiste Monterrat1
Élise Lavoué1
Sébastien George2
MATEL workshop 2013,
Paphos, Cyprus
1 LIRIS, Université de Lyon 2 LIUM, Université du Maine

Learning environments, even if they
are efficient, are not always motivating
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Game and “fun”
enhance motivation
Learning environments, even if they
are efficient, are not always motivating
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Gamification
Serious
Games
Toys
Playful
design
• A game has an objective and rules
Game
Play
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Forms of “fun” in learning [Deterding et al., 2011]

Gamification
Serious
Games
• A game has an objective and rules
Game
Play
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Forms of “fun” in learning [Deterding et al., 2011]

Gamification “use of game design elements in non-gaming contexts”
[Deterding et al., 2011]
Gamification
Serious
Games
• Game elements are less central
with gamification
• Gamification can be based on
existing environments
Whole Part
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Various expectations about games
Killer
Socialiser
Achiever
Explorer
Motivated by
leader boards
Motivated by
friends
Motivated by
clear goals
Motivated by
discoveries
• According to player types [Bartle, 1996]
7B. Monterrat - Université de Lyon

Various expectations about games
Killer
Socialiser
Achiever
Explorer
Motivated by
leader boards
Motivated by
friends
Motivated by
clear goals
Motivated by
discoveries
• According to player types [Bartle, 1996]
• According to
user’s age.
[Charlier et al., 2012]
8B. Monterrat - Université de Lyon

Various expectations about games
Killer
Socialiser
Achiever
Explorer
Motivated by
leader boards
Motivated by
friends
Motivated by
clear goals
Motivated by
discoveries
• According to player types [Bartle, 1996]
• According to
user’s age.
[Charlier et al., 2012]
• According to
user’s gender.
[Hainey et al., 2012]
• Etc.
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Adaptivity
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Adaptivity
• Work on adaptive
learning games :
• Content
• Scenario
• Difficulty
• Learning path
• Etc.
• Work on adaptive
gamification:
• Not yet
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Our objective
Adaptive and generic
Gamification layer
Web based
Learning
Environment
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Research questions
Which architecture to support
adaptivity of game elements
in a learning environment?
How to
characterise
game elements?
User Model : Which
information is required
for personalisation?
How to integrate the
game elements in the
learning environment?
13B. Monterrat - Université de Lyon

Game Elements in Epiphytic Functionalities
Four features to be an epiphyte:
[Giroux et al., 1995]
• The epiphyte can not exist without its host
• The host can exist without the epiphyte
• The architecture of the epiphyte
is independent from the host architecture
• The epiphyte does not affect its host
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User Model:
Related work in adaptive environments
• Kobsa (1999) distinguishes three forms of adaptation: user data, usage data, environment data
• Conati (2002) focuses on what the
learner knows and does not know.
• Bernardini (2010) classifies the learners
according to their way of learning
High Learner, Low Learner
• Bartle’s player types (1996)
Killer, Achiever, Socialiser, Explorer
• Lazzaro’s keys of fun (2004)
Hard fun, Easy fun, Altered state, People factor
• Yee’s motivation components (2006)
Achievement, Social, Immersion
The user as a learner
User model elements for personalisation of learning environments
The user as a player
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16
Gamification layerLearning
Environment
The User Model for Adaptive Gamification
Learner Model Player Model
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Gamification layerLearning
Environment
The User Model for Adaptive Gamification
Learner Model Player Model
Collected data Calculated data
• Player type
• Engagement level
B. Monterrat - Université de Lyon

I – USER DATA
• Age
• Gender
• Location
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Gamification layerLearning
Environment
The User Model for Adaptive Gamification
Learner Model Player Model
Collected data Calculated data
III - ENVIRONMENT DATA
• Learning context
• Size of the group
• Date, hour
• Device
II - USAGE DATA
• Session dates
• Usage of epiphytes
• Response time
• Level of success
• Player type
• Engagement level
B. Monterrat - Université de Lyon

1. Collect the trace of interactions between the learner and environment, *
2. Detect learner disengagement, *
3. Choose a gamified functionality to activate,
4. Integrate the gamified functionality within the UI. *
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* User model updates
Gamification Process
B. Monterrat - Université de Lyon

Architecture
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Conclusion and Future works
We explained the interest for gamification to be adaptive
and generic,
and proposed a user model and an architecture to
support such gamification.
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Conclusion and Future works
We explained the interest for gamification to be adaptive
and generic,
and proposed a user model and an architecture to
support such gamification.
We are working on the first implementation of this
system, based on an environment to learn spelling.
Development and assessments will be iterative.
22B. Monterrat - Université de Lyon

Conclusion and Future works
We explained the interest for gamification to be adaptive
and generic,
and proposed a user model and an architecture to
support such gamification.
We are working on the first implementation of this
system, based on an environment to learn spelling.
Development and assessments will be iterative.
We hope that this work is a step toward more
motivating learning environments.
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B. Monterrat - Université de Lyon 24
Thanks for your attention
baptiste.monterrat@universite-lyon.fr

Keep in mind…
Game should remain a
voluntary activity.
25
We can’t turn everything
into a game.
Games should not
replace learning.
Personalisation to user
data has limits.
B. Monterrat - Université de Lyon

Integration of the epiphytic functionalities
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