Complexity Thinking in PE: Game-Centred Approaches, Games as Complex Adaptive Systems, and Ecological Values
Saved in:
| Title: | Complexity Thinking in PE: Game-Centred Approaches, Games as Complex Adaptive Systems, and Ecological Values |
|---|---|
| Language: | English |
| Authors: | Storey, Brian, Butler, Joy |
| Source: | Physical Education and Sport Pedagogy. 2013 18(2):133-149. |
| Availability: | Routledge. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals |
| Peer Reviewed: | Y |
| Page Count: | 17 |
| Publication Date: | 2013 |
| Document Type: | Journal Articles Reports - Evaluative Information Analyses |
| Descriptors: | Physical Education, Games, Teaching Methods, Motor Development, Feedback (Response), Learning Processes, Physical Education Teachers, Learning Experience, Learner Engagement, Systems Approach, Cooperation, Self Management |
| DOI: | 10.1080/17408989.2011.649721 |
| ISSN: | 1740-8989 |
| Abstract: | Background: This article draws on the literature relating to game-centred approaches (GCAs), such as Teaching Games for Understanding, and dynamical systems views of motor learning to demonstrate a convergence of ideas around games as complex adaptive learning systems. This convergence is organized under the title "complexity thinking" and gives rise to a comprehensive model of game-based learning that addresses theoretical and practitioner considerations relevant to researchers and teachers. Complexity thinking is also partnered with an ecological integration value orientation to reinforce the dominant purposes of game-based learning in physical education. Key concepts: The study of game-based learning from a complexity thinking perspective relies on the foundational alignment of game characteristics with those of complex learning systems. Both complex learning systems and games are (a) comprised of co-dependent agents, (b) self-organizing, (c) open to disturbance, (d) sites of co-emergent learning, (e) open to varying experiences or interpretations of time, and (f) able to evolve their structures in response to feedback. Considering games as learning systems opens the door to consideration of the system being as sustainable and adaptable as it can. Sustainability, adaptation potential, and engagement levels emerge from the "game as learning system" discussion in order to provide insight into the functioning of the game. High levels of engagement and sustainability are the presented goals for teachers working from a complexity thinking perspective. A number of key concepts from systems literature, such as attractors, affordances, attunement, and disturbances, are discussed as identifiable and manipulatable dimensions of game-based learning. Implications for the PE profession: Physical educators are well positioned to notice learning as it emerges and to construct environments that focus learning without forcing learning. Complexity thinking concepts such as flow, coupling, engagement, attractors, affordances, attunement, and disturbance, in combination with the pedagogical principles advocated by GCAs, provide a robust set of analytical and teaching tools. It is to be hoped that a deepening of understanding of how game forms and game play lead to learning during games will improve the quality of learning experiences in games and foster increasing and prolonged engagement by students. |
| Abstractor: | As Provided |
| Number of References: | 35 |
| Entry Date: | 2014 |
| Accession Number: | EJ1025976 |
| Database: | ERIC |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Url: https://content.ebscohost.com/cds/retrieve?content=AQICAHj0k_4E0hTGH8RJwT4gCJyBsGNe_WN95AvKlDbXJGqwxwFYjfz3oZ6qnqNYEnDHNITMAAAA4TCB3gYJKoZIhvcNAQcGoIHQMIHNAgEAMIHHBgkqhkiG9w0BBwEwHgYJYIZIAWUDBAEuMBEEDKDrSvvIomwS9f0legIBEICBma6n935LxFyZoxi_8mg5nY4zAqbeLJUI35puo2kx_rgDc7AwRSZFCmCNL_G8EfwyVfZUXFzet90EsyvVukd5BW5tmDiBmWvCmcRzPHPBwodgottKTo5n70ZjAYy0o6UCwfSxEV7OImGx8osDi8Ycwo0d7rYSsPn_KomPBcMVVC8xXnDbYnKLPTKXCRLiP2p6MIQk09kCy2lwaw== Text: Availability: 1 Value: <anid>AN0087052752;z3x01apr.13;2019Mar20.12:21;v2.2.500</anid> <title id="AN0087052752-1">Complexity thinking in PE: game-centred approaches, games as complex adaptive systems, and ecological values. </title> <p>Background: This article draws on the literature relating to game-centred approaches (GCAs), such as Teaching Games for Understanding, and dynamical systems views of motor learning to demonstrate a convergence of ideas around games as complex adaptive learning systems. This convergence is organized under the title 'complexity thinking' and gives rise to a comprehensive model of game-based learning that addresses theoretical and practitioner considerations relevant to researchers and teachers. Complexity thinking is also partnered with an ecological integration value orientation to reinforce the dominant purposes of game-based learning in physical education. Key concepts: The study of game-based learning from a complexity thinking perspective relies on the foundational alignment of game characteristics with those of complex learning systems. Both complex learning systems and games are (a) comprised of co-dependent agents, (b) self-organizing, (c) open to disturbance, (d) sites of co-emergent learning, (e) open to varying experiences or interpretations of time, and (f) able to evolve their structures in response to feedback. Considering games as learning systems opens the door to consideration of the system being as sustainable and adaptable as it can. Sustainability, adaptation potential, and engagement levels emerge from the 'game as learning system' discussion in order to provide insight into the functioning of the game. High levels of engagement and sustainability are the presented goals for teachers working from a complexity thinking perspective. A number of key concepts from systems literature, such as attractors, affordances, attunement, and disturbances, are discussed as identifiable and manipulatable dimensions of game-based learning. Implications for the PE profession: Physical educators are well positioned to notice learning as it emerges and to construct environments that focus learning without forcing learning. Complexity thinking concepts such as flow, coupling, engagement, attractors, affordances, attunement, and disturbance, in combination with the pedagogical principles advocated by GCAs, provide a robust set of analytical and teaching tools. It is to be hoped that a deepening of understanding of how game forms and game play lead to learning during games will improve the quality of learning experiences in games and foster increasing and prolonged engagement by students.</p> <p>Keywords: physical education; complexity thinking; complex learning systems; games; sport; flow; constraints; teaching games for understanding (TGfU); game-centred approach (GCA); value orientations</p> <hd id="AN0087052752-2">Introduction</hd> <p>Physical education (PE) teachers are held responsible for supporting the motor-skill development of children and youth while simultaneously fostering the joy of movement and lifelong personal and social responsibility. This 'prepare-it-forward' role of the PE teachers has become a constant motivation for teachers and researchers interested in comprehensive models for understanding game-based learning. Consistent with this vein of work, this conceptual article explores the convergence of language and theories occurring between physical educators using game-centred approaches (GCAs) and movement researchers working from dynamical systems views of contextualized learning. Complexity thinking, based on an understanding of games as complex adaptive systems, is presented as a centre for this convergence. From this centre, this article describes how complexity thinking language can be used to understand the nature of learning during physical games and how complexity thinking may inform the desired purposes and outcomes of games in PE settings.</p> <p>In attempts to explain and study how movement is internally organized and learned in relation to one's environment, researchers working with disciplinary foci such as motor learning and biomechanics, as well as researchers seeking applied sport performance and skill acquisition ends, are increasingly employing the language and terminologies of complexity thinking theories, such as dynamical systems theory (see Arzamarski et al. [<reflink idref="bib1" id="ref1">1</reflink>]; Bourbousson, Sève, and McGarry [<reflink idref="bib2" id="ref2">2</reflink>]; Chow et al. [<reflink idref="bib6" id="ref3">6</reflink>]; Davids and Araujo [<reflink idref="bib8" id="ref4">8</reflink>]; McGarry et al. [<reflink idref="bib29" id="ref5">29</reflink>]; Renshaw et al. [<reflink idref="bib33" id="ref6">33</reflink>]; Wagman et al. [<reflink idref="bib34" id="ref7">34</reflink>]). The desired end of much of this research is to aid teachers, coaches, and researchers in their efforts to help students learn more effectively and efficiently.</p> <p>Concurrently, research on curriculum and pedagogy relating to game-based learning in school and coaching settings is increasingly investigating the efficacy and nuances of GCAs. Harvey and van der Mars ([<reflink idref="bib19" id="ref8">19</reflink>]) remind us that the many variations of GCAs, such as Game Sense (den Duyn [<reflink idref="bib14" id="ref9">14</reflink>]), the Tactical Games Model (Mitchell, Oslin, and Griffin [<reflink idref="bib31" id="ref10">31</reflink>]), Play Practice (Launder [<reflink idref="bib24" id="ref11">24</reflink>]), and the Tactical Decision Learning Model (Gréhaigne, Wallian, and Godbout [<reflink idref="bib18" id="ref12">18</reflink>]), all followed the Teaching Games for Understanding (TGfU) model (Bunker and Thorpe [<reflink idref="bib3" id="ref13">3</reflink>]). Furthermore, all GCAs share the goal of keeping the 'delights of human movement' (Kretchmar [<reflink idref="bib23" id="ref14">23</reflink>]) at the centre of game-based learning so that students ultimately want to play again (Waring and Almond [<reflink idref="bib35" id="ref15">35</reflink>]). In the original TGfU model, the delight of human movement, although not specifically named as such, was an underlying theme connecting game appreciation and the model's cyclical design resulting in game play at the beginning and end of the learning cycle.