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Emergent Design: Serendipity in Digital Educational Games

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Using computer games for educational purposes is a fascinating idea that is getting increasingly popular amongst educators, researchers, and developers. From a technical as well as psycho-pedagogical viewpoint, today's educational games are at an early stage. Most products cannot compete with non-educational, commercial games and not with conventional educational software. Research must address fundamental challenges such as methods for convincing learning-game design or individualization of gaming experiences. An important key factor is development costs. To enter the market successfully requires reducing development costs significantly, however, without reducing gaming or learning quality. In this paper we introduce an approach of using existing methods for educational adaptation and personalization together with ideas of emergent game design.
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Emergent Design:
Serendipity in Digital Educational Games
Michael D. Kickmeier-Rust1 and Dietrich Albert1
1 Department of Psychology, University of Graz
Universitaetsplatz 2, 8010 Graz, Austria
{michael.kickmeier; dietrich.albert}@uni-graz.at
Abstract. Using computer games for educational purposes is a fascinating idea
that is getting increasingly popular amongst educators, researchers, and
developers. From a technical as well as psycho-pedagogical viewpoint, today’s
educational games are at an early stage. Most products cannot compete with
non-educational, commercial games and not with conventional educational
software. Research must address fundamental challenges such as methods for
convincing learning-game design or individualization of gaming experiences.
An important key factor is development costs. To enter the market successfully
requires reducing development costs significantly, however, without reducing
gaming or learning quality. In this paper we introduce an approach of using
existing methods for educational adaptation and personalization together with
ideas of emergent game design.
Keywords: Digital educational games, game-based learning, adaptation,
personalization, interactive storytelling, emergent game design
1 Introduction
Computer games are a very successful element of the today’s entertainment landscape
and an integral part of everyday life. The young people, the so-called digital natives,
spend a many hours on playing computer games. Thus, it is not surprising that
educators developed an affinity to the idea of using computer games for educational
purposes. The result is a significant hype over educational or serious games. Digital
educational games (DEGs) are on their way to become a mainstream genre of
educational technology. Of course, this idea is not new, educational games are as old
as computer games. An early example is the game Oregon Trail released first in 1971
and re-released by the educational publisher Brøderbund for the Apple II in 1985. The
game focused on teaching resource management. Today, the examples for educational
games are manifold, ranging from so-called moddings (modifications of commercial,
non-educational games) to games and simulations for primarily educational purposes.
Also the scientific community addresses educational games for a while now,
conducting research on the foundations of effective yet appealing DEGs. The reason
for the hype, however, is not only the appeal of computer games to young people,
computer games enable realizing elementary and essential pedagogical and didactical
Kickmeier-Rust, M. D., & Albert, D. (2009). Emergent Design: Serendipity in Digital
Educational Games. In R. Shumaker (Ed.), Virtual and Mixed Reality, Proceedings of VMR
2009 as Part of HCI Internation 2009 (pp. 206-215). July 19-24, 2009, San Diego, CA. Lecture
Notes in Computer Science (LNCS) 5622. Berlin: Springer.
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.
Surveying the market as well as the body of scientific prototypes and projects,
however, educational computer games are still at an early stage [1]. There exists a
great many of small and simple games for the very young children and also
“gameplay-enhanced” approaches with clear limitations in educational impact and
gaming quality. However, there is a clear lack of DEGs that can compete with their
“non-serious” counterparts in terms of gameplay, narrative, and visual quality as well
as with conventional learning technology in their educational impact.
One fundamental problem of DEGs and at the same time their most prominent
advantage – is the intrinsic motivational potential of computer games. Children,
adolescents, and adults play computer games voluntarily, for fun, and they spend a
significant amount of time on playing. Today’s gamers are used to an incredible
visual quality and appeal of game play of entertainment computer games. However, if
educational games cannot compete with this level of quality, the motivation to play
them will be rather limited. Since the costs of current computer games are exploding –
a good game might well cost 50 to 100 million dollars – educational publishers cannot
keep up with game industry. Even worse, the “education” in educational computer
games makes the development even more expensive. So it is clear that a prerequisite
of commercial and educational success is cost-effectiveness. The consequence is that
compelling DEGs are still rare. Quite in the contrary, more and more off-the-shelf
entertainment games or modifications are used in class rooms.
