Theories, Models, and Principles of Serious Game Theory and Design

This page is an on-going project - I am building a list of theories, etc. that are relevant to serious game theory design.

Serious Game Theory: The theory of how and why serious games work. I have developing this theory since 2003, when I began my doctoral studies. Serious Game Theory is related to but distinct from Serious Game Design. Some theories relate to serious games as a learning medium (foundational) and others are useful to consider when designing specific games (implementation).

Serious Game Theory is NOT the same as or in any way related to Game Theory

As far as possible I will try to include the following with each entry:

Relevance to Serious Games

The Theories

Theories come in many flavours. These are just a few:

  • Cognitive Learning Theories
    • how people think
    • assume that prior knowledge plays an important role in learning and affects the learning of new knowledge.
  • Information Processing Theories
    • how thoughts are input and organized
    • attempt to explain what is going on inside your head when you are learning.
  • Motivational Theories
    • why people do what they do
  • Learning Styles
    • These theories attempt to explain variations in cognition among groups
  • Instructional Design Theories & Models
    • how to design instruction

How do we tell a theory from a model from a style?

I really don't know.

Often it seems simply to be a matter of degree, and whether or not the authors have nice pictures to visualize their ideas.


Adaptation Theory

Basically the idea is that we all have a concept of how the world is and works in our heads (our theory). Whenever we come across something new (practice), we do one of these things:

  • assimilate it (fit practice to theory)
    • add it to what we already know and understand
    • this is possible if the new knowledge fits our current view
  • accommodate it (fit theory to practice)
    • adapt our view to fit better with the new knowledge
    • this is necessary if we are to include the new knowledge in our view
  • combination of both

In all cases the goal is to keep our internal world in a state of equilibrium where everything fits according to our internal logic (which may or may not be valid).

Relevance to Serious Games

These two approaches to internalizing new knowledge require different approaches, so it's useful in design to have some idea of which you are trying to elicit? Do you want to expand on something the players already know or change their minds?

Designers need to be aware of both explicit reinforcers and events that are connected so often that they become associated with each other.


As children we are still building our internal worlds and accommodation happens quite readily and frequently.

I suspect that as we get older and our internal world becomes more complex, we tend to prefer to assimilate new knowledge. Accommodation happens less readily and there is a tendency for us to “assimilate” new knowledge by labeling it negatively (false, silly, bad, …). That way we do not need to change our world view.


This theory is much maligned in education, but is still a key learning mechanism for almost all animals. It is so well accepted that it hardly deserves to be called a theory anymore, but it is most easily seen in relatively uncomplicated situations: basic animal training uses this principle. These days, positive reinforcement (clicker training) is more accepted than negative reinforcement, although negative reinforcement (shock collars) is still used, especially where safety is an issue.

An important variation on this is that partial reinforcement often elicits a much stronger response than regular reinforcement.

Contiguity is about associating one thing with another often enough that they become linked in the individual's mind. This too can be either positive or negative.

Relevance to Serious Games

Most games would be no-where without behaviouristic reinforcers.


See also:

  • Connectionism (E. Thorndike)
  • Operant Conditioning

The basic idea is that what we can take in and remember is finite, but affected by a host of factors, such as what we already know, and how easily we can hang the new learning onto something we already know.

It is possible to facilitate learning by reducing the cognitive load. This can take many forms, such as reducing distractions, presenting new ideas in a familiar form, mixing new and old so that there isn't too much new.

Relevance to Serious Games
  • Games fully support this notion by reducing cognitive load
  • Integrated sources of information games provide many different support mechanisms to help players remember things, thereby reducing the cognitive load, and freeing the player to concentrate on what they want (achieving the goal)
    • Reducing redundancy (? – this is easily possible in games; but it is better to place it under user control – so amount and frequency of repetition can be controlled by user)
  • EXCEPT: “Change problem solving methods to avoid means-ends approaches that impose a heavy working memory load, by using goal-free problems or worked examples.” I don’t agree with this anyways – goal-free problems?? – How can it be a problem if there is no goal?