</p> <p>The reconciliation of GCA literature and complex systems literature is underway. Light ([<reflink idref="bib25" id="ref16">25</reflink>], [<reflink idref="bib26" id="ref17">26</reflink>]) contributed an important piece of conceptual alignment between TGfU and complex learning systems theories by demonstrating the consistency of both frameworks with underlying social constructivist learning theories and an epistemological position based on internal constructions of reality and knowledge. Laboratory-based and applied research supporting the alignment of GCAs and complex learning systems theory has also been driven by developments in motor-learning studies. Motor-learning research based on dynamical systems theory is contributing to an increasingly nuanced view of how specific teacher actions in the form of creating or removing constraints from individuals, tasks, and the surrounding environment during games foster the emergence of situationally relevant and efficacious movement (see Chow et al. [<reflink idref="bib6" id="ref18">6</reflink>]; Renshaw et al. [<reflink idref="bib33" id="ref19">33</reflink>]). Dynamical systems theory, the underlying complexity theory from which the constraint-led approach has emerged, works from a position of organism/environment symmetry (Davids and Araujo [<reflink idref="bib8" id="ref20">8</reflink>]). Organism/environment symmetry forces recognition that player development, movement choices, and learning cannot be considered in isolation from game characteristics and other player abilities. To bring this and other dynamical insights into the realm of teacher practices, Renshaw et al. ([<reflink idref="bib33" id="ref21">33</reflink>]) have proposed a 'constraint-led pedagogy' wherein they advocate for a balanced understanding of learner development in relation to task, performer, and environment constraints. Interestingly, GCAs, which were born from a tradition of reflective practice, had already intuited the role of the environment and constraints in game manipulation and learner development. Whether manipulating rules, scaling equipment, adjusting the number of players, or resizing boundaries, all GCAs deploy some form of taxonomy for organizing aspects of games that can be changed by teachers or students to prioritize the learning of certain movement patterns and decision-making over others.</p> <p>The new dimension added to GCAs by motor-learning research based on dynamical systems theory is a deeper understanding of the characteristics of the environment/learner and task/learner interactions that surround player development. Examples of the added depth emerging from dynamical systems literature include more detailed explanations and study of complex system phenomena, such as degeneracy (Davids and Araujo [<reflink idref="bib8" id="ref22">8</reflink>]; Liu, Mayer-Kress, and Newell [<reflink idref="bib27" id="ref23">27</reflink>]), coupling (Bourbousson, Sève, and McGarry [<reflink idref="bib2" id="ref24">2</reflink>]), self-organization and phase shifts (McGarry et al. [<reflink idref="bib29" id="ref25">29</reflink>]), perturbation and disturbance, attunement, attention, and perception (Arzamarski et al. [<reflink idref="bib1" id="ref26">1</reflink>]; Wagman et al. [<reflink idref="bib34" id="ref27">34</reflink>]). These concepts are developed further during the discussion of the 'Complexity thinking model of game-based learning' presented later in this article.</p> <p>In addition to the language of dynamical systems theory being used in motor-learning literature, language associated with what can generally be described as 'complexity thinking' has emerged across subject areas. This literature has its roots in a biological and evolutionary world view (Doll [<reflink idref="bib15" id="ref28">15</reflink>]) and is exemplified by work such as Mennin's ([<reflink idref="bib30" id="ref29">30</reflink>]), which articulated the characteristics of small problem-based learning groups with the characteristics of complex adaptive systems. The shift to complexity thinking across subject areas represents a paradigm shift in organizing the knowledge of learning (Mennin [<reflink idref="bib30" id="ref30">30</reflink>],  303). At the heart of this language shift is the acceptance of the fact that learning is not predictable, is not linear, nor is it best explained through simple rational models.</p> <p>For example, motor-learning studies looking at the reproducibility of motor performance while limiting environment and task variation have shown that degeneracy is a valid concept for understanding adaptation throughout the biological world, including the study of human movement. Davids and Araujo ([<reflink idref="bib8" id="ref31">8</reflink>]) highlight Pinder, Renshaw, and Davids' ([<reflink idref="bib32" id="ref32">32</reflink>]) study of cricket batting as an example of this phenomenon. Liu, Mayer-Kress, and Newell's ([<reflink idref="bib27" id="ref33">27</reflink>]) study of rotating a roller-ball (gyro-ball) in one hand is another study that explicitly uses the concept to describe motor coordination variability leading to similar outcomes. 'Degeneracy is the ability of elements that are structurally different to perform the same function or yield the same output' (Edelman and Gally [<reflink idref="bib16" id="ref34">16</reflink>], 13764). For this discussion of focused student learning and games teaching in PE, Liu et al.'s ([<reflink idref="bib27" id="ref35">27</reflink>]) description of degeneracy as the 'many-to-one mapping from movement coordination space to performance space' (<reflink idref="bib392" id="ref36">392</reflink>) provides a succinct explanation. Each time a subject in their study successfully rotated the roller-ball, the neurological and muscular–skeletal patterns noted were slightly different and yet, from a performance measurement point of view, subjects produced trial after trial of similar performance outcomes. To describe these and other observations in motor learning, closed models and metaphors for understanding learning are not satisfactory. For example, in the realm of human movement studies, information processing as a model for describing movement choice as a rationalized process has been widely challenged (Davids and Araujo [<reflink idref="bib8" id="ref37">8</reflink>]):</p> <p>A major problem with this view of decision making is that rationality only works in closed systems (such as a computational system), where specific outcomes always derive if a rational reasoning process is followed. (<reflink idref="bib635" id="ref38">635</reflink>)</p> <p>A key concept in complexity thinking is that of open systems, which lie in contrast to the closed and predictable systems described above. In the case of games, the play between players cannot be characterized as closed or simple because there is a constant re-organization of player relationships occurring (Bourbousson, Sève, and McGarry [<reflink idref="bib2" id="ref39">2</reflink>]). Because games are open systems, they can never be played with strictly reproducible outcomes. The events and adaptations that occur in complex learning system, such as games, are probable but cannot be predetermined through a process of design. The variance in learning during a game is due to the fact that 'members of the same class of phenomenon have the capacity to respond differently to the same sorts of influences ... ' furthermore, '... complex systems embody their own histories' (Davis [<reflink idref="bib9" id="ref40">9</reflink>],  94). In the case of games, players are capable of learning during play and, either spontaneously or in a delayed manner, of integrating that learning into subsequent play; therefore, no two games can ever be identical. It stands to reason that if no two games can be alike, then learning within games is also variable. Complexity thinking embraces this characterization of games as open systems and employs pattern analysis and relational analysis (learner to learner, learner to constraints, and learner to disturbance) in an attempt to better understand what is occurring for learners. When patterns become identifiable, a pathway for creating a more productive learning environment also emerges. For example, a skilled observer of children's games will quickly recognize when poorly scaled equipment is keeping players from successful outcomes. Once noticed, either the rules or the equipment is changed to restore a productive pattern of play.</p> <p>For the remainder of this article, we adopt the term 'complexity thinking' as the broad umbrella under which dynamical systems theory, GCAs, and other systems theories converge. To demonstrate that this convergence is grounded in both theory and practice, we first identify the characteristics of games that are consistent with the characteristics of complex adaptive learning systems. Following the articulation of games as complex adaptive systems, we present a game-based learning model that integrates key features of GCAs and complexity thinking in an effort to provide a comprehensive view of game-based learning systems. In an effort to reconsider the purposes of game-based learning in PE, we conclude this article with the conscious alignment of complexity thinking and an ecological integration value orientation (Jewett, Bain, and Ennis [<reflink idref="bib22" id="ref41">22</reflink>]). The purposes we propose rely on an appreciation of games as open and complex adaptive systems, the teacher as an active agent of the system, and the emergent understanding of game functioning assessed along the lines of sustainability, engagement levels, and adaptation potential of a system.</p> <hd id="AN0087052752-3">Complexity thinking: seeing games as complex adaptive systems</hd> <p>Six criteria are now presented to assess whether a game can be considered a complex adaptive system. Each criterion is presented in the form of a question: (a) Is the game comprised of co-dependent agents? (b) Does the game allow for self-organization between players? (c) Is the game designed for equilibrium and open to disturbance? (d) Does the game represent a site of nested and co-emergent learning? (e) Do the players have varying experiences or interpretations of time during play? (f) Can the game structure evolve (Davis and Sumara [<reflink idref="bib10" id="ref42">10</reflink>], [<reflink idref="bib11" id="ref43">11</reflink>], [<reflink idref="bib12" id="ref44">12</reflink>], [<reflink idref="bib13" id="ref45">13</reflink>]; Doll [<reflink idref="bib15" id="ref46">15</reflink>]; Mennin [<reflink idref="bib30" id="ref47">30</reflink>])?