economists who think like ecologists': reframing systems thinking in games for learning

7/28/2019 'Economists Who Think Like Ecologists': reframing systems thinking in games for learning

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ELearning and Digital Media

Volume 7 Number 1 2010

www.wwwords.co.uk/ELEA

3 http://dx.doi.org/10.2304/elea.2010.7.1.3

Economists Who Think Like Ecologists:

reframing systems thinking in games for learning

BEN DeVANE, SHREE DURGA & KURT SQUIREUniversity of Wisconsin-Madison, USA

ABSTRACT Over the past several years, educators have been exploring the potential of immersiveinteractive simulations, or video games for education, finding that games can support the developmentof disciplinary knowledge, systemic thinking, the production of complex multimodal digital artifacts,and participation in affinity spaces or sites of collective intelligence. Examining verbal interaction datafrom a game-based after-school program, the authors offer evidence that expert players of learningvideo games: (a) think relationally and strategically about elements of the game system; (b) draw ontheir experiences in similar activity domains when approaching systemic problems; (c) consider systemicproperties as they are tied to action; and (d) think and act in markedly social ways while engaged insystems-oriented reasoning. Using discourse analysis, the authors examine the talk and game play oftwo participants to understand how they think about the relationships between elements of the gamesystem. From these exchanges a kind of play emerges which contains the kinds of systemic thinkingthat educators might hope to find in twenty-first-century classrooms. There was evidence fromstudents reasoning that the situated systems thinking in which they engage contains the reasoning andproblem-solving strategies for complex economic, political and geographic systems that twenty-first-century classrooms might value.

Introduction

In 2007 and 2008, world food prices rose dramatically. The price of diet staples like rice and wheatdoubled, causing humanitarian crises in developing nations. Most economists agreed that theconfluence of a general set of factors was probably to blame for the near-catastrophe: droughts ingrain-producing nations caused by climate change, rising oil prices, imbalanced agricultural policiesin developed nations among others.

The nuances of the causes of this crisis can be staggeringly difficult to comprehend. Forinstance, rising oil prices increased costs of global food transportation, the use of agriculturalindustrial machinery and the price of oil-based fertilizers. At the same time, food-producing nationsattempted to decrease oil costs by greatly subsidizing agricultural biofuels, which led farmers to

grow crops for fuel rather than food. In this way government policies interacted with market andecological fluctuations to drastically increase the price of food. Notable contemporary research hascautioned that such incongruence between large-scale economic practices and ecological systemscan easily threaten the existence of human societies (Diamond, 2005). In response to the risks foundin an increasingly interconnected global society, Lester Brown wrote that modern societies mustrethink their understandings of social science, policy making and education: Today, more thanever before, we need leaders who can see the big picture, who understand the relationship betweenthe economy and its environmental support systems ... we need economists who think likeecologists. Unfortunately they are rare (Brown, 2003, p. 23).

If such emergent effects can boggle even trained policy makers, how then can citizens indemocratic societies be expected to understand these complex systems in their political and economic


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lives? Furthermore, how can educators and researchers teach their students to think critically aboutthe complex interaction of these systems elements? Some learning scientists have claimed thatvideo games can be vehicles for a form of design literacy that fosters sophisticated cognitive modelsand dispositions towards systems by gradually exposing players to the underlying structures builtinto them by designers. Hence, they show promise as a possible educational approach to systems(Gee, 2003; 2007; Games, 2008; cf. Kafai, 1995; Brown & Thomas, 2008).

Figure. 1. Causes of the world food crisis.

However, the research literature describing the contours of game-based systems thinking remainssparse. Game-based approaches to systems thinking have most often involved learners conductingvirtual investigations in graphically rich three-dimensional worlds (or real worlds augmented bysimulated data) so that participants understand a local ecosystem (Barab et al, 2007; Ketelhut et al,2007; Squire & Jan, 2007). These approaches, while particularly valuable in that they tie into

existing curricular standards and content areas, usually do not explicitly express systems thinking asa pedagogical goal, nor do they include specific references to systems concepts. This studyexamines verbal interaction data from a game-based after-school program that uses the Civilizationgame series to teach young people about materialist history. We offer evidence that expert playersof learning video games: (a) think relationally and strategically about elements of the game system;(b) draw on their experiences in similar activity domains when approaching systemic problems; and(c) think and act in markedly social ways while engaged in systems-oriented reasoning. We see anunmistakable contrast between this very situated form of systems thinking and previousunderstandings of systems thinking in the research literature.

Background

Learning in Game-Based Environments

Good video games are unique in that players must learn how the game system works in order toachieve success within it. In Civilization, for example, players must understand about therelationship between geographical conditions and food production to provide sustenance to theircities denizens (Squire, 2005). Activity in games can often be characterized by a cycle of activity:perceiving a problem, formulating a prediction about the games model of that problem, engagingin situated activity in an effort to solve the problem, and evaluating the relative success of theaction undertaken (Gee, 2003; Young, 2004; Kafai, 2006). The result of a good game, then, is thatplayers learn to infer the properties of its underlying relational model (or, put otherwise, itsideological world). As educators, we design experiences so that players learn to make inferencesabout those models and negotiate their meanings within real-world social and cultural systems(Squire, 2006).