This notion is also related to George Miller's 7 plus or minus 2 theory. The_Magical_Number_Seven,_Plus_or_Minus_Two

Relevance to Serious Games

If we are talking about Computer-Supported Collaborative Learning, then to my mind it doesn’t even belong in a list of learning or instructional design theories. It is far too thin to be considered a theory – it has the potential to produce some useful tools, but not yet. I came across what I believe will become one of my most useful comments in late 2004: “The most basic point in all computer UI design is that the user does not want to use your application. They want to get their work done as quickly and easily as possible, and the application is simply a tool aiding that.“ [] This is germane to the area of CSCL (and also to CSCW), and yet most researchers in the area seem to devote their time to creating more ‘stuff’ to place between the various people who are trying to learn or work, and the work or learning they are trying to accomplish. For the most part, what I have seen of both CSCL and CSCW, neither are invisible (in the sense that Norman promotes).


aka Crowdsourcing

  • members of a group collaborate and cooperate to pol their knowledge and skills
  • at its best it is a Gestalt
  • can be supported by technology
Relevance to Serious Games

Evidence: Folt-It


Cognitive Learning Theory

Bruner’s accomplishments are among the best known of all of major advances in education of the twentieth century. He is known for his foundational work in both cognitivism and constructivism. Deciding which should be associated with his name depends on who is asked, and which part of his long career one examines.

Jerome Bruner ranks among the foremost social thinkers of the last century. His contributions to psychology, cognitive science and education have been equaled by few. He is either responsible for or has been a principal figure in the development of such notions as scaffolding instruction, constructivist learning models, and the role of narrative in learning.


The notion that we construct new knowledge based upon prior knowledge is now quite fundamental to all of cognitive science.

Relevance to Serious Games

In games, this is all about learning by doing.


Cognitive Learning Theory


Often confused with constructivism, constructionism theorizes that we can learn through building things. For example we can learn about various mathematical concepts by building math games.

Relevance to Serious Games

Learning through building games is often associated with serious games, and game building tools like Game Maker are quite popular here.


I think the notion is actually more fundamental than is often considered when using the building of games as he vehicle for learning. In order to build a game about a particular concept, it is necessary to understand that concept quite thoroughly. The learning mechanism at work here is exactly the same mechanism as when we try to teach someone something. This mechanism is why tutoring can be so beneficial to the tutor.

See also: learning_by_teaching


Theory of Human Cognitive Development

Piaget decides that human capacity to learn certain things goes through various stages of development that are determined by age. He did this from watching his own children. While it is now widely accepted that there are serious flaws and gaps in his theory, the fundamental notions are sound and still in use today.

  • Sensori-motor
    • (Birth-2 yrs)
    • Differentiates self from objects
    • Recognizes self as agent of action and begins to act intentionally: e.g. pulls a string to set mobile in motion or shakes a rattle to make a noise
    • Achieves object permanence: realizes that things continue to exist even when no longer present to the sense (pace Bishop Berkeley)
  • Pre-operational
    • (2-7 years)
    • Learns to use language and to represent objects by images and words
    • Thinking is still egocentric: has difficulty taking the viewpoint of others
    • Classifies objects by a single feature: e.g. groups together all the red blocks regardless of shape or all the square blocks regardless of colour
  • Concrete operational
    • (7-11 years)
    • Can think logically about objects and events
    • Achieves conservation of number (age 6), mass (age 7), and weight (age 9)
    • Classifies objects according to several features and can order them in series along a single dimension such as size.
  • Formal operational
    • (11 years and up)
    • Can think logically about abstract propositions and test hypotheses systematically
    • Becomes concerned with the hypothetical, the future, and ideological problems
Relevance to Serious Games

This has obvious implications for educational games designed for children and young learners.


Learning Style Theory


David A. Kolb (with Roger Fry) outlined four elements in his model: concrete experience, observation and reflection, the formation of abstract concepts and testing in new situations. (Kolb & Fry, 1975) These four elements form the nodes of a connected circle of experiential learning, with learners able to enter, as it were, at any point along the circle. Ideally, learners will posses balanced abilities in each of the four areas, but in reality, they tend to polarize towards one of four “poles”. These four poles are summarized in the table below.

