On the Architecture of Game Science

Physical Sciences

“Scientists are faced with the reality quandary, which refers to their unrelenting quest to determine the ultimate nature of reality or, in other words, to explain what the world they are studying ‘looks like’” (Van Gigch, 2002-b, p. 203). How do game scientists address this question?

In physics two parallel views on reality exist, one dealing with the macro world, the other one with the micro world. Einstein is the best-known physicist representing the macro world view of classical physics. For Einstein first comes the mathematical world of formal constructs as representations of the empirical world. Mathematical constructs constitute a model, which is a formal representation of certain conditions and states of the world. Postulates become verified through deductive reasoning. Conclusions are finally checked against empirical evidence. Those who are familiar with mathematical game theory will recognize this style of reasoning. Van Gigch (2002-b) noted that Einstein did not admit empiricism as a source of knowledge. According to Einstein, objectivity follows from the belief in an external world, independent of the perceiving subject.

In the micro world of quantum physics the certainty principle - well known in the macro world - is shattered. It states that the motion of a particle is completely determined if its position and its velocity are both known at a certain moment of time. In quantum physics both variables: position and velocity, cannot be measured at the same time with the same accuracy. This notion places the researcher for the choice – when accurate measurement is the goal - of either focusing on the position or on the velocity of the particle. Heisenberg’s uncertainty principle, states that the act of measuring affects the accuracy of the measurement. Van Gigch (2002-b) pointed out that the uncertainty principle altered the classical idea of objectivity, which pretended a possible disassociation between observers and what is being observed. Cassidy (1992), cited in Van Gigch (2002-b), remarked that in particle physics it is not possible to know both the present position and present velocity of an electron with absolute precision. If we know the present, we cannot calculate (predict) the future. Only the probability of one outcome among a range of possibilities can be predicted. In the classical description of a physical system (the macro world) the traditional meaning of the causal law becomes invalid in the micro world.

Another principle influenced modern physics: Bohr’s complementarity principle, based on the dual interpretation of the nature of light: the wave and particle interpretation. These two descriptions represent equivalent however distinct systems of observable events. Moore (1989) cited by Van Gigch (2002-b) pointed out that in quantum mechanics both interpretations cannot be used at the same time.

Heisenberg’s uncertainty and Bohr’s complementarity principle have had a great impact particularly on physics and more generally on science. Modern physics can no longer find a system of laws unambiguously tying effects to causes (Gleick, 1992). As in Einstein’s physics, no laboratory was needed, only theorems and formal theories were needed. In modern physics laboratories perform experiments to verify a mathematical theory. That approach has become the norm. Modern physics has progressed through the constant interplay of theorists and experimenters.

In order to qualify theories of physics Gell-Mann (1994) introduced the notion of ‘effective complexity’. Effective complexity is based on ‘the length of the message which is required to describe certain properties of a system’. The message must encompass a description of two kinds of properties of the system:

That definition, although developed for theoretical physics, can be extended to other domains such as, computer science. Applied to game science I have re-phrased effective complexity to become ‘algorithmic complexity’, and added ‘organizational’ and ‘organized’ complexity to broaden the scope to game science (Klabbers, 2009, pp. 101-102). In professional games, the message, ‘required to describe certain properties of a system’, can be quite elaborate.

Van Gigch (2002-b) noted that precision and complexity seem to be inversely related. Increasing complexity diminishes our ability to make precise statements about the characteristics of the system. This is in line with Thorngate’s postulate of commensurate complexity (Thorngate, 1976). Rephrasing it to game design it states that it is impossible for a game to be simultaneously general, accurate, and simple. The more general and simple a game is, the less accurate it will be in predicting specific behavior. This understanding has profound impact on the design tradeoffs of games (Klabbers, 2009, p. 184).

Based on these radical developments during the early 20^th century, physicists are introducing doubt, uncertainty, undecidability and imprecision into the world of physics. In the meanwhile, the rest of the scientific community, especially traditional economics, sociology, and psychology, are striving to become more exact, trying to introduce more certainty and precision into the domains of the social sciences (Van Gigch, 2002-b).

Einstein’s general theory of relativity and quantum mechanics are the two pillars of modern physics. In terms of Kuhn (1962), these two paradigms represent normal science: “Research is firmly based upon one or more past scientific achievements, achievements that some particular scientific community acknowledges for a time as supplying the foundation for its further practice. ….. Men whose research is based upon shared paradigms are committed to the same rule and standards for scientific practice” (Kuhn, 1962, pp. 10-11).

The feedback loop: from theory-to-observation (experiment), and from observation (experiment)-to-theory, is the legacy of the pioneering work of Rutherford, Einstein, Bohr, Schrödinger and many other physicists. It has become the standard methodology, the role model for scientific inquiry, which had a great impact on the social and behavioral sciences methodology.

Social Sciences and Humanities

Considering the variety of disciplines of the social sciences and humanities that contribute to game science, it is worthwhile to offer a modernist and post-modernist view that links them together. Soja (1993) remarks that the roots of modernity are found in the European Enlightenment, revolving around the development of an explicit critical awareness of the world “as a source of practical knowledge that could be accumulated and used to change the world, to make it “better”, rather than simply to reinforce and faithfully maintain the status quo. …… The discourse on modernity has thus always been a critical, intentionally enlightening, and potentially emancipatory discourse. …. In reaction both to classicism and theologism, the early Enlightenment turned to science and ‘modern’ scientific understanding as the primary basis of praxis, the transformation of knowledge into presumably beneficial, progressive, social action” (Soja, 1993, pp. 115-116).

Schatzki (1993) argued that philosophically speaking modernity is based upon two pillars, one epistemological, the other political. The epistemological pillar concerns the search for the foundations of knowledge and values. The political pillar encompasses the realization of autonomy, freedom, individual rights, and democracy. Together they carry the roof: humanity’s self-determination or self-assertion.