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Gee (2007) argues that games are powerful tools for helping players develop embodied empathyfor such complex systems. That is, by placing players within a system in which they interact, theyhave the potential for developing students intuitions of how they operate. In the case ofCivilization, this argument was described similarly by Ted Friedman (1999), who suggested that oneof the primary joys ofCivilization playing is learning to think with, and even within the computersystem. While scholarship on games holds that the pleasure of game play is tied to how we think,learn and play in highly leveraged and resourced digital systems, the nuances of how we learn and

think with these game-based systems of meaning have yet to be explored in the literature. Therehave been first-hand phenomenological accounts of ones own game play or studies of howlearning within game-based curricula tie to more traditional academic goals, but there exists littleinterest in understanding how such learning experiences apply toward contemporary geopoliticalissues.[1]

Theoretical Framework: systems thinking

Systems Thinking

Across different fields of social science research systems thinking is a term used to denote anapproach to understanding complex phenomena and problems that considers how elements of anorder relate to each other and the function of the order as a whole (cf. Checkland, 1981; Senge,1990; Banathy, 1991; Reigeluth & Garfinkle, 1994; Forrester, 1997; Squire & Reigeluth, 2000).While scholars from different research traditions have examined how humans think with complexrepresentational systems of meaning, there exists no clear consensus on how scholars shouldapproach the topic of study, nor even the precise nature of systems thinking. While studies havegenerally described how systems thinking works in game-based learning communities (Kafai, 1995;Squire, 2003; Gee, 2005), we seek a less ambiguous description of systems thinking that takes intoaccount prior, related research in the fields of general systems theory, cognitive sciences and thelearning sciences.

General Systems Theory

The phrase systems thinking has been most used by scholars who are schooled in, or affiliate with,

the general systems theory tradition of organizational and sociological research (see Squire &Reigeluth [2000] for a brief history of these ideas in educational reform). These scholars use theterm systems thinking to interchangeably describe: (a) a mode of cognition that that has arisen inresponse to complex environments of modern societies; (b) a way of solving problems and studyingnatural phenomena; and (c) a means of understanding (and managing) the operation of largehuman organizations and institutions (Checkland, 1981; Senge, 1990; Banathy, 1991; Reigeluth &Garfinkle, 1994). It is important to note that this scholarship views these three aspects of systemsthinking as inherently interconnected e.g. more systemic methods of scientific investigation andreal-world problem solving will give rise to more systemic forms of human organization and viceversa.

For the most part, however, this systems thinking scholarship shares a common theoreticalfoundation. Systems thinking starts from noticing the unquestioned Cartesian assumption:

namely, that a component part is the same when separated out as it is when part of a whole(Checkland, 1981, p. 12). In such a view, a systemic approach uses a holistic understanding ofsystems, which emphasizes the relationships between parts of the system relative to the function ofthe system as a whole, to both structure problem solutions in everyday activity and scientificinvestigation. However, this emphasis on holistic understanding exists in uneasy tension alongsidethe fields functionalist roots in hierarchy theory and general systems theory (Ulrich, 1988). Becauseit is rooted in the functionalism of general systems theory (see Boulding, 1956; Simon, 1962), thesystems thinking literature has the odd distinction of emphasizing holistic approaches to problemsolving while prescribing reductionist systems heuristics for problem solving that are uprootedfrom their everyday contexts of use (see Lave, 1988). These problem-solving heuristics are held to

be generalizable in the systems thinking literature they work across and in spite of contexts,activities and knowledge domains (see Checkland, 1981).


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Cognition as Predictive Modeling

Contemporary cognitive science research has drawn incrementally closer to these perspectives onlearning with complex systems, as research argues that humans are always cognitively simulatingthe consequences of action in their social and material worlds (Wolpert & Kawato, 1998; Barsalou,1999; Glenberg & Robertson, 2000). This framework for understanding cognition, alternately calledgrounded cognition and embodied cognition, argues that the mind is constantly making embodied

predictions about the world to better grasp the possibilities for and results of action. Thesepredictions are grounded in a persons experiences in a given activity and their model of therelationship between elements in the world related to their potential actions (Barsalou, 1999).Because good video games present players with clearly structured goals, problems to solve toaccomplish that goal, indications of a solution path and clear feedback on a players solution, theyare learning artifacts that fit relatively well with grounded cognitions view of the simulation-basedmind (Gee, 2007).

Learning about Systems through Play and Design

At the same time research in the learning sciences has independently emphasized the importance ofunderstanding concepts as elements in interconnected webs of meaning related patterns,

processes and elements instead of abstract, self-contained symbolic structures (Papert, 1980;Burton et al, 1984; Brown et al, 1989; New London Group, 1996). From this perspective, conceptsshould be taught and understood according to their relationship to other elements in a givensituation and their function in an activity. In other words, a piece of knowledge is best learned inrelation to other, connected conceptual elements and best understood according to what they cando in a given situation (diSessa, 1988).