</p> <hd id="AN0087052752-4">Is the game comprised of co-dependent agents?</hd> <p>Co-dependence as a characteristic of complex systems refers to the fact that the system is comprised of organisms that are inter-dependent. Without inter-dependence, there is no need of a systems understanding of their interactions. In education, we tend not to refer to our students as 'organisms,' but we do describe them as agents. The 'agents' of games are primarily their players, but may also include teachers, coaches, referees, and in some cases parents. Each individual player is recognized as a complex adaptive organism onto himself or herself. Once players begin to read, react, and respond (Hopper [<reflink idref="bib20" id="ref48">20</reflink>]) to their teammates and opponents, they are acting as co-dependent parts of a complex learning system. In the simplest game with only two players, each player is co-dependent on his or her opponent for the system to operate. When one quits or is injured, the system and all the associated learning (adaptation) potential collapse. As the example demonstrates, co-dependence is not restricted to teammates. Players are also coupled to opponents. Coupling refers to pairings of agents within a system. Recent research in coupling and co-dependence has been undertaken in basketball by Bourbousson, Sève, and McGarry  ([<reflink idref="bib2" id="ref49">2</reflink>]) and in football by Gréhaigne, Wallian, and Godbout ([<reflink idref="bib18" id="ref50">18</reflink>]). Systems comprised of co-dependents do not respond in predictable ways due to the fact that changes in one part of the system lead to responses in another. Learners' awareness of their co-dependence on others, versus their domination of others, is central to the adoption of an ecological integration value orientation that will be discussed later in this article. Helping students gain awareness of their co-dependence on opponents leads to a teaching focus that requires learning how to adjust, adapt, invent, and play games that maximize opportunities for all.</p> <hd id="AN0087052752-5">Does the game allow for self-organization between players?</hd> <p>Self-organization refers to the constant inter-player re-organization of play that occurs during the game. Each time an individual changes, the system must re-organize itself around the emergent learning at each level of consideration in the system. Self-organization presents a challenge for games teachers wishing to maintain control of students' movement or to be overly prescriptive about successful movement patterns. Once a game is started, players are constantly adapting to new situations. Player re-organization is most evident during major phase shifts (or system evolution) in a game, such as the shift between offence and defence when ball possession changes; however, self-organization is constant and ongoing between all players in a game. To visualize self-organization, consider a football game viewed from above and imagine the players moving as a team in relation to the ball position and possession. In nature, the same phenomenon can be witnessed in the complex systems represented by flocks of birds and schools of fish in response to attractor stimuli such as predators or prey. Flocks of birds hunting insects, schools of fish avoiding a predator, and two teams trying to gain possession of a ball and score goals are all subject to the same phenomenon of self-organization within the system. There is a constant reading and response dynamic between each agent and his or her neighbours in the system. A critical step in adopting complexity thinking is recognition that self-organization occurs all the time between players without the direct involvement of a teacher. That is not to say that teachers do not facilitate student learning by way of co-manipulating the constraints present in a game or by providing direct and indirect feedback to the students on their existing and potential movements. This shift from a control orientation to recognition of learning as a biological adaptive process outside the teachers' direct control but within their influence represents a fundamental shift in emphasis from teaching to learning (Davis and Sumara [<reflink idref="bib12" id="ref51">12</reflink>]; Doll [<reflink idref="bib15" id="ref52">15</reflink>]; Mennin [<reflink idref="bib30" id="ref53">30</reflink>]).</p> <p>The examples given above describe system-level self-organization, which can be described at the level of agent–agent and agent–constraint interactions. For conceptual clarity, it is important to note that self-organization is also the term used within dynamical systems theory for studying and explaining situated human movement responses. By adopting a fractal view and looking at individual movements within a game, self-organization can also be used to explain how physiological sub-systems (skeletal, nervous, cardio-vascular, etc.) mobilize to create movement in response to events that occur during game play. Degeneracy (Davids and Araujo [<reflink idref="bib8" id="ref54">8</reflink>]; Edelman and Gally [<reflink idref="bib16" id="ref55">16</reflink>]) describes how from a performance measurement point of view, individual movements may look very similar from time to time; however, when assessing how internal sub-systems organize to create each movement, no two movements produced by an individual are identical. Returning from how individuals represent self-organization as a nested concept within the game to the self-organization of players throughout a game, the performance measures of games, such as goals, passes, outs, overs, etc., are similar from instance to instance, however, the organization of players in each manifestation may differ. Games that allow players to self-organize in an effort to create the performance outcomes that define a game are representative of complex adaptive systems both at the game play level of analysis and through the fractal view that looks more closely at individual movement production.</p> <hd id="AN0087052752-6">Is the game designed for equilibrium and open to disturbance?</hd> <p>Equilibrium in many circumstances is considered desirable; however, in complex adaptive systems, learning does not occur when learners are maintaining their status quo (Mennin [<reflink idref="bib30" id="ref56">30</reflink>]). Disturbances are the events that force agents in the system to adapt. They are disruptions to homeostasis in the individual and the flow of game play. In complexity thinking literature, the terms 'disturbance' and 'perturbance' are used to represent the same phenomenon of disruption to the learner or the system. This article uses the term disturbance to represent this phenomenon. Competitive games, by design, exploit the tension between equilibrium and disturbance in order to leverage the excitement and suspense of an unknown outcome. Equilibrium is typically established at the start of a game using equal score and division of players between teams. This initial state of balance sets the stage for the ensuing attempts to break and restore the equilibrium. This characteristic of games can be described as <emph>equilibrium by design</emph> and <emph>disturbance through play</emph>. This characteristic of games creates adaptive possibilities that do not require the teacher to be the dominant agent in a lesson. Opponents collaborate to play the game and thereby end up co-contributing to the adaptation potential of the system. The teacher is not a passive agent in creating the disturbances that foster adaptation. The teacher is active during the design of games (with or without student involvement) and throughout the game play (either directly or through facilitation) by adjusting constraints and fostering attunement through feedback with the aim of increasing adaptation opportunities for students. The roles of feedback, constraints, attunement, disturbance, and attractors are discussed further in the section titled 'Complexity thinking model of game-based learning.'</p> <p>Doll ([<reflink idref="bib15" id="ref57">15</reflink>]) refers to systems that allow for disturbance as 'open systems', while 'closed systems' are those that do not allow for disturbance. Games are in a continual state of disturbance due to the oscillating roles of players that occur during what Gréhaigne, Wallian, and Godbout ([<reflink idref="bib18" id="ref58">18</reflink>]) call the 'momentary configurations of play'. For example, in a 0–0 football game, the team with possession of the ball is working to break the equilibrium, while the defensive team is attempting to protect the equilibrium by regaining possession. As soon as the ball is captured by the defence, the roles switch. The disturbances in the game come from the unpredictable choices made by players with and without the ball.</p> <hd id="AN0087052752-7">Does the game represent a site of co-emergent learning?</hd> <p>Co-dependence leads to co-emergent learning. If you and I are playing together and you learn a new movement that changes the way I need to respond, an opportunity for me to learn is also created. If our play evolves together in this way, our learning is co-emergent. To expose whether co-emergence is part of the potential of a game structure, we can ask 'When one player adapts and learning is expressed through new movement patterns, does the game allow for others to adapt in response?' If the game represents an open system, then the answer will be affirmative, resulting in an inevitable learning spiral that changes the potentialities of all other agents in the system (Mennin [<reflink idref="bib30" id="ref59">30</reflink>]). From a complexity thinking point of view, the important determinant of nested and co-emergent learning is that learning only emerges in relation to others because it is situated within the system (Luce-Kapler, Sumara, and Davis [<reflink idref="bib28" id="ref60">28</reflink>]). As an example, consider children playing football when one teammate is afraid to head the ball. As soon as he overcomes his fear of heading and begins to demonstrate this movement during game play, all the other players (teammates and opposition) have the opportunity to adapt to the new ability on the field. The new skill affords his teammates new opportunities to experiment with chip passes and affords defenders the opportunity to use their heading skills to oppose the player. The new potentiality and pattern of play are a disruption of the existing pattern creating the possibility for co-emergent learning.