Gill (2000) mentioned that modernity dominated the nineteenth century. It is characterized by “a basic belief in the notion of progress, coupled with a deep confidence in the ability of human thought to comprehend the essential structure and meaning of human existence and reality itself…In Hegel’s words, “What is real is rational and what is rational is real” (Gill, 2000, p. 2). Kierkegaard, Marx and Nietzsche - attacking modernism - rejected Hegel’s rationalistic idealism. During the first three quarters of the twentieth century representatives of logical positivism, logical empiricism, and analytical philosophy, such as, Russel, the early Wittgenstein, and Carnap sought to refine modernist thought. Currently the traditional social sciences are followers of the standard methodology of physics in their efforts to become more exact, being more in line with the scientific rigor of physics, as sketched above. They are concerned with refining modernist philosophy.

Modernist philosophy restricted the definition of knowledge to include only those ideas and assertions that can be grounded in sensory experience and tested by empirical methods. The verifiability criterion of meaning and truth became the cornerstone of scientific knowledge acquisition both for the natural and social worlds. That positivist approach to knowing – making a definite distinction between fact and value - expressed the modernist confidence in rationality and progress, a view that in the nineteenth century gave rise to the social sciences (Gill, op. cit.). From this perspective, the physical sciences are part of modernist philosophy.

Post-modernist philosophy focused on refashioning that definition of knowledge. Existentialist or phenomenological thinkers such as, Sartre, Heidegger, Kierkegaard, Bergson, Husserl, and Camus sought to replace the modernist vision of human rationality. They emphasized the personal, subjective aspect of human experience: the existential understanding. Gill (op. cit.) noted that postmodernists argue that there is no ultimate ground for any and all knowledge claims. They approach “interpretive activity as an opportunity for free and creative exploration of meaning in general, as well as of the meaning of the meaning of specific actual and/or interpretive claims” (Gill, p. 5). According to Derrida, meaning is always a matter of interpretation. The results one gets arise from where one starts and the road one takes. That notion sets us free to play with language, both written and spoken, discovering new meanings hidden within the traditional structures of grammar (Gill, 2000). That sort of play also applies to the grammar of games. We are free to play with the structure of games, and as a consequence with their semantic. Foucault (1980) has further developed this understanding in the sociopolitical domain. He stressed the fact that each and every point of view arises within a given context and is positioned by certain persons who have specific goals in mind and interests to promote. As contemporary spin doctors in the political arena will agree: there is a definite spin or twist that comes with and largely directs any given value proposal or cognitive claim. It blurs the line between fact and fiction.

Soja (1993) mentioned that rather than being mutually exclusive, modernity and postmodernity are intertwined. “Every contemporary individual and social grouping is simultaneously modern and postmodern, albeit with great variations in their relative intensity and explicit proportion” (Soja, 1993, p. 113).

Humanities, including literature, philosophy, history, art, and musicology, use interpretative, critical speculative methods, allowing for greater cognitive freedom and creativity than the ‘modernist’, empirical approaches of the mainstream social sciences and behaviorism in psychology. Referring to postmodernist thought, Van Gigch (2002-a) and Giddens (1993) promote a new methodology for the social sciences.

Applying these postmodernist notions to game science, one can gather that in a game it becomes clear that assertions and actions are a function of the designer’s and player’s intentions in conjunction with the social and linguistic conventions, embedded in the rules and symbols that represent the game resources. Obviously, the designer’s and player’s intentions may not mesh with each other. Playing a game is performing an interpretive act, constituting a hermeneutic process.

The nature of reality for the social sciences and humanities refers to the social ontology: the theoretical study of the basic constituents of social reality (Schatzki, 1993). Modernists and postmodernists will address these constituents of social reality differently, as they use varying meanings about the nature of complexity, heterogeneity, and diversity in social life.

Being aware of, and understanding the impact of advances in modern physics, and being knowledgeable about the ongoing debate between modern and postmodern styles of reasoning is a prerequisite for understanding the challenges that game science is facing. (It is out of scope of this paper to discuss modernism and postmodernism in more detail.)

The Gold Standard of Scientific Research

Both modernist and postmodernist researchers place themselves in the position of observers - outside interpreters - applying different approaches to the analytical science. [Analysis: The process of considering something carefully and in detail in order to understand or explain it. Collins English Language dictionary, 1987] Although modernists and postmodernists pursue different goals, and present different knowledge claims, they all belong to communities of observers, applying an analytic science approach.

Van Gigch (2002-b) presented the following characteristics of knowledge in the physical sciences domains: The physical sciences deal with closed systems that are non-purposeful or goal-seeking. They use mathematical theories and models that they rigorously test via empirical/experimental studies. The physical concept of reality, and what can be known, is based on discovering an external world, independent from the observer. Van Gigch (2002-b) argued that in physics discoveries and laws are grounded in strict scientific rigor, guaranteed by proofs. The validity of its major theories is the ultimate scientific credential. Physics has achieved the highest possible level of sophistication. Its scientific method is the standard for all other sciences. In addition to the classical canon of exactness and precision, the study of particle physics has introduced new principles in the world of physics, enlightening doubt, uncertainty, unknowability and imprecision. As a consequence, physics has grown less exact. The scientific communities outside the world of physics, during the twentieth century have increasingly tried to copy the scientific approach of physics. This applies especially to the social and behavioral sciences, aiming to become more exact by introducing more certainty and precision into their knowledge claims. During the twentieth century, the following recipe has become the gold standard of scientific inquiry in the social and behavioral sciences:

The related rigid rules of enquiry are necessary to isolate and protect phenomena from flawed analysis. The principle of control, randomization, and comparison is a precondition for establishing valid cause-effect relations between treatment and outcome” ( Klabbers, 2009 , p. 218).

