Emergence in Digital Educational Games: A World of Incidents in a Universe of Rules
Michael D. Kickmeier-Rust, Dietrich Albert
Department of Psychology, University of Graz, Austria
Abstract: Using computer games for educational purposes is a compelling idea that is increasingly
adopted by researchers, developers, and educators. Still, digital educational games are at an early
stage. A crucial factor that must be increasingly addressed by future research is a personalization of
learning and gaming experiences in the rich virtual worlds of computer games. In the present paper we
introduce an approach to combine frameworks of psycho-pedagogical adaptation, interactive
storytelling, and emergent game design in order to provide the individual learners with tailored learning
experiences without corrupting the game’s storyline and without requiring massive content production.
Keywords: Competitive educational games, adaptation, personalization, interactive storytelling,
emergent game design
Computer games are an outstanding and incredibly successful part of the present entertainment
landscape. The compelling technology of leading edge computer games, at least in our opinion, must
be considered for teaching and learning also. With the increasing time people of all age groups spend
on playing computer games, the idea of utilizing the games’ motivational and educational potential
becomes more and more convincing and fascinating. Still, today’s computer games not only have a
tremendous motivational potential, computer games enable realizing elementary and essential
pedagogical and didactical principles in a very natural way. Computer games, for instance, provide an
emotionally and semantically appealing and meaningful context for learning, rich and immersive
possibilities for visualizing contents, or the possibility for self-directed, active learning. In short,
computer games do have the potential to make knowledge attractive, important, and meaningful.
For several reasons, the vision that digital educational games (DEGs) become a serious part of
educational technology did not come true yet; from today’s perspective, the realization of this vision is
still in its infancy (Oblinger 2006). This is particularly true if educational games for older children and
adolescents are concerned or when considering games related to school curricula. Most existing
DEGs are rather small and often simple games, focusing on a limited set of competencies (e.g., basic
algebra) or addressing specific skills (e.g., job application trainings). They generally do not related to
school curricula or do not attempt to enable learning about school-related subject matter. More
importantly, existing games do not provide sound assessment methods and generally there is an
imbalance between learning and gaming. Finally, while game intelligence is well developed,
educational games do not include adaptation to the learner in terms of knowledge, learning progress,
motivation, or individual preferences. Thus, they cannot compete with their commercial counterparts
and they cannot utilize the full potential of immersive digital games with respect to learning efficacy
and learning experience. In conclusion, a key aspect of the success of an educational game (i.e.,
effective learning and fun) is an intelligent adaptation to the individual learner.
1.1 Around an Inspiring Virtual Learning World in Eighty Days
The psycho-pedagogical personalization in DEGs is in the focus of the European research project
80Days (www.eightydays.eu). Inspired by Jules Verne’s novel “Around the world in eighty days”, the
project aims at developing psycho-pedagogical and technological foundations for intelligent
adaptation. Basically, the project’s endeavours include melding curriculum-related subject matter with
the fun and excitement of an attractive and compelling computer game. In this context, the intrinsic
motivational potential of computer games is the key to learning success in the sense of voluntary and
maybe hidden learning activities.
In the focus of research and development is an intelligent technology that allows an adaptation to
individual learners, their prior knowledge, abilities, preferences, and learning progress, even more, a
technology that allows a so important but so fragile dynamic balance between challenge and ability.
Figure 1: The three act story model and its translation to a sequence of game elements
Figure 2: A formal representation of restrictions in the sequencing of story elements
This task is not trivial; it requires not only the adaptive mechanisms described earlier, it requires a
formal and computable story model. 80Days relies on the classical three-act structure of Aristotle
providing an arc model with ‘exposition’, ‘rising action to climax’ and ‘denouement’ (Figure 1). Thus,
we can combine the story and learning by linking competence structures with story plots (Figure 2).
This, in turn, generates game paths, possible and meaningful paths through the game accounting for
story model, learning objectives, and pedagogical interventions (see Kickmeier-Rust, Göbel, & Albert
2008 for details).
The outlined approach, unfortunately, has an important drawback: the cost factor. A comprehensive
adaptation throughout an entire game requires massive content (i.e., game elements) production.