When it comes to the question of how best to learn about systems, research in the learningsciences has two distinct, but overlapping, prescriptions for systems-oriented learning practices. Forthe most part, learning sciences research related to systems thinking has, drawing on constructivistperspectives, found that formal design activities help students build more robust understandings ofacademic knowledge domains and practices (Perkins, 1986; Kafai, 1995; Kolodner et al, 1998;Games & Squire, 2008). The core idea here is that by building (often times dynamic)representations of systems, learners come to understand the relationships among sub-components

of systems. A second branch of scholarship focuses on situated experiences within simulatedsystems, hypothesizing that acting in a simulated system (particularly when learners have goalswithin such rule-based systems) helps learners develop meta-understandings of the meaning-making model underlying the system (see Papert, 1980; Schn, 1983; Gee, 2003; Squire, 2005).However, little empirical research exists that details the nature of systems thinking in game-basedlearning environments. Most often such studies, working in the contexts of schools, have focusedmore explicitly on traditional academic standards.

Methodology

We seek in this article to better understand how young gamers think, act and feel in relation togame-based systems of meaning that they inhabit. As such, we adopt the framework of discourse

analysis, which is both a theory and a method for studying how language gets recruited on siteto enact specific social activities and social identities (Gee, 1999, p. 1; see also Fairclough, 1995).Using discourse analysis, we seek to better understand what the language that these game playersuse reveals about how they are thinking relationally about the game system, how they are actingwithin the game space and how they see themselves in relation to the social space surroundingtheir game-based activity (see Steinkuehler, 2006). Because language is an important meansthrough which people coherently structure and systematize their experiences and activities (Lakoff& Johnson, 1980), we examine the talk and game play of two participants in a game of CivilizationIV to understand how they think about the relationships between elements of the game system.We elaborate on some of the key cues that signal how systemic thinking occurs through symbolic(language in game) andgestural (performance in game) usage of language (Levinson, 1983).


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This data was collected through three means: video- and audio-recording of participantsgame play, field notes taken by researchers, and game logs of major events and occurrences.Naturalized transcriptionwas employed for the video-recording in order to capture not just whatwas said, but also, how it was said. The data excerpt in the following section is represented using

Jeffersonian transcript notation revealing sequential features of talk, rise or fall of intonation,abrupt halt or pause, emphasized speech, reduced or increased volume, etc., in order to depictaccurate (or closest approximations of) the perceptions and meaning articulated during the data

collection (Cameron, 2001; Oliver et al, 2005).

Research Background

This article emerges from data collected during a longitudinal four-year design-based researchstudy of a history-based after-school gaming club for young people aged nine through 14. Paststudies of this club have examined how players make the transition from users to designers (Squireet al, 2005) and how individual players develop distinct trajectories of expertise relative to theirknowledge of the game and history (Squire et al, 2008). Throughout the course of our research consisting of ethnographic observation, focus group interviews and task-based assessments weobserved that expert players approach to in-game problems was conceptual and systemic ratherthan procedural (Squire et al, 2005; DeVane & Durga, 2008).

This data features an interaction between two long-time program participants who hadmastered Civilization III (Civ3), and now sought to master Civilization IV (Civ4). One of these Civ3experts, 13-year-old P2, is playing the sequel, Civ4, for the first time. He is assisted by P1, another13-year-old expert Civ 3 player who volunteered to interview him, and by L1, an adult who isserving as a game facilitator for the club. P1, who has a meager two-hours experience playing thegame (which easily takes hundreds of hours to master), is attempting to inhabit the role of an adultresearcher like L1. As such, he is video-recording P2s game play, asking on-the-spot questions totry to ascertain the reasons for P2s in-game actions and trying to act as a mentor to P2. L1, who issupervising and assisting nine other players with their games, intermittently interjects withquestions and advice.

Figure 2. Mechanics of the health system in Civilization IV.


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The Problem Context

P2 is playing a game mod, which is a modification of the game that has somewhat differentmechanics, rules and themes, themed around European conquest and colonization of the

Americas. In this mod, players can lead either a European colonial power or an indigenousAmerican society in the late fifteenth and early sixteenth centuries as they negotiate the economic,military and social issues of the day. P2 has chosen this mod to play because it thematically

resembles his favorite Civ3 mod.This data reproduces the talk and actions of the two young players, and sometimes the adultfacilitator L1, as they try to solve a problem confronting P2. One of P2s in-game cities, Plymouth,England, has become unhealthy. This new municipal health mechanic (a set of game rules thatstructure play) had been introduced in Civ4 and was not present in previous games in the series(like Civ3). In the game, as cities grow in population and industrialize, they become more and moreunhealthy places to live. Players can mitigate these unhealthy factors in cities by buildingimprovements like aqueducts and hospitals, connecting their cities to areas rich in certain foodresources like wildlife and livestock or establishing their cities near bodies of fresh water. As thisis P2s first, and P1s second, encounter with this fairly complex game mechanic again, it had not

been in any previous games that they had played they had very limited problem schema availableto shape a solution.

Figure 3. Unhealthiness in P2s Plymouth.