An obvious idea to overcome the problem of cost-effectiveness is reducing the
development costs. Unfortunately, this is most likely bound to reducing the quality of
education, design, narrative, and game play. In conclusion, driving the establishment
and quality of DEGs requires games that are effective from an educational point of
view, effective from the development point of view, and competitive from the gaming
point of view. And this is a non-trivial problem. In this paper we present an approach
that, essentially, is based on a fusion of an intelligent in-game personalization and
adaptation (in a psycho-pedagogical sense) with interactive storytelling and with ideas
of emergence in game design.
2 Personalization in Digital Educational Games
Using “intelligent machines” for educational purposes has a long history; in fact, it
can be traced back at least to 1926 when Sidney Pressey [2] tried to build a machine
that presented multiple choice questions, their answers, and adequate feedback. The
driving force behind intelligent educational systems is to provide individual learners
with individual solutions, essentially because of the fact that meaningful and suitable
one-on-one teaching is the most effective way of teaching. Unfortunately, a personal
tutor is the most expensive way of teaching also. To address this problem with a
technological solution, over the past decades several methods and frameworks for
intelligent and adaptive tutorial systems were developed [3].
In contrast to conventional adaptive educational technology, for example learning
management systems, DEGs are challenging the technological state-of-the-art by
requiring a non-invasive assessment (e.g., of knowledge or learning progress) and
adaptation. In simple words, typical assessment methods such as multiple choice
questions or cloze texts cannot be utilized in immersive DEGs because, in all
likelihood, popping-up assessments would immediately destroy game flow and
immersion. The challenge is to find ways and methods to embed assessment subtly in
the gameplay and narrative. In addition, the methods of personalization and
adaptation must occur in a non-invasive way as well. Prominent methods are adaptive
curriculum sequencing (selecting and re-ordering learning objects) and adaptive
presentation (changing the look and feel of a learning environment). These methods
(e.g., skipping a learning situation because the systems concludes that the learner
already has the related knowledge) are hardly realizable in an immersive DEG
because they would corrupt gaming experience and game flow, ending up with an
implausible and confusing storyline without any motivational and educational
potential.
Our solution is a non-invasive way of personalization and adaptation, that is, micro
adaptivity, which was developed particularly for DEGs and which is related to
techniques of adaptive problem solving support. The principle of micro adaptivity is
to monitor the learner’s behavior in the virtual world and to interpret the behavior in
terms of available and lacking knowledge or in terms of specific inner states (e.g.,
motivation). To give an example, imagine a game-like exploratory learning situation
within which the learner is required to narrow a light cone from a torch to a small
light beam using a couple of blinds (see Figure 1). If the learner cannot narrow the
light cone, we can conclude that this learner lacks the understanding of the blind
principle. Of course, a single observation is not very significant but with an increasing
number of actions, the (probabilistic) picture of the learner becomes continuously
clearer and more valid. The micro adaptive assessment is complemented with subtle
educational and motivational interventions, which are strictly embedded in the
Fig. 1. Screenshot of a competitive educational game about the physics of optics. The
game is a prototype developed in the context of the European ELEKTRA project
(www.elektra-project.org).
game. An example is to provide the learner with feedback of the learning progress or
hints. By aforementioned example, a non-player character (a NPC) might suggest the
learner promising locations for the blinds. A more in-depth description of the micro
adaptivity concept is provided by [4].
2.1 The Macro Level: Adaptive Storytelling
So far our concept of personalization and adaptation for DEGs just concerned
assessment and interventions within specific limited and pre-defined learning
situations. Educationally important techniques for personalization and adaptation such
as adaptive sequencing of learning units (learning situations in a DEG) or adaptive
presentation, however, are not addressed. To extend and enrich our approach to in-
game personalization and adaptation, we aim for a fusion of the micro adaptivity
concept with interactive and adaptive storytelling. In that way, we can realize a
personalized sequencing of learning situations and units according to educational
aspects as well as personalized adjustments of the game according to individual needs
and preferences. In other words, we can shift in-game adaptation to the macro level.