Regarding game science, this standard is most suitable to mathematical game theory: the study of formal models of conflict and cooperation (Von Neumann & Morgenstern, 1944). Although highly successful in economics, from the broader perspective of game science we need to be aware of the following restrictions of the formal game theory. Mathematical models provide a potentially misleading feeling of realism about the social world through the ‘objectivity’ of the model. They overemphasize quantitative aspects, focus on explicit, rational, and simplified knowledge. Many intangibles of the social world are difficult - even impossible - to formalize, yet they play a vital role in social affairs. The players can only choose from a limited number of prescribed alternatives. The discovery of a problem, the invention how to deal with it, and elaborating a plan are out of the scope. Therefore, the formal game theory is too narrowly rational, to cover the whole field of game science. Its scope is too limited. We have to be aware that the knowledge claims in game science cover a much broader spectrum of knowledge domains than addressed by formal game theory.

There is another - more pragmatic - reason why the scientific method is less suitable for game science. Usually, an adequate budget for performing evaluation studies is not available for rigorously testing the validity of games, especially when field studies are involved. Even quasi-experimental designs do not leave much financial room for the randomization of subjects over the experimental and control groups. Moreover, “the various experimental designs offer trade-offs among the principles of control, randomization, and comparison. The core question of the textbook-style laboratory experiment concerns dealing with the following tensions. Chatterji (2005) noted that to different degrees, such trade-offs threaten the internal validity of the experiment, preventing conclusive causal linkages to be made between the treatment and outcome variables, or to the external validity (generalizability) of the findings. Highly controlled experiments are so closed (sealed of) that they reduce the external validity because they create unrealistic laboratory-like conditions that cannot be replicated in actual settings where an intervention is eventually implemented. More loose controls, on the other hand, diminish internal validity, permitting inferences only about the gross effects of the intervention rather than its net effects (Rossi, Freeman, & Lipsey, 1999)” (Klabbers, 2009, p. 218). In game science, for many fundamental and practical reasons, the gold standard of inquiry is not a realistic goal to achieve. In order to ensure cross-fertilization of ideas, in game science, they need to be integrated in the specifications of the design of games. (For a more elaborate discussion about the shortcomings of the gold standard of the analytical sciences, see Klabbers, 2009, chapter 7.)

Postmodernist researchers have refined the scope of the observer. Nevertheless, they also perform their studies from the position of the outsider. Giddens (1993) referred to single- and double-hermeneutic: hermeneutic being the study of the methodological principles of interpretation (www.merriam-webster.com/dictionary/ hermeneutic). He distinguished the single hermeneutic of natural science and double hermeneutic of` the social sciences. “The development of science is constantly interwoven with, and affected by, social influences and interests that nominally stand outside of science itself” (Giddens, 1993, p. 150). The natural sciences stand in a subject-object relation to their field of study. The resulting meaning-frame of the single hermeneutic – separates it from the meaning frame of the social sciences, which stand in a subject-subject relation to their fields of study. Contrary to the world of nature, the social sciences deal with a world that through language already is pre-interpreted.

Faces of knowledge

Barth (2002) has offered an interesting view on the anthropology of knowledge that is also relevant for game science. He argued that knowledge always has three interrelated faces: a social organization within which activities take place, a substantive corpus of assertions it makes use of, and characteristic media of representation through which it is cast and communicated. He showed how these three faces interrelate in particular ways in cultures such as, in New Guinea, Bali, and a modern biochemical laboratory. I will apply his framework to the study of games.

In any game, these faces of knowledge appear together in the particulars of action, the transaction of knowledge, and in every performance of the players. Barth argued that their systemic interdependence arises by virtue of the constraints that these three aspects impose on each other in the context of every particular application. During gameplay, specific local circumstances determine how the mutual influences between the faces of knowledge are affected. Translating Barth’s anthropology of knowledge to game science, and referring to the interconnected building blocks of games, the game designer will have to define:

Through combining these interrelated faces of knowledge, games temporarily shape and represent typical cultures.

Knowledge Claims

For the design and study of games, which knowledge claims apply to the actors, the rules, and the resources? Assertions either describe how people connect to one another and shape the social organization (social infrastructure), or how objects connect in the physical world and give shape to various material infrastructures: ranging between the built environment of primitive human settlements and the highly sophisticated infrastructures of current industrial societies. In game design terminology, one group of rules connects to the social organization, while another group defines the structure and process at the level of the resources. Therefore, for addressing the question about knowledge claims it sufficient to only make a distinction between knowledge claims that refer to the social organization, and those that refer to the resources. Table 2 summarizes the knowledge claims presented above in relation to the generic structure of games.

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Table 2.

Representation of the Generic Structure of Games Linked to Faces of Knowledge.

Generic structure of games	Faces of knowledge
Actors	Social organization
Rules
Rules	Resources
Resources

Knowledge Claims About the Social Organization

For the design of games, the special circumstances that apply to the faces knowledge vary. It is crucial for game scientists to be aware of two fundamentally different positions to make knowledge claims: the observer’s and the player’s position. Both, acting from different positions, deal with different although related realities. They represent different, however linked knowledge claims. Making the players an integral part of the epistemological considerations, and giving them a voice in knowledge production makes game science special.

Knowledge Claims of Observers and Players

Scientific research advances with the scientist in the position of observer, aiming at discovering and explaining (causal) relationships between the entities of study. Researchers in physics, in the traditional social and behaviorist sciences, following the modernist tradition, and also the postmodernist scholars, place themselves in the observer’s chair. They act from the position of power with regard to their subjects of inquiry: they are the one who define what is real. Even for the postmodernist it presumes an epistemology, a way of thinking about reality, which as such is disconnected from the experience of the players. As Maturana and Varela (1980) learned from their experimental research, perception (sensing and interpreting) should not be viewed as merely grasping an external reality. As can be learned from psychological experiments about apparent movements, the perception of the observer is a constructive activity (Klabbers, 2009, p. 215). However, perception and interpretation are not the exclusive privilege of the researcher. It is a generic human capability that also applies to the players of a game. In game science, that constructive capability has important epistemological consequences.