Results

Problem Solving in Relational Systems

In an effort to characterize the nature of systems thinking with video games, we examine theinclinations and approaches of P1 and P2 as they formulate solutions to problems that confrontthem in their game play. As P1 and P2 try to solve the problem of how to improve the municipalhealth of their city, they explore the connections between the different relational elements of thegame system that are connected to the problem. This problem-solving process is an iterative one,as the two continually encounter a way in which their solution will not work given the state of thegame system, and subsequently create new solution paths. In this interaction, the two playerscreate and test three distinct solution paths: (1) building transport routes to food resource-rich areasnear to their city; (2) using North American colonies in resource-rich areas to supply their resource-poor English cities with food; and (3) constructing city improvements that increase residentshealth.


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Three trends emerge from our analysis of the players problem-solving practices in the gamesystem. First, instead of generating solution paths from general systems thinking formalisms, theplayers solutions to problems confronting them in the game system are assembled on the spotfrom their own past game play experiences (in Civ 3), individual knowledge of history, and availablesocial and material knowledge resources (a history book, in-game tools and a program facilitator).Second, the players exhibit a remarkable ability to leverage new information about both theimportance of individual game elements and the relationships between game elements to

formulate new solutions. Third, the problem-solving process of the two players is highly social innature characterized by collaborative activity, performance of distinct social identities and bids to

be recognized as experts within the gaming community.

Figure 4. The dearth of health resources in England.

Solution 1: relational thinking and experience. The two participants quickly arrived at a solution wherethey would find food resources in the countryside close to the ailing city and build a routeconnecting the two areas, which would provide the city with bonus health points by bringing infresh food. However, when they tried to find a food resource on the well-populated British Isles,they began to realize their proposed solution was problematic. As they explored the areasurrounding the city, they saw that such food resources did not exist anywhere in Englandsterritory. In fact, P1 had to look to other countries to find an instance of such a resource toillustrate to P2 what he was talking about:

P1:Um (.) lets move over here to (.) the Netherlands.who apparently arent doing all that well.Hmm so this is the French.Uhm (.) see like (.)If you have Deeryou can get Hunting-But (.) here look in your bookand see what food sources are around your cities.

Follow-up interviews revealed that their erroneous prediction was grounded in their previousexperiences playingCiv 3 game mods. These scenarios represented Scotland and Ireland as sparselyinhabited resource farms that can supply heavily populated southern England with naturalresources. This, however, was not the case in this Civ 4 game scenario. In fact, there were no food


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resources that would give their city a health bonus in the whole of the overpopulated British Isles(health bonuses disappear as areas become overpopulated or land is deforested).

Instead of trying to verbally instruct P2 how to improve his citys health, P1 found a health-improving resource wildlife represented by a picture of a deer and began to explain how P2might use that resource to improve the citys health. He started to explain that P2 could use theHunting technology (also called a civilization advance) to utilize that resource square. However,he interrupted himself and resumed collaborating with P2 to try to find a more immediate solution

to the problem at hand. This straightforward solution path was grounded in an understanding ofthe games model of the relationship between food supply and health in urban areas.

Figure 5. Section of a fan-created Excel resource chart.

Solution 2: socially and materially situated systems thinking. P1 and P2 looked for bonus food resourcesnear the ailing city which would solve the problem, but were unable to find any. Next, they turnedto external sources of information namely a textbook that one happened to have on hand to

search for health-boosting resources:P1: But (.) here look in your bookand see what food sources are around your cities.P2: Where?Where in the book?P1: See what food sources might be around Spain (indicates P2s land in Normandy)P2: [Mmmmmm.Oh (.) oh] this is a US book.

Because it was a US history textbook, P2s book did not contain information about resources nearP2s cities in England or in Normandy (which P1 calls Spain) that would help them implementsolution path 1. However, use of this artifact did help them generate two new ideas about possiblesolutions: using North American colonies for food, or trading for food on the global market. These

ideas involved more elaborate understandings of the game system to attempt to solve the healthproblem, integrating multiple subsystems (namely, trade routes, diplomacy, and the requisitetechnologies for supporting them):

P2: So (.) it still tells like (.) what resources (.) ( looking through history textbook for resources inNorth America)P1: Well if you have a trade routeyou can tradeP2: Ummmm.

As P2 had not yet explored inland North America in-game, he could not see in-game whatresources were located there and was using the textbook as a sort of cheat for predicting whatsorts of resources it might contain (cf. Squire, 2005). P2 became quiet and pensive for a period of


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time, as he examined his book for food resources near his North American colonies, contemplatinghow to ship those resources back to his city (an involved, multi-step process that requires creatingsettlers, building ships, transporting the settlers, founding a new city, defending the city, buildingharbors, and making sure he had the technologies required for trading over the open ocean, asdetailed below). P1, meanwhile, offered a different solution path, based around the game mechanicof trade routes. Trade routes in the game are sea- or land-based routes between cities that allowcivilizations to trade resources with their neighbors. P2, however, showed little enthusiasm for the

idea and instead continued to look for resources in North America that he could ship back toEngland to increase the health of his cities (note the similarities between this scenario and thoseinvolved in contemporary food shortages):

Off-topic cross talk between P1 and other participants:P2: [to L1]Umm (.)Im trying to find out what resources or [food I can yeah=L1: Food?]L1: Something you might find=you might findthat if you can get a harbor (.) or somethingand trade back=

P1: [Fish! P2! Fish! Fish!L1: You can trade (.) yeah-If you-If you] get a good bunch of stuff kicking in North Americamaybe you can trade back.P2: Mmmk (.)I have [fishL1: Like you have] sheep thereYou have some fishYoull need to get a uh=P2: A worker.L1: Yeah and youll need to get a uh (.)

inside that trade network.Unsure of this nascent solution, P2 asked the program facilitator, L1, for help elaborating thesolution path. Synthesizing the different ideas put forward by P1 and P2, L1 advised that P2 shouldtrade resources internally between his overseas English colonies in North America and domesticcities in Britain.