  • Converger: Abstract conceptualization (AC) + active experimentation (AE)
    • Practical application of ideas
    • Focus on hypo-deductive reasoning on specific problems
    • Unemotional
    • Narrow interests
  • Diverger : Concrete experience (CX) + reflective observation(RO
    • Imaginative ability
    • Generates ideas and sees things from different perspectives
    • Interested in people
    • Broad cultural interests
  • Assimilator : Abstract conceptualization (AC) + reflective observation (RO)
    • Can create theoretical models
    • Excels in inductive reasoning
    • Abstract concepts rather than people.
  • Accommodator : Concrete experience (CX) + active experimentation (AE)
    • Doing
    • Risk taker
    • Can react to immediate circumstances
    • Solves problems intuitively
Relevance to Serious Games

The primary argument being made here, is that many games already include elements to meet the needs of various learning styles, so if true, it should not be surprising that many of the games listed could just as easily have been listed in different columns. It’s all a matter of perspective, and how the player chooses to take up the game.

In more traditional settings, once an individual’s style is identified, instruction can be organized to support his or her strengths, which can give confidence, while still encouraging the further development of the others. In games, the need to appeal to a broad audience ensures that the Converger can remain unemotional, yet imaginative exploration is encouraged and rewarded. Theoretical models can be devised and tested with minimal risk, yet risks can be taken, and normally the worst that will happen is that the player must start over.

This bears repeating: a key aspect of good games is that the player can take up the game in many different ways: as a neutral orchestrator, or as an impassioned participant. Games encourage Accommodator abilities of immediate reaction to circumstances and Converger abilities of the application of ideas, and both can remain within the bounds of the “magic circle” of play (Huizinga, 1950) because the usual rules and consequences of reality don’t apply. Divergers can identify with other players or NPCs (non-playable characters) as if they are people, and Assimilators can relate to them using whatever conceptual frameworks they like. Some strategies will lead to greater success within the game than others, but the fact remains, that it is only a game – exploration and experimentation are actively supported in most good games.


aka DCog


The idea here is that cognition and knowledge is distributed across a bunch of things, including inanimate objects.

Relevance to Serious Games
  • Significant learning takes place when the subject matter is relevant to the personal interests of the student
  • Learning which is threatening to the self (e.g., new attitudes or perspectives) are more easily assimilated when external threats are at a minimum
  • Learning proceeds faster when the threat to the self is low
  • Self-initiated learning is the most lasting and pervasive.
Relevance to Serious Games

Many forms of games are obvious embodiments of this theory of learning.


Miller gave us some very useful ideas, such as the magic 7 +/- 2The_Magical_Number_Seven,_Plus_or_Minus_Two; and the idea of chunking – both of which can be used to great effect in designing games – but when applied too universally it becomes a dangerous analogy – we are NOT computing devices, attempts to explain human cognition in terms of a discrete machine creates a semiotic domain that is too limiting to be of value in work with games.

Relevance to Serious Games

Although not an active researcher in either the area of games or learning, in 1981 Malone presented a theoretical framework for intrinsic motivation in the context of designing computer games for instruction (Malone, 1981) that has been referenced by almost every writer and researcher in the area of digital game based learning. In it Malone states that intrinsic motivation is created by three qualities: challenge, fantasy, and curiosity. Challenge comes from variable levels, hidden information and randomness that inject uncertainly. Fantasy makes something possible that otherwise wouldn’t be. Curiosity can be aroused when learners believe their knowledge structures are incomplete, inconsistent, or un-parsimonious (making the strange familiar). Intrinsically motivating activities supply learners with a range of challenge, concrete feedback, and clear-cut criteria for performance – all essential qualities of successful games.

Relevance to Serious Games

Information Processing <style float-right>



The theory of multiple intelligences is one of the most significant recent developments in learning theories. Gardner proposes seven primary forms: linguistic, musical, logical-mathematical, spatial, body-kinesthetic, intrapersonal (e.g., insight, metacognition) and interpersonal (e.g., social skills).

The implications of this theory are that learning can become more effective if we focus on and develop instruction for these intelligences. For an example of how a single lesson might be varied to connect with each of Gardner’s intelligences see (Becker, 2005). Assessment should include more than one ‘intelligence’, as each is more than simply a content domain; it is also a learning modality. Cultural differences play a key role, as each culture tends to value and emphasize particular intelligences in favour of others.