Applying Maturana and Varela’s findings to game studies, it is both inadequate and misleading to link processes of social organization with causal relations. Linking processes of social organization with causality is misleading because it obscures the understanding of the experiential domain as determined by the individualities of the players that generate them. It is inadequate because that notion of causality pertains to the domain of descriptions (theories; conceptualizations) by an observer, making commentaries about actions and interactions in the game. Those commentaries are only relevant in the meta-domain of that outside observer. They cannot be deemed to be operative in the experiential domain of the players (actors), the objects of the descriptions. In this regard, Sutton-Smith is a well-known representative of the community of observers. In his book: The ambiguity of play he presented ten rhetorics concerning play theory. He pointed out: “… the rhetorics of play express the way play is placed in context within broader value systems, which are assumed by the theorists of play rather than studied directly by them” (Sutton-Smith, 1997, p. 8). Each rhetoric pertains to the domain of descriptions (theories; conceptualizations) by an observer, making general commentaries about games and play.

In game science, in principle the interpretation of reality by the observer is distinct from the experienced reality of the players. Epistemologically they engage in two different – although connected – reality definitions. From the viewpoint of postmodernism, both the observer (the outside researcher), and the players (the inside participants) should be given the autonomy to act on the basis their varying values and experience, and interpret what they know-in-action. In game science the knowledge claims of observer (the outsider) do not necessarily match with those of the players (the insiders). This understanding makes evaluating game sessions tricky if only the reality definition of the observer is what counts, when developing and testing game theories.

In game science, it is the designer’s major task and responsibility to shape the proper and just conditions for the players to enrich their understanding of the situation, to experiment with, improve, and broaden their thinking and acting repertoire with the goal to change the existing situation into a more preferred one. In other words, it is the major task of the game designer to enable the players becoming co-designers.

Meaning frames are developed by and available for active subjects. They enter into shaping that world. The construction of social or behavioral theory is an interpretive act about an already interpreted social world. Therefore, it constitutes a double hermeneutic. The social sciences deal with a world which is already interpreted and constituted by its subjects of study. Giddens argued that the single hermeneutic of the natural sciences should not be separated from the social world, from lay beliefs and common sense. The concepts and findings of the natural sciences, which result from a single hermeneutic, impact on the social world through conceptual and technological interventions, which human beings make into that world of nature. This understanding corresponds with Maturana and Varela’s distinction between the domains of descriptions and experience.

In game science these dual meaning-frames play a vital role in the design and conduct of a game. The game designer generally makes use of the double hermeneutic, borrowing from the meaning-frames of the contributing disciplines as well as setting proper conditions for the meaning-frames of the players becoming manifest. The designer has to ensure that the game connects to, and stimulates the interplay between these frames. Guided by the rules of the game, the players interact with one another, which is the outcome of their, already available, constituting skills. Natural language plays a fundamental role in the “constitution of interaction both as a medium of description (characterization) of acts and as medium of communication between actors” (Giddens, 1993, p. 158). During a game session, descriptions of acts and communication acts are closely interwoven with one another; hence the use of language itself is a practical activity. Understanding what is happening during gameplay (Verstehen) is the basic condition of being able to understand characteristics of human society. It is produced and reproduced by the players.

Referring to the building blocks of games: actors, rules, and resources, the interactions between the actors shape a social organization with a specific structure and process. Interpreting Giddens’ view on the dual role of structure for game science, the interactions during a game are constituted by and in the conduct of the players; structuration, as the reproduction of practices, refers abstractly to the dynamic process whereby structure come into being (Giddens, 1993, p. 128).

In Giddens’ terms, the duality of structure in a game means that the structure of the emerging social organization is both constituted by the players and yet at the same time it is the very medium of its constitution. The players use the structure to communicate and interact with each other, and by doing so they reproduce that structure. Therefore, structure in social organization is not external to social actors. It follows from the ongoing interactions and communication between the players.

In a game the players draw upon rules and resources, and thereby reproduce them in the course of the game. Especially in free-form games (free play) the players have self-organizing, transformative power. As Mouzelis puts it generally for social theory:

“Actors often distance themselves from rules and resources, in order to question them, or in order to build theories about them, or - even more importantly - in order to devise strategies, for either their maintenance or their transformation” (Mouzelis, 1991, p. 27-28).

In rigid-rule games, the players can only play by the rules and only use the resources provided by the designer. They may question them. However, they don’t have the power to transform them. They can only act and communicate within the constraints of the well-defined game space. With respect to free play, the players together define the social organization, rules and resources, and thereby produce and self-reproduce the game space.

The most important understandings from social theory that are vital for advancing game science, are Giddens’ distinction between single- and double-hermeneutics, and the duality of structure. In line with Giddens, Maturana and Varela distinguish between levels of description by science (single hermeneutics) and the experiential and interpretation level of the players. Game designers, and facilitators, need to be aware of the first-order and second-order hermeneutics, and of the duality of structure, otherwise they run the risk that the professional game is not usable for the purpose to which it has been designed, and/or that they devise assessment procedures that miss the point.

Although these authors recognize the dual meaning-frames of social organization, they still place themselves in the position of the observer: the outside interpreter of meaning. Their postmodernist thoughts are most important, however insufficient for game scientists.

The Players’ Experiences

A key question that has not yet been addressed concerns the experiences of the players. What knowledge claims can be gathered from and by the players? What can we learn from their cognitive activity? How do they (re-)construct knowledge?