That the players have little patience with the facilitators explanation indicates that theconcept of mercantile trade between colonies and their mother country was a solution path thatwas not far beyond the competency or understanding of the players. As L1 put forward an outlineof a solution, P1 interrupted and pointed out the presence of a food resource. P2, meanwhile, hadalready begun quietly looking for food resources near his colonies in North America before thefacilitator could specify that he should investigate that area. By the time L1 finished his broadoutline of a solution, P2 had already begun fleshing out the details of the solution path he had

located two food resources and begun building the necessary units (workers). A few minutes later,P2 began constructing a route to the food resource using a worker unit, and researching theAstronomy technology that would enable his ships to carry food across the ocean. This solutionwas notable in that participants used social and material resources to extemporaneously generatenew solution paths that reflected their improved understanding of the relationships betweensystem components.

Solution 3: adaptation and systems thinking. The solution presented above would have eventuallyhelped mitigate the unhealthiness that arose from Englands population density. However, it wasnot the only solution to the problem of unhealthiness, nor was it the quickest. While he waswaiting on his colonies to develop the infrastructure (a pasture, road, and harbor) necessary to


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harvest and transport the nearby food resources, P2 began to construct the Grocers, a cityimprovement that increases the health bonus of certain food resources:

P2: Im trying to build more Grocers in citiestryin not to get people sickSmallpox can-can wipe England out.

Health, as it is represented in a game, is a variable to which many other variables contribute. In

other words, the relative health of a civilization is evaluated by a complex formula of manyvariables. P2 was trying to resolve his problem with unhealthiness in his cities by manipulating twosuch variables food resources and city improvements. P2 had decided to build the Grocers afterhe had thoroughly read the tooltip descriptions that appeared when he placed his mouse overpossible city improvements. P2 was not simply thinking about the game system, but also using theavailable reference tools to think with the game about the relevant problem space. In building anarrative of game events, P2 also spontaneously connected this phenomenon to that of smallpoxepidemics in England, one that he had presumably learned about elsewhere. This form of play,which we have called historiographic play, is a primary pleasure of gaming for many participants andfurther evidence of how game play can mobilize understandings (see Durga & Squire, 2008).

Social Identity and Systems Thinking

The manner in which P1 and P2 approach problems in their Civ 4 game play has much to do withtheir expert identity relative to the Civ 3 game title. Their expert identities in this historical gamingcommunity encouraged them to be confident as they solved problems, allowed them to gain statusin their peers eyes, and gave them a stake in the maintenance of the activity group. The subtext ofstatus and identity are pervasive throughout their conversations. P1, in particular, was attemptingto inhabit the role of expert by acting as a researcher and trying to establish himself as a Civ4mentor to P2.

Though he had only played the game for two hours, P1 methodically used language to self-nominate himself as an expert-mentor in his interactions with P2. Unexpectedly, this often resultedin a productive cooperation between the two in addressing the problem as P1 quickly taught P2 touse the game interface:

P1: Oh (.) well (.) yeah fine (.) here watchHere Ill show you way to get some food.Alright what you want to do (.) is you wanna first (.) click here.and then you wanna click on thisand you wanna find food sources like cows and other such itemsand connect themand connect all your cities together with this

P1 used several different communicative devices to make himself visible as an expert relative to P2in the above passage. First, he used quite a few deictic expressions to situate the interface tools withinthe larger problem context (see Levinson, 1983). Second, P1 enacted an expert identity throughdeclarative, interrogative and imperative designations of grammar (Halliday & Martin, 1993, p. 27).

These language-based methods of identity enactment persisted as P1 advised P2 where to look forfood resources:

P1: So like up here, lets see.oh so this is up by Germanyyou have cities over here tooWell what you wanna dois you wanna look up in Germanys area=P2: Scotland.P1: Scotland? Yeah Scotland.

Even as P1s bid to display his historical knowledge failed, the significance of this exchange withregard to identity is that he made such a bid at all. P1 is trying here to establish to P2 his fluency


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with historical language, and thus nominate himself as an expert within the community. P1,perhaps feeling a bit anxious that his expertise might be called into question in the aftermath of hissolutions failure, immediately endeavored to find a food resource elsewhere and show how hissolution would work with that resource. P1 then paused the problem-solving activity to engage ina face-saving exercise by redirecting the interaction (see Goffman, 1967). By instructing P2 step bystep how to go about linking his cities with nearby food resources, P1 moves the conversationaway from a discussion of his lapses in historical and geographical knowledge, and again re-

nominates himself as an expert or mentor to P2.