In the literature several techniques for interactive or adaptive storytelling are
described, varying in the openness of story generation and in their operational
reliability. The approaches range from a recombining of self-contained story elements
to an open-ended automated generation of “new” stories. For our goal of adaptation
we rely on a robust approach based on the specification of atomic story-related
entities (ranging from single spoken sentences to self-contained story units). In this
context, a crucial aspect of interactive storytelling is to find an appropriate storyline
on the basis of a pool of given atomic story or game elements. These entities can be
compared to the rooms of a house and the furniture in those rooms, each entity has a
specific goal (e.g., providing the learner with information, assessing internal states, or
contributing to story and gameplay), specific characteristics and properties. During a
gaming episode the single game entities must be adaptively re-combined and re-
assembled into a meaningful storyline and a meaningful environment. The assembly
is driven by specific sets of rules which refer to aspects of the game genre, the story
model, educational aspects, and individual aspects.
The story model underlying our approach relies on a formalization of the classical
three-act structure of Aristotle providing an arc model with ‘exposition’, ‘rising
action to climax’, and ‘denouement’ (Figure 2, left panel). The related set of rules is
supplemented with domain-related rules, defining the set of educationally meaningful
sequences of learning, so-called learning paths through the learning situations of the
game (or learning objectives of a conventional learning environment). This
combination generates game paths (Figure 2, right panel), possible and meaningful
paths through the game accounting for story model, learning objectives, and
pedagogical interventions (see [5] for details).
The outlined approach, unfortunately, has an important drawback that is
contracting our initial aim, the cost factor. A comprehensive adaptation throughout an
entire game would require massive content (i.e., game elements) production. We
address this problem by extending the approach of adaptive, educational storytelling
with ideas of emergent game design.
Fig. 2. The left panel shows the three act story model and its translation to a sequence of game
entities. The right panel shows a formal representation of restrictions in the sequencing of story
elements.
2.2 Emergence in (Educational) Game Design
A potential solution to the dilemma is making the game more “autonomous”. In
regular games, a sequence of scripted events occurs throughout the game. According
to [6], 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. Emergence, 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 [7] suggested, 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 incidentally.
One method of realizing emergent game design is that gameplay is based on
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
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 players receive a very unique and personalized gaming experience
as a direct result of their own behavior.
There exist several techniques from complex systems, machine learning, and
artificial life that potentially enable emergent behavior in games. According to [8]
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 is Blade Runner; here a pre-
defined storyline is “enriched” or altered by accidental aspects, making the game
different at each time. Important work in this area comes from [9] 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.
3 Educational Game Design
Realizing emergent game design requires a game context. Two fundamental
dimensions of a game are gameplay and narrative. The gameplay determines the what
and how, the narrative determines the why. Although both dimensions occur on a
continuum, specific games are either gameplay-oriented (e.g., role playing games,
action adventures, or campaign games) or narrative-oriented (e.g., simulation games,
management games, or strategy games). To give very prominent examples, a game
like Tetris is fundamentally driven by the gameplay without any story behind;
adventure games such as the famous Zak McKracken are, almost like an interactive
movie, driven by a story.
These 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.
When aiming for an effective and efficient design of DEGs, of course, more
dimensions of computer games must be considered. A valuable contribution to
formalizing viewpoints to computer games came from Smed and Hakonen [10].
These authors argue that the main dimensions of the computer game concept are
linked together in a subtle way by the representation form (medium), by rules, by the
goal definition, and by the absence or presence of opponents. Figure 3 illustrates these
dimensions. A further important systematization of game genres we have to consider
came from Lindley [11]. This approach begins with a classification of games on a
‘plane’ of ludology, narratology, and degree of reality (the author terms this
‘simulation’ or ‘prosthetic reality’). In a next step, the model is extended by a 3rd
dimension, that of chance (the author terms this ‘gambling’ or ‘decisions about gain
and loss’). The model manifests as a three-dimensional pyramid, which allows for
classifying game types along its dimensions (Figure 3). Although Lindley’s taxonomy
offers a systematic approach that covers a wide range of aspects, the “purpose” aspect
is not represented very well. Particularly educational aspects and intentions establish a
micro universe of educational game types that must be considered in educational
game design. With respect to the idea of emergence, finally, this dimension must be
considered as well.
Emergent approaches involving intelligent gameplay and intelligent characters
might play a crucial role in future mainstream game design, particularly in the context
of serious games. The “intelligence” of game characters can be considered as essential
Fig. 3. The left panel shows the dimension of computer games according to [10], the right panel
shows a different approach to describe game types according to [11].
factor. Those characters are supposed to behave flexible, challenging, unpredictable,
or cunning [12]. 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
[13]. 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 [14]. 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 by meaningful responses on
changes in the agent’s neighborhood.