Relevance to Serious Games

Connecting Gardner’s ideas with the design of games is particularly effortless, as almost every one is evident in almost every game – one of the features of games that make them so engaging is that they address each one of these forms, providing game players with a particularly rich experience:

  1. Linguistic: Games often include written and spoken elements.
  2. Spatial: They are of course highly visual, providing a rich 3 dimensional environment.
  3. Musical: All include sound to enhance play, and in some cases musical scores for games are as sophisticated as they are for film. A case in point is the Final Fantasy franchise, which has been featured in more than one professional orchestral performance.
  4. Kinaesthetic: Most games require players to ‘place themselves’ in the game in one way or another and virtually all involve movement and action. Players who are heavily engaged in a game will tense, relax, and shift their muscles in tandem with the actions of their avatar, and while the movement may not be very aerobic, it is still presents physically.
  5. Logical-mathematical: Strategy is one of the key elements in play. Most includes various forms of problem-solving and puzzles.
  6. Intrapersonal: Games also offer plenty of opportunities for solitary effort and reflection. To some extent, the perspective one takes on play involving NPC’s within a game, whether it be inter- or intra-personal is a matter personal choice.
  7. Interpersonal: Many of the most popular games are now multi-player games, and even those who aren’t involve interactions with non-playing characters (NPC’s).

Gardner’s more recent work has shifted focus somewhat to mechanisms of creativity, and professionalism, both in practice and the attached moral and ethic issues. Gardner and his colleagues have called this project “GoodWork”, and this area as well, games can play a role – games can serve as a medium to allow people to examine and play out various scenarios and thereby explore the concept of “good work”.


Cognitive Learning Theory

Facts, Concepts, and Schemas ALso: Piaget & Anderson


We make things into patterns.

I can’t remember exactly what he did, so I’ll just give you the reader’s digest version…

Believing that memory was a social and cultural phenomenon, Bartlett’s work centered on confirming this notion. Through his research, he learned that when people are told stories and asked to retell them later, the stories tend to be shorter, and are often coloured by the teller’s own culture and experiences. So for example when a part of the original story involves some aspect unfamiliar to the listener, an internal incongruency is created which the listener fills in from their existing knowledge base in order to make sense of it.

Bartlett is most often attributed to the description of the notion of “schema”, which is instrumental in organizing information so it can be remembered and recalled. Today, the concept is widely used in reference to categorization and classification of all kinds of information, and is also a useful tool when discussing many aspects of games that can be used for learning, as well as knowledge gained from game play. His work on group behaviour also has relevance to the use of games for learning.

Relevance to Serious Games

At its simplest we should keep things recognizable so we can categorize them in our heads easily. Schemata are used for everything from level design to interfaces.


This is almost like a theory of everything - it is how we learn. Pattern matching is what we DO. All the other theories are coloured by this one.


Motivation Theory


Self-Determination Theory is a theory of motivation and personality that addresses three universal, innate and psychological needs: competence, autonomy, and psychological relatedness.

Relevance to Serious Games

Learning is a function of activity, context, and culture – it is situated. Unfortunately, judging by the experiences of all three of my own children in a total of eight different schools, classroom situations are not often like this. Jean Lave states that social interaction is a critical component of situated learning – participants build a “community of practice”. Newcomers or beginners start off at the periphery but eventually become encultured and can ultimately assume the role of expert through “legitimate peripheral participation .”

The concept of situated learning has proven to be a fertile beginning for numerous other concepts, including those of John Seely Brown and William J. Clancey.

Relevance to Serious Games

The potential for games to create just the kind of environment Lave describes exists now – what’s lacking is a broad recognition of this fact.

  • Lave, J. (1988). Cognition in practice : mind, mathematics, and culture in everyday life. Cambridge ; New York: Cambridge University Press.
  • Lave, J., & Wenger, E. (1991). Situated learning : legitimate peripheral participation. Cambridge [England] ; New York: Cambridge University Press.

We learn by watching and interacting with others. This applies to knowledge, but also to behaviours and attitudes.

Relevance to Serious Games

We can learn by watching others play.