</p> <hd id="AN0087052752-8">Do the players have varying experiences or interpretations of time during play?</hd> <p>As researchers, we are often tempted by the allure of objectivity and might thus hope that understanding games as complex systems offers this promise. However, the ecological roots of complexity thinking and biological adaptive theories such as dynamical systems theory remind us that the agents of games are, at their core, biological beings. Therefore, adaptation is a fully embodied experience for the player. In this regard, we contend that it is helpful to understand complex adaptive learning systems as functioning in accordance with their own biological clocks, not the Cartesian seconds, minutes, and hours that have layered onto them. The focus here is on student experiences of time, not the fixed time allotments of PE periods or structured game segments such as 'periods' and 'quarters'. As fixed and ordered components of game structure, quarters and periods tell us little about the learning occurring during game play or student experience of games. Luce-Kapler, Sumara, and Davis ([<reflink idref="bib28" id="ref61">28</reflink>]) used the expression 'fractal time' to describe the difference between mechanical time and biological time:</p> <p>Fractal time, then, like fractal geometry is a more complex form. It is commonplace to speak of life forms having their own clocks – a way that the passing of time is measured whether it is a cell, a tree, or an ecosystem in a recursive process that has an identifiable rhythm or pattern. In the mechanical interpretations of time, humans have regularized rhythms so that quantitatively every second, minute, and hour is of the same length, but in doing so, human beings have lost the sense that one moment exists within another. (360–1)</p> <p>Games hold the potential to free us from artificial notions of time and to return us to the rhythms of breath, heartbeat, and body that relate directly to our level of engagement, retreat, exhilaration, and disappointment. The ebb and flow of energy, focus, and effort in a game wax and wane both individually and systemically. 'Flow' is the word used by Csiksanetmihalyi to describe this engagement during games. Flow 'is a state of consciousness where one becomes totally absorbed in what one is doing, to the exclusion of all other thoughts and emotions. ... More than just focus, however, flow is a harmonious experience where mind and body are working together effortlessly, leaving the person feeling that something special has just occurred. So flow is [also] about enjoyment' (Jackson and Csiksanetmihalyi [<reflink idref="bib21" id="ref62">21</reflink>], 5). As embedded facilitators in the complex learning systems of games, we are challenged to recognize when flow occurs in our class from the student perspective and subsequently to learn how to harness, redirect, replenish, and dampen it to generate student learning most effectively. It may take a great deal of research to frame game-based learning in ways that do not minimize the importance and subtleties of fully embodied learning. Ultimately, describing experiences of play, games, and embodied learning using language may be an incongruent act; however, by including the criteria for biological or ecological experiences of time by participants, we hope to draw attention to the fact that the insider's view of games is not measured in the same analytical way as the outsider's view.</p> <hd id="AN0087052752-9">Does the game structure evolve in response to feedback?</hd> <p>Game structure refers to the rules, equipment, and environments, which bound or constrain movement possibilities in games. Player–player feedback and teacher–player feedback are implicit in the fact that games are comprised of co-dependent agents. As well, the suggestion that games are complex adaptive systems posits that the game structure itself is open to feedback in order for the system to evolve. As new movement potential is achieved by players and old constraints give way to new, new game structures are required to permit continued evolution of players and push the game to its next iteration. GCAs are helpful for understanding this process because they predominantly adopt an open-system view of game structures. As players gain new insights into tactical options and their abilities, teachers can use direct, Socratic, or democratic methods to adapt the game structure, thereby extending or expanding the adaptation potential of a game. The presentation of a complexity thinking game-based learning model in the following section relies on an open-system understanding of game structure that sees game structure constraints evolving with player abilities.</p> <hd id="AN0087052752-10">Complexity thinking model of game-based learning</hd> <p>The recognition of games as complex adaptive learning systems raises questions about how best to utilize complexity thinking to inform day-to-day PE practices. In this section, we present a model for understanding learning during games that utilizes the language of GCAs and dynamical systems theory to provide a complexity thinking view of game-based learning (see Figure 1).</p> <p>Graph: Figure 1. Complexity thinking model of game-based learning.</p> <p>The learning depicted in Figure 1 attempts to capture a number of elements present in the complexity of game-based learning, including all the criteria relating to the definition of games as complex adaptive systems. <emph>Equilibrium by design</emph> and <emph>disturbance through play</emph> are represented by the balance of <emph>game structure constraints</emph> controlled by the teacher and students during game design on the top half of the model and <emph>game play constraints</emph> representing distributed and coupled player abilities on the bottom half of the model. The <emph>game structure constraints</emph>, depicted in the top triangle, are those represented by the physical environment, rules, or equipment. In their constraint-led pedagogy approach, Renshaw et al. ([<reflink idref="bib33" id="ref63">33</reflink>]) refer to these as task and environmental constraints. These constraints range from very fixed and predetermined in organized sport to open and changing in educational, inventive, and playground games. The game context, category, and form labels chosen for Figure 1 are from the game manipulation taxonomy developed by Bunker and Thorpe ([<reflink idref="bib3" id="ref64">3</reflink>]) in the original TGfU model.</p> <p>The <emph>game play constraints</emph> depicted in the bottom triangle as a collection of individual learners represent the performer constraints (Renshaw et al. [<reflink idref="bib33" id="ref65">33</reflink>]) and abilities that manifest themselves as a set of inter-related movement opportunities and challenges during any given 'state of play' (Gréhaigne, Wallian, and Godbout [<reflink idref="bib18" id="ref66">18</reflink>]). To exemplify the role of game play constraints in relation to the adaptation potential present in a game, imagine a basketball game wherein no player can shoot from beyond the three-point line. The fact that this ability is not present on the floor means that the defence does not need to tightly guard for a shot when play occurs outside that line. As soon as a player demonstrates this ability, the <emph>co-dependent</emph> and <emph>co-emergent learning</emph> characteristics of games and the games' ability to allow for <emph>self-organization</emph> allow the defensive player <emph>coupled</emph> to the offensive player to adjust her defensive movements in response to the newly expressed player ability. An important characteristic of game play constraints is that they are not fixed due to the possibility of emergent learning being instantaneously spiralled back into the game. Furthermore, game play constraints may emerge and decay (Renshaw et al. [<reflink idref="bib33" id="ref67">33</reflink>]) as performers' abilities emerge and decay. Remembering the example of three-point shooting, it is not hard to imagine this ability coming and going for a player throughout the course of a game due to any number of variables, such as fatigue, concentration levels, and/or opponent actions.</p> <p>The interaction of game structure constraints and game play constraints leads to learning conditions that will prioritize some adaptations over others. In keeping with the complexity thinking learning model for games presented in Figure 1, the terms <emph>attractors</emph>, <emph>affordances</emph>, and <emph>disturbances</emph> are used to represent the internal mechanism of games that favour the emergence of some movement patterns over others. <emph>Attractors</emph> are the components of a game around which play is organized. Open space, the net, and the ball are all attractors during different states of play. McGarry et al. ([<reflink idref="bib29" id="ref68">29</reflink>]), in describing inter- and intra-player couplings, describe how 'the ball may be thought of as an attractor onto which the behaviour of each player and coupling is anchored' (<reflink idref="bib777" id="ref69">777</reflink>). By using GCA techniques to manipulate a game, teachers or students can bring an attractor into stronger or lesser focus. Rewarding players with points for passing five times before shooting is an example of using <emph>game structure constraints</emph> to attune students to open-space considerations. <emph>Attunement</emph> refers to the focusing of attention on specific details or dimensions of a phenomenon (Arzamarski et al. [<reflink idref="bib1" id="ref70">1</reflink>]; Wagman et al. [<reflink idref="bib34" id="ref71">34</reflink>]). Attunement is closely linked to what we perceive and, therefore, has an impact on the attractors of a game. When observing young children play football, for example, their attraction to the ball can be so great that when they finally get it, they would have lost track of what direction they are going. For teachers, learning to perceive the dominant attractors present during game play opens the possibility of manipulating game structure constraints to change players' attunement, thereby strengthening or weakening the selected attractor.