3.1 Serendipity Instead of Emergence
If we consider emergence, as mentioned above, as a box of toy cars, certain rules and
possibilities are fixed, what the play will be exactly is open – in other words,
emerging. The problem is that this idea of openness is not compatible with (most)
educational purposes. The existing ideas and approaches were developed in the
context of entertainment games. Educational computer games cannot simply overtake
such ideas since a distinct difference between the two kinds of games is that
educational objectives require the learner to pass through certain learning situations
following a certain curriculum. 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.
Quite naturally, the question is arising whether both ideas can be merged into one
game; 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 [15].
The story generation is based on the interaction with the beholder, a story-ontology,
and vectors of story elements and relationships.
To overcome the incompatibility of emergence and educational purpose while
still taken advantage of an open approach, we generated a narrative context model.
This model is based on the characteristics of the hero’s journey [16] 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. As underlying data model we extended an
ontological approach [17]. As shown in Figure 2, the atomic story elements provide
the game with a certain degree of freedom of how the story proceeds and about what
is happening in the game. To bring education into play, the story elements are mapped
to educational objectives and pedagogical implications – utilizing a formal cognitive
theoretical framework, that is, Competence-based Knowledge Space Theory [17],
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.
In a next step we introduce an abstraction layer. On an ontological basis we
separate game play features, story features, and educational features from the game
entities (story elements, in-game-objects, NPCs, etc.). As a result, we obtain a set of
generic modules (cells), which can be “furnished” just-in-time in accordance with the
ontological cognitive model and which can be sequenced in accordance with the
narrative. The theoretical background of the generation of modules and their
sequencing is similar to the principles of cellular automata. Many of today’s
approaches to modeling real-world phenomena, which aim to come up with accurate
models, are based on this approach. Within games it is not necessary to be accurate in
that sense; it is all about be consistent and credible. Forsyth [18], for example has
described methods with which natural processes (e.g., fluid flow) can be simplified
for games using cellular automata.
The game entities are seen as cells of a multi-dimensional grid. Each cell is 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. The properties of cells can either be discrete
or steady. For example, probability distributions over cells are used to estimate the
learner’s knowledge (in the sense of an associated memory). In such a way, actions of
the user influence the properties of the cells (the present game state). 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 narrow a light cone properly, the next learning unit automatically
adjusts itself to teach the learner about the blind concept.
What does this mean for our initial goal, reducing the costs of intelligent DEGs?
The big advantage of this approach is that it is not necessary to develop all possible
learning situations in a traditional sense. On this basis it suffices to develop a pool of
assets (basic environments, objects, characters, sentences, etc.). The underlying
intelligent technology autonomously builds the game upon the given assets.
Fig. 4. Brief sketch of the architecture for an emergent behavior of the autonomous NPC
named Feon – that is currently developed in the 80Days project.
4 Conclusion and Future Directions
To make effective and competitive DEGs mainstream educational technology, it is
necessary to reduce the cost factor and to increase personalization and adaptation
(which is likely even more important for DEGs than it is for conventional learning
environments). The presented approach takes up existing intelligent technology for
adaptation in the game-context and extends by a component of emergence – or rather
serendipity (making fortunate discoveries by accident). We presented 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. Of course,
the ideas and their technical realization are at an early level. Future work must extent
the present theoretical approach, implement it, and evaluate its applicability. In the
context of the European research project 80Days (www.eightydays.eu), we are
currently focusing on an autonomous and intelligent NPC (Figure 4), which is
supposed to serve as teacher in a competitive DEG. As outlined, the behavior of this
character as a certain awareness of the game and learning progress and tailors its own
behavior to those requirements. Thus, the script of what is happening when is not
authored but emergent in the interaction with the learner. At the present stage,
however, we have clear limitations in the variability of the overall story. Future
developments will increase the freedom by extending the cellular network and by
increasingly adding the so-called smart props.
Acknowledgements
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, www.eightydays.eu).
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... Emergence occurs when more or less simple rules interact to give rise to behavior that was not specifically intended by the developer of a system (Kickmeier-Rust & Albert, 2009). This is what Salen andZimmerman (2003a, 2003b) have dubbed emergent gameplay. ...
... Emergence occurs when more or less simple rules interact to give rise to behavior that was not specifically intended by the developer of a system (Kickmeier-Rust & Albert, 2009). This is what Salen andZimmerman (2003a, 2003b) have dubbed emergent gameplay. ...
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