See Also
Relevance to Serious Games

Cognitive Learning Theory <style float-right>



[1896 – 1934] – Social Interaction, Zone of Proximal Development

Although Vygotsky’s work took place at about the same time as Pavlov, his ideas did not become widely known until long after he died. Vygotsky is best known for his proposition that cognitive development requires a social context in order to reach its potential. Through his theories about the “zone of proximal development”, he suggested that an individual could achieve far more with some help than he could alone. Further, the level of achievement possible with help (ZPD) varies from one individual to the next, and can be used as a measure of potential. “Experience has shown that the child with the larger zone of proximal development will do better in school. This measure gives a more helpful clue than mental age does to the dynamics of intellectual progress.” (Vygotsky, 1934)

Given Vygotsky’s emphasis on social interaction, he is one of the earliest and strongest champions of collaborative work, and in some ways it is not surprising that the idea still has not really caught on in North American school systems, except to an extent at the elementary level. The school system here remains very much an adversarial, competitive environment. This is easily evidenced by the continued reliance on homework where collaboration is typically not encouraged, and the tenacious adherence to ‘individual work’ and isolation during exams. While some of this has to do with cost-effectiveness and efficiency (out of school collaboration is likely to require technological support, and isolation is easier to invigilate during tests), I suspect much of this is due to the fundamentally competitive and adversarial nature of our educational system and its administrators.

Relevance to Serious Games

In most ways, game-based learning is highly collaborative; sometimes making use of peers; sometimes mentors, and sometimes a proxy in the form of the game AI. In this way the game environment actively supports Vygotsky’s ‘zone’. In fact, many games would be unplayable, or at least unchallenging if they did not rely heavily on a modern equivalent of Vygostky’s zone.


Learning Theories & Models as Expressed in Commercial Games

Below is a selection of relatively well-known learning theories and models. This section looks at how the theory is connected to or embodied in games. A connection to existing commercial game design is described for each one in the first group ([base] means it forms a basis for Serious Game Theory, and [implement] measn it is used in the design and implementation of games), and an explanation for exclusion is provided in the second group. (Original Source of list of theories:

  • ACT (J. Anderson) While I cannot buy the “we think like a program” theory, games can easily be used to implement the ACT ideas – this might work well to produce a portion of the AI in a game but it still does not help explain the kind of learning that happens while playing games, nor how. ACT is a modeling language of the AI variety - closer to Scheme, and Prolog than anything I would recognize as a learning or ID theory. It is a language that permits certain models of learning to be described or simulated, but it is not itself a model, nor a theory.
  • Adult Learning Theory (P. Cross) Games do provide a framework that supports the principles important according to CAL: use existing experience; adjust for limitations; increasingly advanced stages; choice over availability and organization
  • Andragogy (M. Knowles) [base] [used]
    • This theory should apply to ALL learners, not just adults –
    • We ALL
      • need to know why
      • need have some control (self-directed)
      • prefer experiential
      • just-in time
      • problem-oriented rather than content oriented]
  • Anchored Instruction (J. Bransford & the CTGV) [implement] [used]
    • It’s not a videodisc, but it sure is anchored around a problem situation and it permits exploration
  • Aptitude-Treatment Interaction (L. Cronbach & R. Snow) [implement]
    • well, duh! (matching instruction to aptitude helps learning)
    • once again, games can do this well
  • Attribution Theory (B. Weiner)
    • We attribute success internally/externally
    • Approaches to learning vary depending on type of attribution you tend towards
    • Games can certainly be designed with a sensitivity to both – in the same game; different parts of the same game; variations of one game; different games
  • Cognitive Dissonance Theory (L. Festinger)
    • Not sure where this one fits in
  • Cognitive Flexibility Theory (R. Spiro) [base] [used]
    • Multiple representations; don’t oversimplify; support context-dependency; case-based; constructive; interconnected
    • Games do all of this
  • Component Display Theory (M.D. Merrill) [implement]
    • It is possible to set up all of the requirements for CDT in a game format; the first level (before all the details) is a fairly good guide, but the rest becomes very picky and complex – I don’t see how it would be possible to meet the requirements without a program to control it. This one strikes me as an engineering approach. Learning is itself a wicked problem; so it is not possible for an engineering approach to be complete.
  • Computer Supported Cooperative Learning [discarded]
    • is neither a theory nor a model - it concerns itself with application tools for the most part.
  • Conditions of Learning (R. Gagne) [base] [used]
    • This is one that is already implemented in most good games
    • This one can be written up as a paper
      1. gaining attention (reception)
      2. informing learners of the objective (expectancy)
      3. stimulating recall of prior learning (retrieval)
      4. presenting the stimulus (selective perception)
      5. providing learning guidance (semantic encoding)
      6. eliciting performance (responding)
      7. providing feedback (reinforcement)
      8. assessing performance (retrieval)
      9. enhancing retention and transfer (generalization).
  • Contiguity Theory (E. Guthrie) [discarded]
    • Largely to do with animal training – stimulus-movement; doesn’t concern itself with reward/punishment; we tend to remember what works and forget what doesn’t
    • Doesn’t really apply to games – except that this principle of “remember what works” gets used as people progress through levels etc.
  • Conversation Theory (G. Pask) [discarded]
    • This one strikes me as simply a different way to describe existing principles – people need to learn relationships among concepts; in order to learn something one needs to teach it (Lancaster); some people like to do things sequentially; others like to jump around.
    • There isn’t anything distinct here.
  • Criterion Referenced Instruction (R. Mager) [implement] [used]
    • Mastery learning and performance-oriented instruction
    • Games are already all about this
    • Games could certainly be used as one of the media
  • Double Loop Learning (C. Argyris) [implement] [used]
    • Effective problem solving about interpersonal or technical issues requires frequent public testing of theories-in-use.
    • Double loop learning requires learning situations in which participants can examine and experiment with their theories of action.
    • Games are perfect for implementing this approach. People do this all the time in games.
  • Drive Reduction Theory (C. Hull) [discarded]
    • Early theory: more for physical tasks; satisfying needs/wants. Applies to kinetic games (Wii, Guitar Hero, DDR,..)
  • Dual Coding Theory (A. Paivio)
    • There are two cognitive subsystems: linguistic and other. Recall/recognition is enhanced by presenting information in both visual and verbal form. I’m sure that’s true any time you need to be able connect verbal and visual concepts, so if you need to be able to say something about what you’ve seen, then presenting it in both forms is a help. If you only need the information in its visual form (true for avoiding some dangers) then attaching words might actually interfere, or slow things down. It is useful to know that if you want people to be able to recognize and name things, it helps to present the information in both forms. Seems kind of obvious though.
  • Elaboration Theory (C. Reigeluth) [base] [used]
  • Experiential Learning (C. Rogers) [base] [used]
  • Functional Context Theory (T. Sticht)
  • Genetic Epistemology (J. Piaget)
  • Gestalt Theory (M. Wertheimer)
  • GOMS (Card, Moran & Newell) [implement]
  • GPS (A. Newell & H. Simon) [implement]
  • Information Pickup Theory (J.J. Gibson)
  • Lateral Thinking (E. DeBono) [implement]
  • Levels of Processing (Craik & Lockhart) [implement]
  • Mathematical Learning Theory (R.C. Atkinson)
  • Mathematical Problem Solving (A. Schoenfeld)
  • Minimalism (J. M. Carroll)
  • Model Centered Instruction and Design Layering (A.Gibbons)
  • Modes of Learning (D. Rumelhart & D. Norman) [base]
  • Originality (I. Maltzman)
  • Phenomenonography (F. Marton & N. Entwistle)
  • Repair Theory (K. VanLehn) [base, small]
  • Script Theory (R. Schank)
  • Sign Theory (E. Tolman)
  • Soar (A. Newell et al.) [implement]
  • Stimulus Sampling Theory (W. Estes)
  • Structural Learning Theory (J. Scandura)
  • Structure of Intellect (J. Guilford)
  • Subsumption Theory (D. Ausubel) [implement]
  • Symbol Systems (G. Salomon) [base]
    • Symbol systems affect who learns what from media
    • This tells me that games literacy (knowing about games & how to play them) is important to learning with games – at least, it is for learning with complex games
  • Triarchic Theory (R. Sternberg)
  • Algo-Heuristic Theory (L. Landa)
    • Suggests we can provide an algorithm for solving problems
    • I think this only works for a subset of tame problems
    • The value of using games is that it provides a framework within which individuals can work out their own way to solve problems; they can try again as often as necessary; they can change their strategy and try again - the point of using games is to NOT give people a recipe for solving problems but to give them a problem space and let them choose.


Here are other places you can look for more lists and additional information.

  • gd-theories.txt
  • Last modified: 2015/05/18 13:45
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