The Higher Education of Gaming

New models of schooling are necessary as educational institutions attempt to transition into the digital age. This article is an ethnography of Apolyton University, an informal online university of gamers created to enhance pleasure from the game experience, teach the game, and improve upon the game’s standard rule set. It identifies the life trajectory of the community from formation to completion, and identifies key participant structures that scaffold learning. The article argues that participation results in a trajectory of experience whereby players enter as players but leave as designers, as evidenced by gameplay practices, as well as several participants being hired by game companies as a result of their participation. The authors argue that this sort of participatory ethos is central to learning systems in a digital age. For decades, educational technologists have lamented that our educational system is built on an industrial model whereby schools are factories that process students into products by filling them with knowledge that can be measured with ‘scientific’ instruments (Reigeluth, 1995; Tyack & Cuban, 1995). The social values, politics, and epistemological assumptions underlying such a design have long been criticized by educators, particularly for the hidden curriculum that it imparts: students’ role in the classroom is to absorb whatever information teachers, committees of ‘experts’, or federal officials decide ought to be learned (Apple, 1995). Students’ experience of the system largely consists of receiving objectives, reading state-sanctioned materials, and completing routinized activities such as the worksheet, story problem, five-paragraph essay, or occasional book report – none of which appear again outside of school. Whether or not such a system ever worked is debatable, but with changes in global communications, media, and economy, critics from progressives to neo-liberals are questioning the viability of such a system for the twenty-first century (Papert, 1980; Reich, 1991; Bánáthy, 1992; Shaffer, 2004; Friedman, 2005; Squire, in press). Not surprisingly, students’ attitudes toward school are at an all-time low and, for the first time in the history of the United States, a majority of students – even those succeeding in school – perceive it as worthwhile only for its exchange value (Lave, 1993; Baines & Stanley, 2003). The story for those who don’t do well in school is worse. Young males (particularly those from workingclass or marginalized backgrounds) are not affiliating with schools (Smith & Wilhelm, 2002). Males now lag behind females in achievement in most academic areas, and are less likely to attend and complete college. Perhaps surprisingly, white males are the only demographic group with increasing drop-out rates (King, 2000; Horn et al, 2002). However, the issue with low-achieving males is most dramatic for African Americans; nearly two-thirds of the African Americans attending college are women. Jacob (2002) describes the problem of boys in secondary and post-secondary education as one of ‘non-cognitive’ skills; students (particularly males) lack the ability to pay attention in class, organize homework, and seek help from others. In short, they are a poor fit for the social organization of contemporary schools. While formal schools perpetuate an industrial-age educational system, disruptive technologies such as computer and video games, the Internet, and mobile computers make possible new social forms of social organization for learning (Scardamalia & Bereiter, 1994; Lankshear & Knobel, 2003; Gee, 2004; Squire & Steinkuehler, 2005; Lankshear, 2007). Anyone with The Higher Education of Gaming 3 an Internet connection can access online references (e.g. Wikipedia), communities of specialists in specific domains such as politics (e.g. Daily Kos), and libraries of scanned print materials (e.g. Google Print) – and increasingly participate in the production, legitimization, and dissemination of information (Squire, 2002; Jenkins, 2006; Lankshear & Knobel, 2006). Computer and video games give players designed experiences where they can lead civilizations, travel to foreign lands, or become international financiers (Squire, 2006). Studies of informal learning communities occurring on the Internet suggest that they function in a radically different way to traditional schools; they function as sites of collective intelligence, affinity spaces, or self-organizing learning systems that embody values of the new capitalist work order (Levin & Arafeh, 2002; Wiley & Edwards, 2002; Gee, 2003; Lankshear & Knobel, 2003; Jenkins, 2006; Steinkuehler, 2006). Is it surprising, given these realities, that our students seem more interested in their games than they are in schools? (Smith & Wilhelm, 2002; Gee, 2004). Yet, just what an ‘educational system’ for the information age would look like is not clear. If the communities associated with these technologies tend to have distributed rather than centralized knowledge structures, and value expertise over credentialing and open knowledge sharing over closed knowledge structures, how will they be used given the current organization of schools? When classrooms and schools (on the local level) have adopted these technologies and associated curricular innovations, the particular technologies have been subsumed by existing classroom and school cultures rather than transforming them (Squire et al, 2003; Leander & Duncan, 2004; Leander & Loworn, 2006). Thus, to understand the future of education, it is critical not just to look at school-based interventions, but also to look at learning systems indigenous to the digital age. To paraphrase Seymour Papert, if you want to design an automobile, there is only so much you can learn from studying the horse and buggy. This article attempts to do just this through an ethnography of Apolyton University (AU), an online college of game players designed to usher players from the novice to expert level, which, along the