Discussion

Systems Thinking as Relational Thinking

This design-based research study has sought to produce, and then study in context, how complexforms of systemic thinking forms and evolves in situ. These data points illustrate how theformation of such complex systemic thinking, at least in this example, arises at the intersection ofthe material affordances of the Civilization game, and the social contexts in which play is situated.Knowledge of complex systems is employed as tools-for-action, or as ways of achieving goals at thematerial, personal and social planes, or as Nitsche (2008) would describe it, at the game as action onscreen, the game as a model in the players mind, and in the social game unfolding in real time andspace.

The process of learningthinkingdoing described here can be described as a collectiveprocess of trying to simultaneously understand the primary properties of the game system (e.g. therules as inscribed in the game) and the second-order emergent effects (e.g. the relative speed atwhich health can be increased via obtaining food from trade networks vs. building grocers). Thisinquiry process of trying to make sense of indeterminate systems is reminiscent of Deweyspragmatist account of scientific inquiry, in which he wrote that, with regard to complex problems,understanding or interpretation is a matter of the orderingof those materials that are ascertained to

be facts; that is, determination of their relations (1938, p. 511), or, in other words, how variouselements work together toward combining solutions that work in the world (1938, p. 511). Morerecent investigations into systems thinking in a number of fields from general systems theory tothe learning sciences have reached similar conclusions, namely that the ability to understand the

relations among elements in a system of meaning is critical for participation in todays society. Inthe interaction examined above, a clear pattern of thinking in which P1 and P2 go about iterativelyordering and understanding the relations of elements in the game system is evident. In seeking to

build a solution schema for the problem of unhealthiness in their cities, P1 and P2 navigate thegames detailed relational model of urban health, resource use and colonial trade. However, thegame play in this context is a deeply interpretive act, far more complex than simply one ofimporting the game model into the players head.

The manner in which P1 and P2 learn with and think about the problems that confront themin the game system, however, diverges at times from established notions of systems thinking in theliterature in that its deeply socially situated. The systems thinking seen in this interaction ismediated by the immediate context for the activity, grounded in similar prior experiences of theparticipants, distributed across social and material knowledge resources in the setting, and shaped by

their identities and discourse affiliations. We call this articulation of relational thought situatedsystems thinkingto distinguish it from amodal and decontextualized descriptions in prior research.An approach to situated systems thinking, of course, draws on prior research and adds nuance

to the topic, rather than invalidates it. Building on the prior researchs emphasis on relationshipsbetween system elements and the function of the system as a whole (see Checkland, 1981), weargue that studies of systems thinking in game-based learning environments should also accountfor participants experiential knowledge, the tools that structure and support systems thinking, andthe (social, physical and discursive) domains in which activity occurs (see Dewey, 1938; Lave, 1988;Gee, 1989; Glenberg, 1997). In the above interactions, systems thinking is thoroughly mediated bythese situated social dynamics, instead of existing only as an abstract and amodal heuristic forproblem solving.


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Systems Thinking is Distributed across Tools and People.

As they collaboratively make sense of how health bonus resources are modeled in the game, andhow such resources can be used by civilizations, P1 and P2 must understand how the different in-game micro-systems that they encounter can be used to solve their problem. These overlappingmicro-systems include: urban population health, use of resources local to cities, trade of resources

between nations, and trade of resources across oceans. In order to solve the problem immediately

confronting them, P1 and P2 have to act within and through different, interrelated, in-gamestructural activity schemes that model how human societies interact with the natural world andeach other.

As P1 and P2 collaboratively use their experiences as game players, interact with in-gameinformational tools that scaffold activity, and draw on external knowledge resources to solve theproblem of unhealthiness, a clear pattern of interaction with the game system emerges. Time aftertime, they make informed guesses about the game system that are grounded in a particular socialor material knowledge resource (e.g. past play experiences, in-game tools, history books, school-

based historical knowledge, etc.) and test the correctness of those predictions in the game world. Assuch, the players had their own mental model of the game system, background information abouthistory, and related dispositions for acting within that system all of which are driven by their goalsand realized through action. After acting on a prediction within the system, they use the resultingfeedback from the game to formulate their next solution prediction.

Systems Thinking is Grounded in Experience

The notion that players are making predictions about the consequences of action within a system of making bets about how the world will respond to an act (Holmes, 1993; Malaby, 2008) findsantecedent in contemporary psychological literature. Research from the grounded cognitionparadigm argues that humans are always mentally mapping the projectable properties of ourenvironment and, given a particular goal, its possibilities for that goal-oriented action (Glenberg,1997; Wolpert et al, 2003). At the same time, we frequently make predictions about theconsequences of action relative to our goals. Similarly, we see P1 and P2 learning about theproperties of the game system (their environment) by taking action according to a theory theyhave about the system, and seeing if the two align. Action in the system reveals the relative

incongruence of the players theory of the system and the extant operation of the system itself.Situated systems thinking, however, is grounded not just in making predictions about the

properties and dynamics of a system, but also the development of understanding and intuitionsabout the system. This view is indebted to Gees (2007) contention that good video games helpplayers develop an embodied empathy for the function of and relations between elements in asystem. But what happens when players are taken out of the context in which they have developedexpertise? Does situated systems thinking, as a mode of thought, extend across different activitycontexts?