</p> <p> <emph>Affordances</emph> are players' opportunities to utilize their movement capacity or develop new capacity within the game structure (Renshaw et al. [<reflink idref="bib33" id="ref72">33</reflink>]). In an over-simplified example, the affordances to develop dribbling skills in football are doubled if you halve the number of players on a field. GCAs frequently advocate the use of small-sided games and use the pedagogical principles of sampling, modification representation, modification exaggeration, and controlling tactical complexity (Werner, Thorpe, and Bunker [<reflink idref="bib36" id="ref73">36</reflink>]; Butler et al. [<reflink idref="bib5" id="ref74">5</reflink>]) to increase specific affordances. Much like the attractors and attunement, affordances and attunement are also closely related. Attunement to cues that precipitate effective movement will increase the likelihood that affordances are taken advantage of by the learner. Understanding how game play constraints and game structure constraints combine to create affordances provides insight into the <emph>adaptation potential</emph> of a game system. Seeking high adaptation potential is discussed as a goal of complexity thinking teachers in the following section.</p> <p>Attractors, affordances, attunement, and disturbance can all be considered on an individual level in order to understand how our internal self-organization contributes to the movement choices we make and how manipulation of the player environment will prioritize some potentialities over others for us. When working with the sum total of player abilities in the form of game play constraints as presented in Figure 1, the teacher is not only focused on the individual, but also concerned with maximizing overall system <emph>adaptation potential</emph>. If an area of skill or attitude can be identified as holding back the evolution of game complexity, then the teacher has identified the game play <emph>constraint of most relevance</emph> (CMR)<emph>.</emph> The CMR can be described as the skill or ability that if most players developed, the system would evolve to its next iteration. Using a typical GCA example, students may be asked to play a 2v1 game of handball before being asked to try the same game with dribbling. If students can perform a give-and-go during the handball version of the game, but cannot do it during the dribbling version, then the CMR related to evolving this particular game to its more complex form is dribbling. Through a process of reduction of complexity, GCAs attempt to find the CMR, overcome it, then gradually re-introduce complexity, and identify a new CMR. Throughout this process, the mode of learning is predominantly game based and the role of the teacher is to remain emergent learning focused.</p> <p>The phenomenon of recognizing CMRs for groups of learners is a core component of practice for expert coaches and GCA advocates. The ability to discern CMRs within an active group of learners provides complexity thinking coaches and teachers with a set of open-ended learning possibilities. Just as one CMR in the game is decaying, another will be emerging. Both the emergence and decay of a CMR may represent shifts in patterns of play, creating an opportunity for the teacher to disturb the system and facilitate its movement to the next iteration (see the upper loop in Figure 1). As part of a reflective process, students can help identify the CMR in a game which is common during the questioning or discussion phase of a TGfU lesson. If students are given the opportunity to reflect and adjust game structures, the system may benefit from the goal-driven motivations of the students. By identifying desired movement, identifying areas to work on, and shaping the game, the students are invested in the game, which may lead to high engagement levels.</p> <p>The following is an extended example of how complexity thinking and GCA techniques can provide an open-ended pathway for assessing students during play and for creating the appropriate balance of game structure and game play constraints in an effort to create a positive developmental spiral for students. Imagine a class of 32 eleven-year-old students learning invasion games with a focus on football. Upon arrival at the field on the first day, the teacher divides the class into four groups of 8, then divides each group into two, and sets them off to play 4v4 football games. The students play the game without special instructions, while the instructor watches to assess their play. After the first five minutes, it is clear that there are two main attractors in the game (<reflink idref="bib1" id="ref75">1</reflink>) the ball, which is being mobbed in all games, and (<reflink idref="bib2" id="ref76">2</reflink>) the net, which receives shots from everywhere and now has at least one if not two goalies on each team. It is also clear that a few players in each game are making off-the-ball movements; however, there are few <emph>affordances</emph> for passing due to the mobbing. The teacher decides to interrupt the game and, by way of a discussion and questioning session, decides to reduce the games to 4v2 to emphasize the role of open space for offensive players. She also decides to change the scoring rules so that each time the offensive team gets three passes, they get a point, and each time the defensive team kicks the ball out of the field of play, they get a point. Both <emph>game structure</emph> changes are attempts to increase players' <emph>attraction</emph> to open space and increase <emph>affordances</emph> to make passes. Furthermore, the net is removed as an attractor in the reformed game. The games are reset to zero to create <emph>equilibrium by design.</emph> The new game continues for five more minutes, and in spite of the changes, the defensive teams continually kick the balls all over the field and students become frustrated. In spite of the game structure creating affordances for passing, the <emph>game play constraints</emph> representing the distributed abilities on the field may limit the success of offensive players. <emph>Equilibrium by design may</emph> not result in the desired balance between game play and game structure constraints. At this point, the teacher might recognize the CMR, strong accurate passing. On the next day, she might start with a game she knows will help students develop strong and accurate passing. After witnessing improvements in passing strength and accuracy (the decay of the CMR), she might retry the 4v2 game to see if the students' <emph>attunement</emph> to passing and their recent practice have rebalanced the game play and game structure constraints. It is likely that the games would be much closer on the second day with a healthy flow of points to both offensive and defensive teams. <emph>Equilibrium by design</emph> makes student learning look a lot like play again!</p> <p>This section describing the complexity thinking game-based learning model presented in Figure 1 focuses on the importance of interpreting game-based learning from an open-system understanding. The model attempts to understand learner development in relation to the context. Furthermore, teachers are best understood as the catalysts of learning in contrast to the cause of learning. An important final consideration for teachers wishing to adopt complexity thinking is to recognize that different GCAs afford practitioners varying degrees of control over game design, reflective processes, and subsequent game redesign. This control exists on a continuum of teacher involvement ranging from teacher-directed game design to problem-based learning approaches that utilize criteria and a challenge to foster student game invention (Butler [<reflink idref="bib4" id="ref77">4</reflink>]; Curtner-Smith [<reflink idref="bib7" id="ref78">7</reflink>]). The complexity thinking game-based learning model can be used to analyse game function for all GCAs with open-system interpretations of game structure.</p> <hd id="AN0087052752-11">Restating the purpose of game-based learning in PE: adaptation and sustainability</hd> <p>The adoption of complexity thinking language to help describe game-based curriculum, pedagogy, and learning for those already working from a GCA perspective may or may not represent a significant paradigm shift. As mentioned previously, Light ([<reflink idref="bib25" id="ref79">25</reflink>], [<reflink idref="bib26" id="ref80">26</reflink>]) articulated the underlying learning theory consistency (social constructivism) between GCAs and complexity thinking. For these individuals, the new knowledge may be what Gerhart and Russell ([<reflink idref="bib17" id="ref81">17</reflink>]) refer to as an analogic act, an expansion of breadth and depth to an existing field of meaning. However, for those working from alternate perspectives, such as a disciplinary mastery value orientation (Jewett et al. [<reflink idref="bib22" id="ref82">22</reflink>]), any consideration of games as complex adaptive systems may represent a metaphoric shift regarding how learning occurs during games. A metaphoric shift stems from a cognitive challenge to existing fields of meaning. The final challenge of this article relates to articulating the purposes of game-based learning that emerge from the adoption of complexity thinking on top of an ecological integration value orientation that values the whole learner embedded in his or her learning community.</p> <p>The purpose of PE game-based learning can be articulated as the creation of adaptation opportunities through positive engagement in an ongoing effort to foster game system sustainability. To give meaning to this definition and relate it back to complexity thinking and GCAs, expanded explanations of engagement, system adaptation potential, and system sustainability are provided below. It is our view that the most successful games are identifiable by their high levels of engagement and the positive nature of interactions during play. Positive engagement results from the presence of appropriate game attractors and from players supporting each other's learning as well as their own. An idealized description of high/positive engagement resulting in a self-sustaining learning system full of adaptation potential is represented by the upper right-hand quadrant of Figure 2.</p> <p>Graph: Figure 2. Game system engagement model.