In accordance with the modernist view on knowledge, sketched above, Popper is in favor of eliminating entirely the personal element in knowledge claims; see “Epistemology without a knowing subject” (Popper, 1967/1970). That position, if being applied to game science, would exclude the experiential level of the players completely from the discourse. Contrary to Popper, Polanyi places the epistemic process squarely within the context of the personal and social dimensions of human experience. Acquiring knowledge is a clearly human enterprise. The results of those efforts cannot exist independently of humans (Gill, 2000).

Instead of trying to ground knowledge on some sort of foundation that should provide a common basis for knowledge claims, Polanyi places the act of knowing at the center of personal experience. It is out of the scope of this paper to elaborate Polanyi’s epistemology in more detail. (The interested reader should among others, turn to Gill, 2000; Polanyi, 1964, 1966). The person positions himself in physical and mental space through continuously gearing up to the shifting circumstances. Adapting Polanyi’s thoughts to game science, three dimensions of human cognition play a vital role in that positioning process (Klabbers, 2009, pp. 71-72; Gill, 2000), see Table 3.

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Table 3.

Representation of Human Experience.

Dimensions	Tuning cognitive activity
awareness dimension	focal ____________________ subsidiary (figure/background relationship)
activity dimension	conceptual ___________________ bodily
articulation dimension	pronounced ___________________ silent

Contrary to the common use of dimensions, conveying a dichotomy between the knower and the known, the experience comprised of distinct and independent abstract objects, and contrary to dualistic and atomistic understandings of experience, Polanyi construes our experience as constituted of three simultaneous, interpenetrating dimensions. This way of modeling experienced reality avoids the tendency of modern thought to separate the various aspects of knowing from one another (Gill, 2000). The person continuously positions him-, or herself in three dimensional mental and physical space. Neuro-cognitive embodiment is the clue for the knowing subject. The dimensional construing of experience allows for a mediational understanding of the structure of reality.

The Awareness Dimension

If something, or someone (A) is the focus of our attention, then we are only subsidiary aware of the situation and the persons and objects (B) that populate it. The focal object A is always identifiable, while simultaneously we are subsidiarily aware of objects B that may be unidentifiable. Would we switch our attention to another object, for example B, then B becomes the focus of our attention, and we would only become subsidiarily aware of A. Gill (2000) illustrates this as follows: “As the reader focuses on the meaning of these very words he or she is only subsidiarily aware of the fact that they are written in English, and that they follow certain rules of grammar? Physiologically speaking, one is focally aware of the markings on the page but only at the best subsidiarily aware of the movements of the muscles controlling the eyes” (Gill, 2000, p. 32). Tacit knowing is closely related to proprioception, which signals the muscles and joints, and the starting point of the movements. Subliminal sensing also plays a role. The brain picks up sensory stimuli, below the individual’s threshold for conscious perception. Both provide background information throughout the course of our mental and bodily actions. Proprioception maintains a monitoring function to check that the intended movements are indeed carried out. It plays a vital role in learning new skills.

What is focal in one situation at one moment in time may become immersed in the context the next moment, while simultaneously another object or person may enter the focus of our attention. We permanently attend from some things to others. From Gestalt theory we learn that the context influences the meaning of what is the focus of our attention. While playing a game we continuously shift our attention along the awareness dimension.

The Activity Dimension

According to Polanyi’s analysis, the awareness dimension of experience is intersected with the activity dimension, switching between the bodily and conceptual poles, functioning like an electromagnetic force field, serving both to define and sustain each other (Gill, 2000). Human action is always a blend of the bodily and the conceptual. Our personal development from child to adult involves moving along the activity continuum toward increased intellectual achievement and conceptual understanding, in addition enriching and deepening our embodied knowing, among other through improved proprioception. Nevertheless, also as adults we engage in bodily activities to perform purely conceptual tasks. We learn to connect intentionality and conceptual understanding. In sports this dynamic tuning of the bodily and conceptual is basic to the performance. As Weick (1979) puts it: How can we know what we think until we hear what we say; see what we do?

Combining these two dimensions of human cognition produces what Polanyi terms ‘explicit’ and ‘tacit’ knowing Gill (2000). Explicit knowing places the conceptual in the focus of attention, shoving back the bodily experience to the background. Tacit knowing combines the bodily and subsidiary poles. These two intertwined modes of experiential knowing define human cognition. Tacit knowing is embodied, and embedded in situated awareness. It is a silent body language.

Although sufficient to describe human cognition and related experience these two dimensions are incomplete regarding game science. For understanding what happens during a game session, in addition we need a third dimension: the articulation dimension.

The Articulation Dimension

In a game session, players, for various reasons may choose to keep silent or be pronounced in their ways of acting. For tactical or strategic reasons, or because they are shy, they may decide to refrain from engaging in the conversation, not articulating their explicit knowing. It may also be that they want to dominate the discussion, and consequently become very articulate. These considerations influence the dynamics of a game, as they directly impact on the focus/subsidiary dimension. Who is the focus of attention, for how long, and who is not?

The combination focal-conceptual-pronounced brings forward articulated explicit knowing, which can be shared and demonstrated. It stresses ‘knowing that’. The combination subsidiary-bodily-silent constitutes tacit knowing, the body language that is richer than can be expressed through words. It encompasses affects, emotions, and feelings that often teach us that intellect is not always in command. It links to ‘knowing how’. Explicit knowledge can be coded and transmitted via a computer. Tacit or embedded knowledge is highly situation specific and less diffusible across groups than explicit knowledge. It resides in individual and social relationships. It can primarily be revealed and communicated via face-to-face relationships: the body language of the players in the game (Klabbers, 2009). It acts as a compass that guides moving through the social organization.