However, cost-effectiveness is a crucial factor for a DEG’s success on the market. We address this
problem by extending the approach of adaptive, educational storytelling with ideas of emergent game
2. Emergence in (Educational) Game Design
In regular games, a sequence of scripted events occurs throughout the game. According to Smith
(2002), however, this bears the downside that the game system has a limited awareness of what is
happening and, more importantly, the game is lifelessly determined by what the designers think is
exciting and fun. Emergent behavior, on the other hand, occurs when more or less simple rules
interact to give rise to behavior that was not specifically intended by the developer of a system.
Emergence refers to the process of deriving new but coherent patterns or behaviors in complex
systems. Emergent phenomena occur due to a non-trivial interaction of system components with each
other and with the user. As Johnnson (2001) pointed out, the collective of such kind of interactions
forms novel, complex, and unexpected results. Emergent game design offers a ‚platform’ and ‘tools’
for gaming, however, without any further blueprint; this is comparable to improvisational theatre or
giving a kid a box of toy cars. The context is fixed but what happens occurs interactively and
One perspective is that emergent gameplay appears due to excellent and comprehensive simulations.
Rich virtual worlds enable the player to interact with a large degree of freedom and, more importantly,
to interact with game entities that respond in a realistic way. Examples might be SimCity, The Sims, or
the interaction with the people in Grand Theft Auto. The key to emergent gameplay and emergent
narrative is a meaningful and “intelligent” interaction with the game and within the game. The
advantage is that each player receives a very unique and personalized gaming experience, which is
potentially enriching the possibilities for educational adaptation/personalization. On the other hand, to
create such intelligent and complete game world may require a significant amount of resources,
perhaps much more than scripted games need.
There exist several techniques from complex systems, machine learning, and artificial life that
potentially enable emergent behavior in games. According to Sweetser (2006a) some examples are
flocking (simulating group behavior such as a flock of birds), cellular automata (discrete time models
simulating complex systems), neural networks (machine learning techniques inspired by the human
brain), or evolutionary algorithms (optimization techniques using concepts from natural selection and
evolution to evolve solutions to problems). Some of those principles have already been transferred to
real games; for example, Half-Life used flocking to give its monsters more lifelike responses. Another
example might be Blade Runner; but also in this example a pre-defined storyline is only “enriched” or
“altered” by accidental aspects, making the game different at each time. Important work in this area
comes from Sweetser (2006b) who developed and evaluated a technically sound framework for
realizing emergent game design. Several authors claim that emergence is the direction game
development is heading, which includes more flexible, realistic, and interactive worlds Sweetser
2.1 Gameplay versus Narrative
Gameplay and narrative are two fundamental dimensions along each game can be described. The
one determines the what and how, the other determines the why. Although both dimensions occur on
a continuum, specific games are either predominantly gameplay-based (e.g., role playing games,
action adventures, or campaign games) or predominantly narrative-based (e.g., simulation games,
management games, or strategy games). Those dimensions also aroused some debate on which a
game should focus more: The ludologists say that games should be played and not perceived like
interactive movies. The narratologists, instead say, games should follow a red story thread. Both, the
gameplay dimension as well as the narrative dimension can be described on a continuum between
open/emergent and predefined/scripted.
With respect to emergent approaches on the gameplay side, intelligent characters play a crucial role.
The “intelligence” of game characters is a essential factor. Those characters are supposed to behave
flexible, challenging, unpredictable, or cunning (Sweetser, Johnson, Sweetser, & Wiles 2003). An
intelligent agent can be considered autonomous if it relies on its own precepts and not on the
predefined ‘will’ or ‘knowledge’ of the game designer (Russel & Norvig 2003). Being autonomous, in
turn, requires situational awareness. An example for such approach in an existing computer game is
the agents in Half Life. Those characters “look” and “listen” to what is happening in their neighboring
areas (Leonard 2003). Still, the realization is rather simple; pre-defined check scripts are processed. In
psychological terms, existing models perform a top-down approach driven by the
designers/developers intelligence. The next generation of artificial in-game intelligence will rather
purse a bottom-up approach, meaningful responses on changes in the agent’s neighborhood.
2.2 The Educational Ways
However, aforementioned approaches were developed in the context of entertainment games.
Educational computer games cannot simply overtake such ideas since a crucial difference between
the two kinds of games is that educational objectives require the learner to pass through certain
learning situations (in whatever way they are realized). This means that pedagogical implications limit
the degree of freedom and randomness in emergent approaches to game design. It is necessary that
a learner is exposed to certain learning situations in a certain sequence.