</p> <hd id="AN0087052752-12">Engagement</hd> <p>Between the idea of games as fluid, self-propelled, iterative learning systems and the image of games collapsing under conflict or lack of system constraints lies the continuum of system functioning characterized by the players' level of engagement and the positive or negative dimensions of that engagement (Figure 2). Positive engagement contributes to system sustainability, and high levels of engagement lead to higher levels of adaptation potential throughout the game. As an example, consider how unsupervised playground games at recess and lunch collapse, restart, change players, and exclude and include both discriminately and indiscriminately. These games result in positive growth for some and, at times, the stunting of others. When games fail or 'putter along' due to the lack of engagement, or worse, contain outright conflict, the game can be said to hold limited positive adaptation potential for the players. The lack of potential is due to either high negative engagement in the form of conflict (Figure 2, bottom right quadrant) or the low levels of overall engagement, possibly due to a lack of adaptive challenge in the system for many (Figure 2, bottom left).</p> <p>The key differences between lunch time and recess games and PE-based games are the role of the teacher and the intended purpose of the game. It is our view that the responsibility of public school PE teachers is to facilitate games that aim to achieve high levels of positive engagement. From this perspective, the complexity thinking teacher cannot accept self-exclusion or aggressive behaviours as essentialist elements of game play. The responsibility of the teacher from a complexity thinking view stems from the fact that the teacher recognizes himself or herself as a co-dependent agent in the learning system. This acceptance carries with it the responsibility to act when games are unsustainable or lack the possibility for adaptation to accommodate and include students. The ability to modify the <emph>game structure</emph> and influence <emph>game play constraints</emph> empowers the teacher to continually reflect, reset, rethink, and ultimately retry to establish <emph>equilibrium by design</emph> in games that are not representative of high/positive engagement.</p> <hd id="AN0087052752-13">System sustainability</hd> <p>Sustainability of game-based learning relates specifically to the aim of fostering games wherein the learner, upon completion of the game, has (a) experienced opportunities for growth and (b) retained his or her desire to play again. Within ecology literature, sustainability refers to the deployment or consumption of a system's resources in ways that allows for those resources to be regenerated in sufficient quantities to maintain system potentiality. In the learning system of games, the primary resources are its players. Unless players desire to play again, future engagement opportunities are lost and the adaptation potential of the group as a whole suffers.</p> <p>The nature of a sports contest is competitive and cooperative. In team sports, each player on the same team seeks to coordinate with his or her team members in the pursuit of a common competitive goal. Beyond this, each protagonist – individual or team – cooperates with the other to varying extents at various times. (McGarry et al. [<reflink idref="bib29" id="ref83">29</reflink>],  772)</p> <p>System sustainability is perhaps the easiest link to make between GCAs and complexity thinking. All GCAs have as part of their aim the desire and ability to play again as a core principle of their models. At the game system level, when games are uneven or all participants are not included, the <emph>will to play</emph> of some is sacrificed as the collateral damage of a poorly functioning system. Alternatively, if we are successful in our attempts to create <emph>equilibrium by design</emph>, the 'delight of human movement' (Kretchmar [<reflink idref="bib23" id="ref84">23</reflink>]) becomes a more probable outcome. In contrast to the state of play described by Kretchmar, wherein joy, spontaneous movement, and energy are observable, unsustainable outcomes stem from physiological and/or psychological injury. Although one hopes to never facilitate games with negative outcomes, when they do occur, our attention to the goal of sustainability forces reflection by the teacher on the impact of the system functioning on the individual. If students are losing interest in a game form and/or the system is starting to demonstrate low and/or negative engagement, the pattern and relational analysis (learner to learner, learner to constraints, and learner to disturbance) of our games should provide insight into what is limiting the adaptation potential of the game. What are the attractors in the game? What are the affordances for players? What is the constraint of most relevance and is it in decay or emergent? These and other questions are the analytical tools that come with a complexity thinking view of games. Within complexity thinking, sustainability of the system is not based on chance. Sustainability is proactively achieved by teachers attending to interaction of the games they facilitate and the players in their care.</p> <hd id="AN0087052752-14">System adaptation potential</hd> <p>The third system-level descriptor of interest to the complexity thinking teacher is the potential of the learning system for adaptation. Do the <emph>game structure</emph> and <emph>game play constraints</emph> combine to create the appropriate <emph>affordances</emph>, <emph>disturbances</emph>, and <emph>attunement</emph> to specific <emph>attractors</emph> that result in desirable adaptation (learning) opportunities for students? The adaptation potential of the system is highest when all players are challenged near their current limits, resulting in the potential for new movement patterns and thought to emerge from self-organizing responses to the events of a game. When a game is under-stimulating for some and over-stimulating for others, the adaptation potential of the system is diminished.</p> <p>The top left quadrant of Figure 2 provides a description of games representing positive yet low levels of engagement, meaning intensity or challenge is lacking for the players. This situation may be common in PE games where students play familiar games with friends and the <emph>game structure constraints</emph> are rarely modified to challenge skilled movers or provide affordances to those still developing their skill. Sustainability, or the <emph>will to play</emph> in this regard, is a necessary but insufficient condition for judging the quality of game-based learning. Both adaptation potential and sustainability are required to meet the educational aim of providing growth and development opportunities in accordance with PE teachers' educational mandate.</p> <p>The adaptations that occur during games are often categorized along social, psycho-motor, cognitive, and affective dimensions; however, as complex self-organizing agents in symmetry with their environment (Davids and Araujo [<reflink idref="bib8" id="ref85">8</reflink>]; McGarry et al. [<reflink idref="bib29" id="ref86">29</reflink>]), players do not behave and act discretely in these domains. Players demonstrate situated expressions of their ability during play that draw on all of their physiological sub-systems in different magnitudes in response to different disturbances or perturbations (McGarry et al. [<reflink idref="bib29" id="ref87">29</reflink>]; Chow et al. [<reflink idref="bib6" id="ref88">6</reflink>]). Positive adaptations in this light are those that contribute to the increasing capacity of a person's physiological sub-systems to demonstrate flexibility and self-organization in response to a variety of movement challenges.</p> <p>The adaptation potential of a system is not open ended and unlimited because the system is composed of individuals, and an individual's adaptation potential is bound by structure determinism (Davis and Sumara [<reflink idref="bib12" id="ref89">12</reflink>]). 'The manner of response is determined by the agent's structure, not by the perturbation. That is, a complex agent's response is dependent on, but not determined by, environmental influences' (p. 464). Furthermore, structural determinism impacts both the rate of learning and the limits of learning for each player. Players new to a challenge and working far from their limits may show significant rates of adaptation, while experienced players, due to the law of diminishing returns, may appear to progress more slowly because they are working at, or near, their structurally determined limits. As an example, consider that it may take an elite marathon runner a year of training to shave five minutes off her race time; in comparison, an adult who takes up running may complete a marathon in her first year and within her second year may reduce her inaugural time by more than an hour. The elite runner is training and racing at, or near, her structurally determined limits, while the novice runner starts competing when she is far from hers. Learning is more obvious in the novice runner; however, both are adapting by way of training. In spite of the unpredictable and sometimes unobservable nature of learning, a teacher employing complexity thinking using GCAs gains confidence in his or her ability to provide opportunities for students to adapt by attending to the engagement levels and sustainability of the system.</p> <p>We now turn to a badminton example to demonstrate how adaptation potential and engagement are linked to the use of game structure constraints to create both <emph>equilibrium by design</emph> and specific <emph>affordances</emph>. A shot considered strategically essential in badminton is the deep clear. This high and deep shot allows a player to slow play in an effort to re-establish court position. While designing a game for two players to practise this skill, the teacher may initially manipulate the game structure so that no points can be scored in the front half of the court, thereby eliminating the <emph>attraction</emph> of the 'short shot' to gain a quick point. The <emph>affordances</emph> for deep shots are increased by this simple rule adjustment. If one player is struggling in the initial game, some additional performer-specific constraints may be applied to one of the players to re-establish the <emph>equilibrium by design.