In a game the knowledge claims about the social organization need to pay explicit attention to the experiential level of the players, and the way they interpret the social situation they take part in. Players are engaged in self-referential meaning processing. This understanding presumes a triple hermeneutic of the players who are trying to make sense of what happens during game play, in addition to the single hermeneutic of the natural sciences, and the double hermeneutic of the social sciences, which are already included in the game structure. While assuming their roles, the players enter the world of the single and double hermeneutic embedded in the design, and start constructing their particular explicit and tacit knowing of the evolving situation: developing a triple hermeneutic.

Those who study games – the observers - should be aware that the double hermeneutic they use to interpret what is happening at the experiential level are not a proper position to adequately read the tacit knowing of the players. They should also be aware of their own tacit knowing while making observations about a social situation that to a large extent is intangible, and hiding from their perceptions. The facilitator is in a better position as s/he is able to tap the explicit and tacit knowing that emerged from gameplay. Through the debriefing, while focusing on ‘reflection-on-action, s/he can stimulate the reflexive capabilities of the players. Without a debriefing, assessing what happened during a game is limited to explicit knowing. Explicit knowing, although important for assessing professional games, may lead to a narrowly rational approach to knowledge. Ignoring mutual tacit knowing between the players - what may have really happened during a game - may lead to completely wrong conclusions and recommendations, because it may lack information about what is meaningful for the players.

Game designers, facilitators, and evaluators should be aware of Polanyi’s paradox (Polanyi, 1966). People know more than they can express through language. They are not always able to articulate what they know, what competencies they have, what they want, and what they can do. Properly tapping both explicit and tacit knowing in evaluations studies, needs much more thorough attention from game scientists than currently is the case. Generally, evaluation studies focus on the surface of the game experience by addressing questions that are related to explicit knowing. However, there is a cost involved, tacit knowing is being neglected.

Knowledge Claims About the Resources

Action is a quality of the individual, of the social organization, and of collective networks. In the context of game science, speaking of an individual player is to speak not just of a subject, but also of an agent, or actor, demonstrating purposeful behavior, applying knowledge to secure certain outcomes, or to set in motions events. Such actors have the capability for reflexive monitoring not only their own behavior, but also that of the other actors in the game. Action involves the application of means to achieve outcomes through the interventions of an agent in a course of events. Power is the capacity of the agent to mobilize resources to constitute those means (Giddens, 1993).

In game science the social organization enacts the power to mobilize these resources. The great variety of games is an expression of the great variety of resources that are being used. In general management games, manufacturing products and services are the means to achieve business goals. They represent the resources in the game. In a healthcare gaming, the surgery with all its equipment are resources of the operating team. In urban management gaming the physical infrastructure embedded in the natural environment is a resource. In war games, the terrain and the military equipment are the vital resources. In video games, the avatars use various resources to act and move in a virtual landscape. The great diversity of games is an expression of the great variety of resources and related media of representation that are utilized in game design.

In general, the resources in a game represent material and information processes that are considered vital for achieving purposes. Information flows deal with explicit knowledge that is coded and transmitted. As pointed out above, a great diversity of media of representation are available for mapping resources. They represent the many faces of knowledge that can be embedded in game design. They range from signs, symbols that are being used during consecrations, holy dances, sacral contests, to mathematical language used for computations, to images in gross anatomy atlases, to technical laboratory equipment for microbiological experiments, micro-economic models for business simulation, chemical models, geography atlases and scale models, flow diagrams of technological processes, and so on. Regarding board games, media of representation are: the configuration of the board, and the imagery of the pieces on the board. As mentioned earlier, media of representation shape both thought and action and thus the practices of the players.

Underlying those media of representation are the different inference schemes of the contributing disciplines. Referring to Giddens (1993), these schemes are meaning-frames shared by members of a discipline. For each discipline they prescribe how to interpret the particular knowledge domain. As a consequence, with respect to the resources, each contributing discipline brings forward a typical knowledge claim. For example, in video games, the movement of the objects in virtual space need to obey laws of physics. Combining various knowledge claims in game design is an art, a craft and a science.

Wrong Labeling: Serious Games and Gamification

As games are forms of play, a great variety of forms are available. To understand their differences and commonalities, various classifications of games have been developed and applied (Klabbers, 2009, chapter 2). The related terminology is more than a mental puzzle. It concerns the internal consistency and coherence of the basic concepts that support the architecture of games. It concerns the credibility of game science, making it intelligible to outsiders.

Classifications in science serve to make distinctions between classes of objects in unequivocal ways. Each classification introduces a typical class of objects (games are artefacts) that assigns particular qualities to them. Comparing classifications of games should enhance fruitful communication among game scientists and professionals. The resulting debate is a prerequisite for advancing the field.

Gamification

Transforming the workplace into a real-time, finite and infinite playful game would be a great idea. That would be an interesting example of the use of games to enhance workplace learning (Klabbers, 2009). “Workplace learning - on the job learning and training - addresses the demands of global marketplace and the subsequent need for continuing professional learning. The idea of workplace learning acknowledges that learning is context dependent, that workplaces with differing sociocultural practices promote differing abilities, and that workplace cultures are important in determining what is learned, and how it is learned” (Klabbers, 2009, p. 67).

However, that is not what gamification in business practice is all about. For the sake of clarity of the argument, I further will make a distinction between gamification-as-business-practice, and gamification science as elaborated by Landers, Auer, Collmus, and Armstrong (2018).

Gamification science is a recent offspring of the behavioral sciences. As Landers et al. (2018), point out, it links the post-positivist epistemology of the social sciences with game science. It uses elements of the game science toolkit, and assesses how they may affect the behavior of individuals in organizations.

Gamification-as-business-practice runs the risk to be applied to manipulate and exploit people. Under these circumstances, it is a management technique to modify behavior through a simplistic reward system to benefit short-term, narrowly economic business interests: points, badges, leaderboards, levels and so on. Although used in games, as such they are not an intrinsic quality of games. They are so-called paraphernalia that can be used interchangeably. A game is more than the sum of its parts. It does not embed the players as individuals, but as actors, assuming organizational roles. The players form the social organization in the game.