These limitations contribute to an interactive dilemma (Peinado, Gómez-Martín, & Gómez-Martín
2006) the designers do not want to (and also must not) lose all control and system-only generated
story plots are likely not very convincing. Thus, a subtle balance is required between a global idea of
the story and emergent aspects; research proposed a dual layer model that separates a narrative
layer and an agent/simulation layer (Peinado, Gómez-Martín, & Gómez-Martín 2006). The story
generation is based on the interaction with the beholder, a story-ontology, and vectors of story
elements and relationships.
In this work we want to present a model for involving emergent game design ideas in educational
contexts. This model considers the learning domain, the learner, and it relies on character-based and
3. Educational Adaptation - Interactive Storytelling - Emergent Game Design
First, a narrative context model must be generated. This model is based on the characteristics of the
hero’s journey (Campbell 1993) and the classical three-act story model. It determines a general red
thread through the game and it defines the intro act and the closing act. In-between, we have a large
number of possible story/game paths (Figure 1). These are associated with educational objectives and
pedagogical implications – using the cognitive competence-based knowledge space theory
(Kickmeier-Rust & Albert 2008), which establishes a structure of story/game elements that are
meaningful in terms of education and in terms of story. The cognitive model reflects the psycho-
pedagogical requirements and thus determines the admissible game parameters. Formally, we can
summarize the psycho-pedagogical aspects as an “inner state”, which constitutes n-tuples, which in
turn determine transition probabilities (Figure 2). However, in terms of game development this model is
the anti-thesis of cost-effectiveness since it requires massive content production.
As a consequence, we introduce an abstraction layer. On an ontological basis (extending Kickmeier-
Rust & Albert 2008) we separate game play features, story features, and educational features. The
game progresses through a sequence of generic modules (cells) which are sequenced adaptively and
filled with game play, story, and education in real time and system driven.
The theoretical background is similar to the principles of cellular automata. Many of today’s
approaches to modeling real-world phenomena aim to come up with accurate and error-free models.
Often such modeling occurs in the context of scientific applications and forecasts. In games this
complexity is not necessary. It’s all about providing appealing and realistic visual effects (e.g., smoke
or fire) – not necessarily accurate but rather credible. Forsyth (2002), for example has described
methods with which natural processes (e.g., fluid flow) can be simplified for games using cellular
The game elements are seen as cells of a multi-dimensional grid (Figure 3). Each cell must be in one
of a finite set of admissible states (e.g., in terms of story or in terms of knowledge) and each cell has a
set of update rules. The state of a cell is a function of the states of the neighboring cells and it is
sensitive to the actions of the learner. This results in an ebbing and flowing of incidents and it allows
an emergent development of game play as well as narrative – of course limited by the global red
thread through the game and the educational objectives. In more practical terms this means, if the
learner performs an action (e.g., closing the electric circuit) the probability distribution over the
competence states is altered. In combination with other indicators (e.g., intervals between actions or
the number of re-trials) this determines the properties of the game elements (the cells). In turn, altering
the properties of a cell changes the properties of the neighboring cells, comparable to the propagation
of waves when a stone hits the water surface. To give an example, if the learner fails to establish an
electric circuit, the next learning unit automatically adjusts itself to teach the learner about electric
circuits. The advantage of this approach is that the game only needs the assets for the described
adjustments (maybe a set of re-combinable sentences an avatar could say), it is not necessary to
develop all possible learning units.
Figure 3: Cellular automata – or a stone hitting the water
In conclusion, the presented attempt to emergent game design in educational contexts can be seen as
a hybrid model which tries to combine the best of both worlds, the author driven scripting of the global
context (including the educator driven design of learning) as well as the degree of freedom and cost-
effectiveness of emergent approaches to game design. Apart from the educational context, the hybrid
model provides also ideas for designing virtual environments in general.
Emergence is primarily driven by “intelligent” characters and “smart props” (prop is a term for objects
in the game such as tools, weapons, furniture, etc.). The approach of cellular automata enables
changes in the game context (by actions of the player and by micro or macro adaptive assessments)
affecting not only one specific character or prop but, driven by more or less complex rules,
semantically neighboring characters and props.
The research and development introduced in this work is funded by the European Commission under
the seventh framework programme in the ICT research priority, contract number 215918 (80Days,
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