</emph> While watching the play unfold, the complexity thinking teacher may be aware of technique; however, she is primarily interested in whether or not each player is performing the deep clear with increasing consistency and accuracy. As long as both players are enjoying the game and the affordances for both players to make deep clear shots are high, the game continues in a state of high/positive engagement. Ideally, if one player needs a rule adjustment to reset the equilibrium, the players will make that adjustment on their own in order to maximize the adaptation potential of their time together. In this example, adaptation potential as a focus for the teacher is an important anecdote to focusing on progressions that expected development on fixed timelines. By creating a system with high/positive engagement with affordances to practise the deep clear, the teacher has co-created the learning environment that allows for the desired skill to emerge and become more consistent through practice while respecting the concept of biological adaptive concept of degeneracy. In contrast, to continue to expect players to progress on a fixed schedule without respect for individual variations in learning represents a closed-system view of learning and is inconsistent with a complexity thinking view of learning.</p> <p>It is with caution that we have utilized the terms 'positive adaptation' and 'desirable forms of play' in the above discussion relating to the purposes of games. Both concepts are normative constructs and teaching choices can either reinforce or challenge the local and broader cultural norms surrounding the games. The adoption of an ecological integration value orientation in support of complexity thinking represents our bias towards PE teachers challenging overly competitive notions of games and sports and creating a game-based learning culture that values competitors as co-dependents and seeks to maximize the adaptation potential of a system by seeking to provide appropriate challenges for all students in the game.</p> <hd id="AN0087052752-15">Conclusion</hd> <p>Complexity thinking in PE literature is an emergent construct, and to foster sustained dialogue and investigation around these concepts, the definition of games as complex adaptive learning systems is seen as an important core to an emerging field of meaning. Game-based learning can be aligned with six core characteristics of complex adaptive learning systems; they both (a) are comprised of co-dependents, (b) allow for self-organization, (c) are designed for equilibrium and open to disturbance, (d) are sites of co-emergent learning, (e) can be described by players using non-Cartesian expressions of time, and (f) have system structures that can evolve. In a complex adaptive learning system, any learning that occurs during games is iteratively spiralled back into play and the game structures are open to feedback in order to shape future learning opportunities. From this stance, games are open learning systems wherein learning trajectories may be probable, but precise learning outcomes and timelines are not always predictable.</p> <p>Following the characterization of games as complex adaptive systems, a comprehensive model for understanding game-based learning from a complexity thinking perspective outlined key components of games learning systems. Within the model, both teacher and player agency are recognized as essential in creating the <emph>equilibrium by design</emph> needed to promote specific <emph>affordances, attractors,</emph> and <emph>disturbances</emph>. These identifiable components of game functioning are important signifiers of the adaptation potential and the actual learning occurring during a game. Teachers who adopt complexity thinking and utilize GCA pedagogical techniques become aware of the open-ended learning opportunities that present themselves in games. Learning opportunities for a group can be focused on a game's CMR that has either emerged through play or been designed into the game to create specific affordances. As the CMRs emerge and decay in games, opportunities for the teacher to catalyze learning also emerge and decay. To take advantage of the learning opportunities present in games, complexity thinking provides analytical tools for recognizing the phases and characteristics of game play. As system characteristics change or new learning emerges, a proactive teacher is constantly assessing if the game structure and game play constraints are creating the right balance leading to the positive and high levels of engagement needed to foster sustainable game-based learning.</p> <ref id="AN0087052752-16"> <title> References </title> <blist> <bibl id="bib1" idref="ref1" type="bt">1</bibl> <bibtext> Arzamarski, R., Isenhower, R., Kay, B., Turvey, M. and Michaels, C.2010. Effects of intention and learning on attention to information in dynamic touch. Attention, Perception &amp; Psychophysics, 72(3): 721–35. (doi:10.3758/APP.72.3.721)</bibtext> </blist> <blist> <bibl id="bib2" idref="ref2" type="bt">2</bibl> <bibtext> Bourbousson, J., Sève, C. and McGarry, T.2010. Space–time coordination dynamics in basketball: Part 1. Intra- and inter-couplings among player dyads. Journal of Sports Sciences, 28(3): 339–47. (doi:10.1080/02640410903503632)</bibtext> </blist> <blist> <bibl id="bib3" idref="ref13" type="bt">3</bibl> <bibtext> Bunker, D. and Thorpe, R.1982. A model for teaching of games in secondary schools. Bulletin of Physical Education, 18(1): 5–8.</bibtext> </blist> <blist> <bibl id="bib4" idref="ref77" type="bt">4</bibl> <bibtext> Butler, J.2006. Curriculum construction of ability: Enhancing learning through teaching games for understanding. Sport, Education and Society, 11(3): 243–58. (doi:10.1080/13573320600813408)</bibtext> </blist> <blist> <bibl id="bib5" idref="ref74" type="bt">5</bibl> <bibtext> Butler, J., Oslin, J., Mitchell, S. and Griffin, L.2008. The way forward for TGfU: Filling the chasm between theory and practice. Physical &amp; Health Education Journal, 74(2): 6–12.</bibtext> </blist> <blist> <bibl id="bib6" idref="ref3" type="bt">6</bibl> <bibtext> Chow, J., Davids, K., Button, C., Shuttleworth, R., Renshaw, I. and Araujo, D.2006. Nonlinear pedagogy: A constraints-led framework for understanding emergence of game play and movement skills. Nonlinear Dynamics, Psychology, and Life Sciences, 10(1): 71–103.</bibtext> </blist> <blist> <bibl id="bib7" idref="ref78" type="bt">7</bibl> <bibtext> Curtner-Smith, M.1996. Teaching for understanding: Using games invention with elementary children. Journal of Physical Education, Recreation and Dance, 67(3): 33–7. (doi:10.1080/07303084.1996.10607218)</bibtext> </blist> <blist> <bibl id="bib8" idref="ref4" type="bt">8</bibl> <bibtext> Davids, K. and Araujo, D.2010. The concept of 'Organizmic Asymmetry' in sport science. Journal of Science and Medicine in Sport, 13(6): 633–40. (doi:10.1016/j.jsams.2010.05.002)</bibtext> </blist> <blist> <bibl id="bib9" idref="ref40" type="bt">9</bibl> <bibtext> Davis, B.2004. Inventions of Teaching, New York, NY: Lawrence Erlbaum Associates.</bibtext> </blist> <blist> <bibtext> Davis, B. and Sumara, D.2002. Constructivist discourses and the field of education: Problems and possibilities. Educational Theory, 52(4): 409–28. (doi:10.1111/j.1741-5446.2002.00409.x)</bibtext> </blist> <blist> <bibtext> Davis, B. and Sumara, D.2003. Why aren't they getting this? Working through the regressive myths of constructivist pedagogy. Teaching Education, 14(2): 124–40.</bibtext> </blist> <blist> <bibtext> Davis, B. and Sumara, D.2005a. Complexity science and educational action research: Toward a pragmatics of transformation. Educational Action Research, 13(3): 453–64. (doi:10.1080/09650790500200291)</bibtext> </blist> <blist> <bibtext> Davis, B. and Sumara, D.2005b. Challenging images of knowing: Complexity science and educational research. International Journal of Qualitative Studies in Education, 18(3): 305–21. (doi:10.1080/09518390500082293)</bibtext> </blist> <blist> <bibtext> Den Duyn, N.1997. Games sense: Developing thinking players, Canberra, , Australia: Australian Sports Commission.</bibtext> </blist> <blist> <bibtext> Doll, William. 1993. A post-modern perspective on curriculum, New York, NY: Teachers College Press.</bibtext> </blist> <blist> <bibtext> Edelman, G. and Gally, J.2001. Degeneracy and complexity in biological systems. Proceedings of the National Academy of Sciences, USA, 98(24): 13763–8. (doi:10.1073/pnas.231499798)</bibtext> </blist> <blist> <bibtext> Gerhart, M. and Russell, M.2004. Metaphor and thinking in science and religion. Zygon, 39(1): 13–8. (doi:10.1111/j.1467-9744.2004.00556.x)</bibtext> </blist> <blist> <bibtext> Gréhaigne, J.F., Wallian, N. and Godbout, P.2005. Tactical-decision learning model and students' practices. Physical Education &amp; Sport Pedagogy, 10(3): 255–69. (doi:10.1080/17408980500340869)</bibtext> </blist> <blist> <bibtext> Harvey, S. and van der Mars, H.2010. Teaching games using "Play Practice" part 1: Designing the right games. Journal of Physical Education, Recreation and Dance, 81(4): 26–33. 54 (doi:10.1080/07303084.2010.10598461)</bibtext> </blist> <blist> <bibtext> Hopper, T.2003. Four Rs for tactical awareness: Applying game performance assessment in net/wall games. Teaching Elementary Physical Edudation, 14(2): 16–21.</bibtext> </blist> <blist> <bibtext> Jackson, S. and Csiksanetmihalyi, M.1999. Flow in sports: The keys to optimal experiences and performances, Champaign, IL: Human Kinetics Inc.</bibtext> </blist> <blist> <bibtext> Jewett, A.E., Bain, L.L. and Ennis, C.D.1995. The curriculum process in physical education, Dubuque, IA: Brown and Benchmark.</bibtext> </blist> <blist> <bibtext> Kretchmar, S.2005. "Teaching games for understanding and the delights of human activity". In Teaching games for understanding: Theory, research, and practice, Edited by: Griffin, L. and Butler, J.199–212. Windsor: Human Kinetics.</bibtext> </blist> <blist> <bibtext> Launder, A.G.2001. Play practice: The games approach to teaching and coaching sports, Champaign, IL: Human Kinetics.</bibtext> </blist> <blist> <bibtext> Light, R.2008. Complex learning theory – It's epistemology and its assumptions about learning: Implications for physical education. Journal of Teaching in Physical Education, 27(1): 21–37.