Systems Thinking in Context

The question, Does game-based systems thinking transfer across activity contexts? is one that will

inevitably be asked. Based upon the data we have presented here and published elsewhere (seeSquire et al, 2008; DeVane & Durga, 2008), there is some evidence ofcontinuity of systems-orientedcognitive strategies across activities and contexts that we recognize as the foundation of a systemsdisposition. Evidence for this continuity can be found in players enlisting school-based resourcessuch as textbooks in the service of game play, or in their developing narratives to make sense of thegame model that include real-world referents (such as smallpox wiping out the population ofEngland). Such a movement of cognitive resources, narratives, and concepts across contexts isquite commonplace in the club, as we have reported here and elsewhere (see especially DeVane etal, 2009). We purposely eschew the use of the term transfer to describe this continuity of cognitivepractices as it tends to dissociate cognition from the contexts the communities, discourses, toolsand situations in which it is embedded.


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From a situated learning perspective, there are several issues with looking for the completeand comprehensive transfer of systemic knowledge across contexts. First, transfer research, andarguably the very notion of transfer, removes cognition from the activities, forms and contexts inwhich it takes place and to which it is inextricably tied (Lave, 1988). Moreover, it presumes thatcognition is centered in the individual and that it has a consistent internal structure. Second, theterm transfer makes invisible how comparably specific the differences are between the measuredactivities, settings and contexts. For instance, our research compares activities (e.g. Civ3 play to Civ4

play, Civ3 play to map-based civilization tasks, etc.) that are fairly similar and share some specificelements aside from their shared physical and social settings. Participants enlist previousexperiences (whether they are from school-based learning experiences, previous games at camp, orfrom watching a History Channel documentary the night before) toward understanding newsituations.

While we understand situated systems thinking to be strongly tied to the relevant distributedsets of structuring resources for an activity (Lave, 1988; cf. Bourdieu, 1977), we do not see it aslimited to isolated learning contexts and tethered entirely to the arena of an activity. Instead, weimagine that, given the right scaffolding and structure in a learning community, participants who

become proficient with systems thinking practices in a game-based learning context can develop asystems disposition towards different problem contexts. Such a disposition is not a universalheuristic for inquiry like that espoused in earlier works, but it is a set of attitudes toward systems

that can be seen to be interconnected in a general way (Thomas & Brown, 2007, p. 156). Thissystems disposition is the generative mechanism for situated systems thinking to occur in a context it is the inclination and demeanor required for a person to use available resources to structure aproblem in a systemic way. As such, we understand game-based learning communities as arenaswhere participants will gain embodied experiences with emergent complex systems that can beleveraged for future academic learning.

One limitation of the Civ-based approach to teaching systems thinking from this perspective isthat the game itself does not include systems-type concepts (such as positive feedback loops, orirreversibility of conditions), which might be important in other complex systems, such as ecologyor game design. This study (like others with Civilization) indicates some evidence for participantsdeveloping intuitions of such ideas; however, one could imagine a well-integrated learningcurriculum around systems thinking that involves players identifying and labeling such concepts in-game, reinforcing them through participants using them as tools to analyze game play (and solveproblems, much as happens here in discussion), and then applied to new, divergent scenarios.Consistent with a situated approach, however, we caution against simply introducing systemsconcepts and then thinking that participants will magically apply them across situations, just aslearning scientists have long noted that teaching algebra does not mean that people enlist theseideas in other aspects of their lives with any regularity (Lave, 1988; Lave & Wenger, 1991).

Social Identity and Systems Thinking

Research over the past three decades has made clear that learning is a very social phenomenon thatis deeply rooted in social languages, tied to social activities, and occurring in relation to socialinstitutions (Scribner & Cole, 1981; Gumperz, 1982; Engestrm, 1987; Gee, 1989). Learning isclosely tied to a persons identity how a person sees themself in relation to a social group, social

institution, social activity or set of social values (Gee, 1996). As such, people learn best when theyfeel that the role available to them in a learning activity is both valued by others in their activitygroup and in alignment with their interests and values. This phenomenon is clearly at work inthese examples, and it is in the interaction among individual/personal goals, the game space, andthe social plane in which learning is most robust.

If the values, structures and relationships of activities of communities of practice guide thedevelopment of expert practices, competencies and dispositions in a given social activity (Lave &Wenger, 1991), then the particularities of this context as a unique learning community should also

be acknowledged. We have argued here that expert identities are formed from relevant materialand social knowledge resources, and strategically performed in situated social contexts, and arecritical for accounting how systemic understandings arise (Wenger, 1999). Expertise, then, is the


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performance of a certain identity in a culturally-devised activity system and the ratification of thatidentity by the activity community, and this study illustrates how the particular identities availableto participants constrain and make possible different forms of systemic understandings (Cazden,1981; Holland, 1992; Gee, 2003).

Thus, the relational, systems-oriented way that the participants approach problems in thegame did not occur in a social vacuum it emerged from the (expert) identities that they inhabited,the social relationships of the group, and the moment-to-moment interactions among the

participants. P1, for example, appeared to put significant effort into displaying his nascentunderstanding of the relational game system because such a performance would afford him morestatus in that particular discourse group. In a similar manner, L1 provided P1 and P2 with supportthat enabled them to problem solve at a level that was above their familiarity with game playdetails. The systemic structures of meaning-making present in the interaction emerge not just outof the players experiences with game play and the game tools with which they interact, but alsothe dynamic social resources and interactions that flow through the activity space.