Would gamification aim at organizational processes, then those involved in game design would have to consider which organizational configuration would be most suitable to address the play element of the organizational culture, considering that play includes voluntariness, spontaneity, and desirability for its own sake. Games are linked to rules that guide and facilitate the processes that generate the players’ experiences, understanding, enlightenment, commitment, fun, hope, knowing-in-action, and reflection-in-action.

How would such a game look like in each one of the following organizational configurations: the machine bureaucracy, the divisional form of organization, the professional bureaucracy, the simple structure, the adhocracy, the open systems form, the matrix and project organization, the mechanistic and organistic organization, the learning organization, or in new forms of organization that show an increased fluidity in the external appearances such as, chains, clusters, networks, strategic alliances, and virtual organizations (Klabbers & Gust, 1998)? In terms of game science, all these different organizational structures apply different vertical and horizontal communication rules that allow for and trigger varying degrees of playfulness among management and staff. In other words, these varying organizational configurations require different sets of rules. Each of these configurations offers the staff a different game space, allowing them more or less autonomy, freedom to act. It all concerns the play element of the business culture. One particular organizational form that sticks out to be the least playful working environment is the bureaucratic organization. Unless those games are played according to their specific rules, they are not games at all.

Translating these work environments into the framework of organization theories, ‘gamifiers’ apply a behaviorist approach to managing the workplace, to improve performance. Gamification, thus understood, acts as a form of operant conditioning in Pavlovian sense, leveraging worker’s desire for competition, achievement, and status. Management uses points, badges, leader boards, and rewards by pressing those “buttons”, and the staff starts eliciting “conditioned responses”. The dogs and pigeons in those operant conditioning settings are replaced by the workers. From that viewpoint, the term “gamification” could better be substituted by the term “Pavlovication” of the workforce. Bogost (2011) views the term a marketing fad. He suggested “exploitationware” to be a more suitable name.

Following the sloppy use of the term “serious game”, discussed above, gamification is a next example of slipshod language based on that untidy terminology. Gamification-as-business-practice does not seem to be concerned about the unique qualities and characteristics of games, as for example expressed through general management games since the 1950s. It obscures the very idea of playful gaming in working conditions.

Conclusion: The term “gamification” does not meet the requirements of a proper scientific description of games. Gamification science takes game elements, one at a time, to be used in a non-game environment. From management and organizational science perspective it does not specify the organizational configurations in which those game elements can be embedded. The core of gamification science may be a design process of work conditions, a form of task structuring, it is not about game design as understood in game science (Klabbers, 2009).

The gamification science methodology puts it squarely in the applied behavior sciences. Gamification science should not be considered a sub-discipline of game science. For reasons elaborated above, the terms: “serious games” and “gamification”, do not fit into game science terminology.

Summarizing comment

The macro-cycle conveys that the interactive learning environment is focus of attention, the unit of study. A game should always be integrated in that broader scheme. The interactive learning environment defines the scope of the game. It constitutes the conditions for and context of playing the game. The professional facilitator is accountable for the proper design of that learning environment.

Social Problem Solving

Shortcomings of the applied sciences: Even when the analytical sciences have produced valid knowledge from laboratory experiments there is no guarantee that it can be successfully applied in real world settings.

“Knowledge – in the rationalist tradition sketched above - is general, theoretical, and propositional. It enjoys a privileged position in academia. While teaching professional knowledge, many methods of didactic education assume a separation between knowing and doing. Knowledge is treated as an integral, self-sufficient substance, theoretically independent of the situations in which it is learned and used ( Brown, Collins & Duguid, 1989 ). …. Accordingly, professional activity consists of instrumental problem solving made rigorous by the application of scientific theory and technique ( Schön, 1983 ).

From a practical point of view there is a growing crisis of confidence in this type of professional knowledge and consequently in this type of knowledge transfer by our educational institutions. Schön (1983, 1987) has argued that professionally designed solutions to public problems have had unanticipated consequences, sometimes worse than the problems they were designed to solve. He observed that newly invented technologies, professionally conceived and evaluated, have turned out to produce unintended side effects unacceptable to large segments of our society. In order to be able to cope with complex, uncertain and unique social situations, Schön has proposed the term problem framing: a process in which we interactively name the elements and attributes to which we will pay attention, and frame the contexts in which we will pay regard to them ( Schön, 1983 )”, (Klabbers, 2009, p.65).

There is another reason for being critical about the knowledge claims of the analytical sciences. Because of the complexity of many social and political problems and the existing scientific uncertainties about future scenarios, consider for example global climate change, the credibility of the analytical sciences is questioned.

“ Wynne (1992) noticed that the discussions about uncertainty seemed to rely implicitly on the naive notion that inadequate control of environmental risks is due only to inadequate scientific knowledge. He criticized this idea, and added the concept of indeterminacy as a category of uncertainty. Indeterminacy refers to the open-endedness (both social and scientific) of the processes of environmental damage caused by human intervention. Indeterminacy introduces the idea that contingent social behavior, including decision and policy makers’ behavior, has to be related to the analytical and design science frameworks. It also acknowledges the fact that many of the intellectual commitments, which constitute our knowledge, are not fully determined by empirical observations. The latter implies that scientific knowledge depends not only on its degree of fit with nature, but also on its correspondence with various social constructions of reality. The richness and reach of knowledge transfer depends on its success in building and negotiating trust and credibility for science. In addition to Wynne’s comments on knowledge construction, it is worthwhile to realize that different scientific disciplines define knowledge differently, and that these differences play an important role in the debate about Global Climate Change (Klabbers, 1996-a; Klabbers et al. 1995). Referring to the term post-normal science ( Funtowicz & Ravetz, 1993 ) for issue-driven research in a context of hard political pressure, values in dispute, high decision stakes and high epistemological and ethical systems uncertainties, the puzzle-solving exercises of normal science (that is: analytical science in the rationalist (Kuhnian) sense) are no longer appropriate when society is confronted with the need to resolve policy issues regarding unquantifiable trans-national and trans-generational environmental risks” (Klabbers, 2009, p. 197).