</bibtext> </blist> <blist> <bibtext> Light, R.2009. "Understanding and enhancing learning in TGfU through complex learning theory". In TGfU ... simply good pedagogy: Understanding a complex challenge, Edited by: Hopper, T., Butler, J. and Storey, B.Ottawa, ON: Physical and Health Education Canada.</bibtext> </blist> <blist> <bibtext> Liu, Y., Mayer-Kress, G. and Newell, K.2006. Qualitative and quantitative change in the dynamics of motor learning. Journal of Experimental Psychology: Human Perception and Performance, 32(2): 380–93. (doi:10.1037/0096-1523.32.2.380)</bibtext> </blist> <blist> <bibtext> Luce-Kapler, R., Sumara, D. and Davis, B.2002. Rhythms of knowing: Toward an ecological theory of learning in action research. Educational Action Research, 10(3): 353–72. (doi:10.1080/09650790200200191)</bibtext> </blist> <blist> <bibtext> McGarry, T., Anderson, D., Wallace, S., Hughes, M. and Franks, I.2001. Sport competition as a dynamical self-organizing system. Journal of Sports Sciences, 20(10): 771–81. (doi:10.1080/026404102320675620)</bibtext> </blist> <blist> <bibtext> Mennin, S.2007. Small-group problem-based learning as a complex adaptive system. Teaching and Teacher Education, 23(3): 303–13. (doi:10.1016/j.tate.2006.12.016)</bibtext> </blist> <blist> <bibtext> Mitchell, S., Oslin, J. and Griffin, L.2006. Teaching sport concepts and skills: A tactical games approach, 2, Champaign, IL: Human Kinetics.</bibtext> </blist> <blist> <bibtext> Pinder, R., Renshaw, I. and Davids, K.2009. Information-movement coupling in developing cricketers under changing ecological practice constraints. Human Movement Science, 28(4): 468–79. (doi:10.1016/j.humov.2009.02.003)</bibtext> </blist> <blist> <bibtext> Renshaw, I., Chow, J., Davids, K. and Hammond, J.2010. A constraints-led perspective to understanding skill acquisition and game play: A basis for integration of motor-learning theory and praxis?. Physical Education &amp; Sport Pedagogy, 1(21): 1–21.</bibtext> </blist> <blist> <bibtext> Wagman, J., Shockley, K., Riley, M. and Turvey, M.2001. Attunement, calibration, and exploration in fast haptic perceptual learning. Journal of Motor Behaviour, 33(4): 323–7. (doi:10.1080/00222890109601917)</bibtext> </blist> <blist> <bibtext> Waring, M. and Almond, L.1995. Game-centered games: A revolutionary alternative for games teaching?. European Physical Education Review, 1(1): 55–66. (doi:10.1177/1356336X9500100106)</bibtext> </blist> <blist> <bibtext> Werner, P., Thorpe, R. and Bunker, D.1996. Teaching games for understanding: Evolution of model. JOPERD, 67(1): 28–33.</bibtext> </blist> </ref> <aug> <p>By Brian Storey and Joy Butler</p> <p>Reported by Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib29" firstref="ref5"></nolink> <nolink nlid="nl2" bibid="bib33" firstref="ref6"></nolink> <nolink nlid="nl3" bibid="bib34" firstref="ref7"></nolink> <nolink nlid="nl4" bibid="bib19" firstref="ref8"></nolink> <nolink nlid="nl5" bibid="bib14" firstref="ref9"></nolink> <nolink nlid="nl6" bibid="bib31" firstref="ref10"></nolink> <nolink nlid="nl7" bibid="bib24" firstref="ref11"></nolink> <nolink nlid="nl8" bibid="bib18" firstref="ref12"></nolink> <nolink nlid="nl9" bibid="bib23" firstref="ref14"></nolink> <nolink nlid="nl10" bibid="bib35" firstref="ref15"></nolink> <nolink nlid="nl11" bibid="bib25" firstref="ref16"></nolink> <nolink nlid="nl12" bibid="bib26" firstref="ref17"></nolink> <nolink nlid="nl13" bibid="bib27" firstref="ref23"></nolink> <nolink nlid="nl14" bibid="bib15" firstref="ref28"></nolink> <nolink nlid="nl15" bibid="bib30" firstref="ref29"></nolink> <nolink nlid="nl16" bibid="bib32" firstref="ref32"></nolink> <nolink nlid="nl17" bibid="bib16" firstref="ref34"></nolink> <nolink nlid="nl18" bibid="bib392" firstref="ref36"></nolink> <nolink nlid="nl19" bibid="bib635" firstref="ref38"></nolink> <nolink nlid="nl20" bibid="bib22" firstref="ref41"></nolink> <nolink nlid="nl21" bibid="bib10" firstref="ref42"></nolink> <nolink nlid="nl22" bibid="bib11" firstref="ref43"></nolink> <nolink nlid="nl23" bibid="bib12" firstref="ref44"></nolink> <nolink nlid="nl24" bibid="bib13" firstref="ref45"></nolink> <nolink nlid="nl25" bibid="bib20" firstref="ref48"></nolink> <nolink nlid="nl26" bibid="bib28" firstref="ref60"></nolink> <nolink nlid="nl27" bibid="bib21" firstref="ref62"></nolink> <nolink nlid="nl28" bibid="bib777" firstref="ref69"></nolink> <nolink nlid="nl29" bibid="bib36" firstref="ref73"></nolink> <nolink nlid="nl30" bibid="bib17" firstref="ref81"></nolink> |
|---|---|
| Header | DbId: eric DbLabel: ERIC An: EJ1025976 AccessLevel: 3 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Complexity Thinking in PE: Game-Centred Approaches, Games as Complex Adaptive Systems, and Ecological Values – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Storey%2C+Brian%22">Storey, Brian</searchLink><br /><searchLink fieldCode="AR" term="%22Butler%2C+Joy%22">Butler, Joy</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Physical+Education+and+Sport+Pedagogy%22"><i>Physical Education and Sport Pedagogy</i></searchLink>. 2013 18(2):133-149. – Name: Avail Label: Availability Group: Avail Data: Routledge. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 17 – Name: DatePubCY Label: Publication Date Group: Date Data: 2013 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Evaluative<br />Information Analyses – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Physical+Education%22">Physical Education</searchLink><br /><searchLink fieldCode="DE" term="%22Games%22">Games</searchLink><br /><searchLink fieldCode="DE" term="%22Teaching+Methods%22">Teaching Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Motor+Development%22">Motor Development</searchLink><br /><searchLink fieldCode="DE" term="%22Feedback+%28Response%29%22">Feedback (Response)</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Processes%22">Learning Processes</searchLink><br /><searchLink fieldCode="DE" term="%22Physical+Education+Teachers%22">Physical Education Teachers</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Experience%22">Learning Experience</searchLink><br /><searchLink fieldCode="DE" term="%22Learner+Engagement%22">Learner Engagement</searchLink><br /><searchLink fieldCode="DE" term="%22Systems+Approach%22">Systems Approach</searchLink><br /><searchLink fieldCode="DE" term="%22Cooperation%22">Cooperation</searchLink><br /><searchLink fieldCode="DE" term="%22Self+Management%22">Self Management</searchLink> – Name: DOI Label: DOI Group: ID Data: 10.1080/17408989.2011.649721 – Name: ISSN Label: ISSN Group: ISSN Data: 1740-8989 – Name: Abstract Label: Abstract Group: Ab Data: Background: This article draws on the literature relating to game-centred approaches (GCAs), such as Teaching Games for Understanding, and dynamical systems views of motor learning to demonstrate a convergence of ideas around games as complex adaptive learning systems. This convergence is organized under the title "complexity thinking" and gives rise to a comprehensive model of game-based learning that addresses theoretical and practitioner considerations relevant to researchers and teachers. Complexity thinking is also partnered with an ecological integration value orientation to reinforce the dominant purposes of game-based learning in physical education. Key concepts: The study of game-based learning from a complexity thinking perspective relies on the foundational alignment of game characteristics with those of complex learning systems. Both complex learning systems and games are (a) comprised of co-dependent agents, (b) self-organizing, (c) open to disturbance, (d) sites of co-emergent learning, (e) open to varying experiences or interpretations of time, and (f) able to evolve their structures in response to feedback. Considering games as learning systems opens the door to consideration of the system being as sustainable and adaptable as it can. Sustainability, adaptation potential, and engagement levels emerge from the "game as learning system" discussion in order to provide insight into the functioning of the game. High levels of engagement and sustainability are the presented goals for teachers working from a complexity thinking perspective. A number of key concepts from systems literature, such as attractors, affordances, attunement, and disturbances, are discussed as identifiable and manipulatable dimensions of game-based learning. Implications for the PE profession: Physical educators are well positioned to notice learning as it emerges and to construct environments that focus learning without forcing learning. Complexity thinking concepts such as flow, coupling, engagement, attractors, affordances, attunement, and disturbance, in combination with the pedagogical principles advocated by GCAs, provide a robust set of analytical and teaching tools. It is to be hoped that a deepening of understanding of how game forms and game play lead to learning during games will improve the quality of learning experiences in games and foster increasing and prolonged engagement by students. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: Ref Label: Number of References Group: RefInfo Data: 35 – Name: DateEntry Label: Entry Date Group: Date Data: 2014 – Name: AN Label: Accession Number Group: ID Data: EJ1025976 |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1025976 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/17408989.2011.649721 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 133 Subjects: – SubjectFull: Physical Education Type: general – SubjectFull: Games Type: general – SubjectFull: Teaching Methods Type: general – SubjectFull: Motor Development Type: general – SubjectFull: Feedback (Response) Type: general – SubjectFull: Learning Processes Type: general – SubjectFull: Physical Education Teachers Type: general – SubjectFull: Learning Experience Type: general – SubjectFull: Learner Engagement Type: general – SubjectFull: Systems Approach Type: general – SubjectFull: Cooperation Type: general – SubjectFull: Self Management Type: general Titles: – TitleFull: Complexity Thinking in PE: Game-Centred Approaches, Games as Complex Adaptive Systems, and Ecological Values Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Storey, Brian – PersonEntity: Name: NameFull: Butler, Joy IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2013 Identifiers: – Type: issn-print Value: 1740-8989 Numbering: – Type: volume Value: 18 – Type: issue Value: 2 Titles: – TitleFull: Physical Education and Sport Pedagogy Type: main |
| ResultId | 1 |