Conclusion

One of the key challenges in weaving twenty-first-century themes, such as global awareness,financial, economic, business and entrepreneurial literacy into core subject areas is that these

emerging fields are interdisciplinary in nature (see twenty-first-century framework for learning).They do not fit neatly into any traditional academic area and indeed, problems in these emergingfields are deeply distributed across multiple people and groups; they transcend the capacities ofindividual minds and often demand collaborative problem solving within decentralized anddispersed sources of information. How do we then reconcile the need for young people to learnhow to comprehend and think critically about relational, morphologic elements that constitutethese complex systems?

We argue in this article not for such game-based learning communities as any sort of magicbullet for producing such systemic thinkers, but rather, we envision the emergence within thesespaces of a kind of play which contains the kinds of systemic thinking that educators might hope tofind in such twenty-first-century classrooms. We find evidence from students reasoning here thatwhile the designers of a game like Civilization might not have had the sort of explicit agenda thatwould use the design of the game as a vehicle to teach systems thinking, Gees perspective thatgood video games can move players to a perspective of games as designed systems (2003) holds for

both the game and the world phenomena it represents, as the thinking participants engage incontains the morphologic elements and the kinds of complex relationships among economic,political and geographic systems that such calls for twenty-first-century classrooms might value.

This sort of thinking seems simultaneously deeply situated, embodied and dispositional. It isdifficult to imagine P2 developing such systemic knowledge in a more static medium; the kind ofthinking described here is full of multiple cycles of questions and answers, of multiple forms ofinterrogating the game system to consider how it responds. As expert players navigate the highlydynamic game environment of Civilization IV, they engage in practices that are unique to themedium of games and are radically different from learning in formal settings where the frameworkand organization of resources needed to accomplish the task are predisposed and fixed. How, then,will participants leverage these uniquely systemic experiences for life in an increasingly complex

world?Situated systems thinking is also profoundly social, and constructed around opportunities for

being an expert. This article has extensively focused on the mechanisms of expertise in action,information seeking as a source for action and the socially constructed identity of being an expert.Because mastery of complex organizations of content knowledge is empowering in games, itnaturally promotes players inquisitiveness to garner information resources beyond the game.Cognition in games, from a Peircean view, is a dynamic interaction of structured knowledge andexperience within complex semiotic spaces (Peirce, [1878] 1998). Thinking and the nature ofreasoning in such complex systems is triadic (see symbol/index/icon, Peirce, [1878] 1998, p. 247).Triadic divisions pervade semiotic spaces in games, making them rich sites for learning through


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experimenting with truth or knowledge that is refutable through a continuing process ofinterpretation.

As such, the development of game-based situated systemic thinking appears to be bothmaterially and socially situated in a manner that conjures a pragmatic theory of knowing (seePeirce, [1878] 1998; Dewey, 1938; Holmes, 1993), one that emphasizes that our thinking especially complex systems thought is fundamentally functional, grounded in the materialproblems of the moment, and also deeply social, expressed through social enterprise. As learning

scientists studying game play, we see the power of interlocking morphological complex systemswithin complex social environments to support and sustain this kind of meaningful identity work.

As game scholars studying learning, we are reminded of the critical importance of going beyondthe construction of a particular game, or even an individuals interactions with the computer, butinvestigating play in its most robust, complex forms.

Acknowledgements

The authors would like to thank the MacArthur Foundation for their support of this work. Inaddition, we would like to thank James Paul Gee, who (yet again) provided the original spark of anidea that this article is based on. Hopefully we did it justice.

Note

[1] An exception to this can be found in Squire & Giovanetto (2008), a cognitive ethnography ofApolyton University which found evidence for advanced participants applying concepts fromCivilization game play to contemporary events; however, conducted at a distance, this study did notinvestigate whether such thinking unfolded as a part of play in situ.

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BEN DeVANE is a doctoral candidate in the Educational Communications & Technology programat the University of Wisconsin-Madison. His current research is on the role of social identity ingame-based learning environments. His work has appeared in E-Learning, Games & Culture, andTheory into Practice. Correspondence: Ben DeVane, Department of Curriculum & Instruction,University of Wisconsin-Madison, 225 N. Mills Street, Madison, WI 53706, USA(ben,[email protected]).

KURT SQUIRE is an associate professor of educational communications and technology at theUniversity of Wisconsin-Madison. He is also co-director of the Games+Learning+Society Program

and Associate Director of Educational R & D at the Wisconsin Institutes of Discovery.Correspondence: Kurt Squire, Department of Curriculum & Instruction, University of Wisconsin-Madison, 225 N. Mills Street, Madison, WI 53706, USA ([email protected]).

SHREE DURGA is a doctoral student in the Educational Communications & Technology programat the University of Wisconsin-Madison. Her doctoral research is centered primarily on gamemodding and examining what and how players learn through continued participation in complexprogramming practices within these modding communities.Correspondence: [email protected]

economists who think like ecologists': reframing systems thinking in games for learning

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