Referring to the analytical and design science we have to be aware that, dependent of our professional background, we frame problematic situations in different ways. Schön (1987) distinguished two zones of practice: determinate and indeterminate zones. Determinate zones are characterized by the following conditions. They are ordinary in the sense that they are common. Practices are widely used. In professional practice, there is certainty about the knowledge needed to deal with the issue, and consensus exists among the stakeholders about the values at stake. Contrary to determinate zones, indeterminate zones are characterized by uniqueness, uncertainty, and dissension about values. Determinate zones of practice lend themselves for instrumental problem solving, based on technical rationality. Artistry is well tuned to deal with indeterminate zones. The partially indeterminate zone is the area of professional practice that requires craftsmanship. The framework of Table 5 summarizes Schön’s ideas.

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Table 5.

Linking Professional Competences With Zones of Practice.

Professional competences
	Zones of practice
Conditions⇓	Determinate	Partially determinate	Indeterminate	Conditions⇓
OrdinaryCertainHarmony	Instrumental problem solving Systematic application of techno-scientific rationality; Routine application of facts, rules, and procedures to problematic situations; Knowing that ;	Craftsmanship Searching for the best practice in existing situation; Knowing how; Knowing- in-action;	Artistry Dealing with processes of continuous change and renewal; Continuously anticipating course of events & adjustment of plans; Reflection-in-action; Reflection-on-action;	UniqueUncertainConflicted

With this frame of reference in mind, applying it to game science, to design science and social problem solving, Table 6 illustrates the linkages between applied science, rule-based gaming, and free play. Flight simulators represent the generic structure of rule-based games. The structure of the social organization, and the resources and their coupling are well-defined. The locus of control of those games is with the designer. The players search for best practice within the well-defined game space. They are not allowed to step out that box. Implicit in rule-based games is the assumption that value conflicts are not relevant. The major goal of rule-based games is sharing knowledge that is distributed among the various actors. The main objective is addressing the question: This is the problem. How will you solve it? Free play at the beginning of a game session offers a description (a scenario) of the issue. The actors are asked: How will you deal with it?

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Table 6.

Illustration of Zones of Practice in Connection With Sorts of Games.

Professional competences
	Zones of practice
Conditions⇓	Determinate	Partially determinate	Indeterminate	Conditions⇓
OrdinaryCertainHarmony	Applied science Solutions in search for problems	Type-I games:Rule-based gaming (“flight simulators”) Manageable knowledge problems	Type-II games:Free play (free-form gaming) Wicked (tricky) problems	UniqueUncertainConflicted

In the context of social problem solving, and design-in-the-large, it is worthwhile to distinguish two types of games that address those different zones of practice. They relate to the following typology of policy problems, see Table 7.

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Table 7.

A Typology of Type-I and Type-II Games (with permission of the publisher: Klabbers, 2014 ).

	Knowledge Values	Certainty about knowledge to be, or to become available	Uncertainty about that knowledge
Type-IGames	Consensus(Competitive goals)	Manageable knowledge problems	(In-) tractable knowledge problems
Type-IIGames	Dissension(Conflicting goals)	Tricky ethical problems	Wicked governance problems

Explanation Table 7:

For the following reasons, wicked policy problems resist conventional analysis and problem-solving techniques (Kalff, 1989).

Type-I games are well suited to deal with manageable knowledge problems. Because of their rigid structure – for reasons indicated above – they miss the flexibility to deal with tricky ethical and wicked governance problems. For those issues type-II games are better suited. They not only are flexible to deal with the current situation, moreover they are adaptable to shifting circumstances, which can occur during gameplay.

Type-I games deal with issues that concern competitive interests, in sharing the distributed information and knowledge among the social actors (stakeholders) involved, who agree on the underlying values. Type-II games, in addition, deal with value conflicts among the social actors involved.

Social problem solving, viewed this way, is founded on the willingness of the actors involved, to engage in a constructive dialogue, aiming at shared citizenship and respecting human dignity, which are the so-called meta-rules of the game. Citizenship refers to a sense of responsibility by all actors involved towards the community and the wider socio-economic and ecological environment in which they operate.

Design Science Research

The starting point of game science is the design of games: artefacts. Once they are designed game studies can either focus on the analytical, or the design science approach sketched above. In case an existing game is chosen for doing research, it is the first task of the professional to check whether the specifications of design are consistent with the purpose of that study. In the analytical science tradition games are used to theorize, to justify (validate), and predict.

Design science engages in a continuous cycle of development and research through building artefacts, enacting them, assessing them in their context of use, and - while entering the next design cycle - continue redesigning them. In professional gaming, design-in-the-small produces interactive learning environments, the results of which are used as interventions in the design-in-the-large: enhancing the process of social problem solving. Those interventions embody specific claims about the designed artefacts and practice. Research on interventions should contribute to underpinning those claims to advance the design methodology, and to improve processes of change and renewal.

Game science research should start from the position of design-in-the-large, which sets the conditions for design-in-the-small. Design research should start with studying the social organization of the referent system, in connection with its resources, the media of representation included, see Table 2. It should lead to the design brief and the specifications of design of the intended game (Klabbers, 2009). Game design research should address the following six questions (Blasi & Alfonso, 2006):

In relation to the attribution of causes and effects in the evaluation, evaluators should focus on variables, events, processes, and activity structures.