way, positions them as content producers, something that we contend is a core feature of digital learning environments in the twenty-first century. We argue that a core intellectual feature of a twenty-first-century educational system should include inroads into participation in cultures of simulation (Starr, 1994; Turkle, 1995). Starr (1994) argues that simulations – the process of setting up scenarios and exploring under what conditions they might work – are at the core of business, government, science, and entertainment, and video games are the public’s primary exposure to this important way of thinking. As the number of new literacy studies (and particularly game studies) grows, it is critical to understand how learning occurs with interactive media in ‘indigenous’ settings. A few studies have examined how learning occurs through gameplay as primarily computer-machine interaction (Gee, 2004; Squire, 2004, in press; Davidson, 2005); from a sociocultural learning theory perspective, studies of gaming cultures are somewhat slower to develop (as an example, see Steinkuehler, 2006). This study seeks to understand how self-organizing online communities for learning function through a cognitive ethnography of AU. AU is an online learning community of game players dedicated to improving their understanding of the computer game Civilization III. Civilization III is a world history simulation game (played on realistic or fictitious maps) where players lead a civilization from 4000bc to 2000ad. Although players receive no credits for participating in AU, they create and participate in dozens of courses with the intended purpose of teaching new strategies, countering for inadequacies in the game’s artificial intelligence (AI), and expanding their understanding of the game. This study investigates three interrelated research questions: (a) What are the participant structures that emerge at AU? (b) What are the consequences of participation, or what learning occurs through participation in AU? and (c) What is the life cycle of such selforganizing learning systems? Understanding how game-based learning communities function might not only contribute to our understandings of educational systems, but also to theoretical issues central to game studies, including what constitutes highly developed game literacy. Kurt D. Squire & Levi Giovanetto 4 Interactive Learning: education in a knowledge-based information-communication age Immersive interactive technologies – or ‘video games’ – have emerged as a powerful social, technological, and cultural force (Squire, 2002). Not only do games push the boundaries of interactivity, consumer-grade simulation, AI, and virtual-world design, but they also initiate students into practices, literacies, and cultures central to the information age (Gee, 2003). And, as surveys by Beck & Wade (2004) show, participation in games cultures is promulgating cultural values such as an increased appetite for risk, a valuing of expertise over formal credentialing, and entrepreneurialship; values and dispositions that align closely with those of the new capitalist work order but are at odds with those of formal schooling (Gee et al, 1996; Beck & Wade, 2004). It is ironic that games have had little impact on education as they embody powerful principles of learning (Gee, 2003). Games ‘teach’ concepts by immersing players in experiences where knowledge is useful, modeling expert problem solving, calling attention to key features of the problem through cues, and structuring problems so that the player builds on previous understandings, which are all features of powerful learning environments (Bransford et al, 2000; Gee, 2003). Crucially, games do not let players do whatever they want, but recruit a particular way of thinking through the careful construction of tutorials, scenarios, and rules (Gee, 2004). After 40 hours, game players learn not only new vocabulary and concepts, but also to adopt a particular set of values; to see the game world in a particular way. Already the United States Army and corporations such as Chrysler use the medium for communicating ideologies. However, mainstream educators have been slower to respond (Squire, in press). Interactive Learning Systems Lemke (1998) develops the notion of the interactive learning paradigm to describe the framework for learning in the information-age society. Contrasted with the curricular paradigm, where learning objectives are determined by specialists and curricula implemented by teachers, the interactive learning paradigm assumes that people determine what they need to know based on their participation in activities in which such needs arise, and in consultation with knowledgeable specialists; that they learn in the order that suits them, and a comfortable pace, and just in time to make use of what they learn. This is the learning paradigm of the people who created the Internet and cyberspace. It is the paradigm of access to information, rather than imposition of learning. It is the paradigm of how people with power and resources choose to learn. Its end results are generally satisfying to the learner, and usually for business or scholarship. It is perhaps also the paradigm of fast capitalism. (Lemke, 1998, p. 294) A core feature of this information age – and an important location where technology, learning, and contemporary culture intersect – is video games (Gee, 2003; Squire, in press). Digital gaming, the entertainment medium and subcultures indigenous to the computer may be quintessential sites for studying how such a paradigm emerges and functions, particularly because of the centrality they place on digital tools such as (1) simulations to think within, (2) tools to think with, (3) cultural spaces to create and inhabit, and (4) media for personal expression (Gee, 2003; Squire, 2003; Jenkins, 2006; Shaffer & Clinton, 2006; Steinkuehler, 2006). Cultures of Simulation The growth of gaming in government, business, and now education is part of a broader phenomenon, which Starr (1994) and Turkle (1995) (drawing from Baudrillard) call a culture of simulation. In science, many fields operate less like the classic high-school textbook process of hypothesis testing and more by a process of gathering data, using digital tools to build models and simulations, and then refining scientific theories (Casti, 1997; Feurzeig & Roberts, 1999; Wolfram, 2002). In public policy, issues such as social security are debated not through hypothesis testing and experiments, but through building sophisticated models and simulations of economic systems, so that literacy requires an understanding of how such models are developed and how they can be The Higher Education of Gaming 5 manipulated by changing initial conditions or the parameters of the simulation. Models and simulations are equally central to business, where spreadsheets are used to forecast scenarios and test ideas in virtual worlds before they are tried in the real one. In examining SimCity from a policy standpoint, Paul Starr (1994) argues that the real importance of games in education is not their ability to teach facts or improve learning according to a fixed set of objectives, but rather their ability to help develop new digital literacies. Starr writes: Moreover, as computer games become more elaborate and widely used, their sheer multiplication and increasing plasticity may promote a healthy skepticism about their predictive power. Playing with simulation is one way to see its limits as well as its possibilities. ... For better or worse, simulation is no mere fad. Indeed, to think of simulation games as mere entertainment or even as teaching tools is to underestimate them. They represent a major addition to the intellectual repertoire that will increasingly shape how we communicate ideas and think through problems ... We shall be working and thinking in SimCity for a long time. It is not yet well specified just what this culture of simulation is. Perhaps due to the rise of the Internet and the concurrent shift to sociocultural models of learning (cf. Kim, 2000; Turkle, 2003; Barab & Roth, 2006), notions of simulation briefly took a back seat to theories of virtual communities for learning in educational technology in the late 1990s. The popularization of video games in academia and popular culture, combined with the capacity of games for placing learners in collaborative problem-solving spaces, has recently pushed them back to the forefront as spaces to be investigated for the future of online learning environments (Steinkuehler, 2006, 2008). The distinction between video games and simulations is increasingly blurred. Games such as Flight Simulator, Full Spectrum Warrior, or America’s Army are simulations of real-world practices and are routinely treated as such for the purposes of training. Indeed, the classic textbook definition of simulations and games – simulations are symbolic representations of a system, whereas games are playing by a set of rules for the purposes of entertainment – are not mutually exclusive in any way. One can take a game such as Doom, which on the surface is not a simulation of anything in particular, and use it as a metaphor for corporate life – perhaps as part of a training session where office managers play through a level and compare the basic game mechanics with their corporate rule structure. These examples suggest how simulations can be considered by their levels of fidelity to the systems that they represent. Thiagarajan (1998) distinguishes between highand low-fidelity simulations; low-fidelity simulations, which are commonly called idea simulations, seek to illustrate a few relationships by simplifying complex situations to a few key variables. The most common example of an idea simulation might be a very simple predator–prey simulation, such as one that models how an increased number of predators (such as foxes) would affect a population of prey (such as rabbits). Such simulations are used to show counter-intuitive properties of systems, such as how an increase in predators will eventually set the system out of balance, causing wild fluctuations in populations, if not extinction of both the predator and the prey. High-fidelity simulations are those that attempt to model the real world to a point where they have predictive power over how the world behaves. The classic example might be a flight simulator, where one assumes that adjusting the pitch of the aircraft will have the same results in the simulation as one would find in an actual airplane. In complex conceptual domains, such as the understanding of world history, predictive simulations are not only impossible to create, but may not be educationally valuable if they did exist; the problem, which has been called the 1:1 mapping problem is this: a perfectly detailed map where one mile equals one mile does not serve to make any relationships clearer. A perfect representation of history would include so many variables that it would do little to help discern key relationships. Within the simulation literature, it is believed that explanatory models and simulations that fall in-between these two levels of fidelity are the most desirable for educational purposes. Explanatory models are strategically designed to capture the key necessary variables to understand a particular phenomenon, yet not completely predict future behaviors (Brown, 1994). In the case of Civilization III, it contains enough data and simulated systems to explain the processes by which civilizations flourish and fade over thousands of years, but would not necessarily predict what would happen to the United States in the year 2050 given current conditions. Educators using models and simulations also stress the importance of detailing the purposes behind a model. As Kurt D. Squire & Levi Giovanetto 6 simplifications of reality, models leave out key data; in the case of Civilization III, it is a poor simulation for investigating cultural processes, and does relatively little to explain the particulars of any civilization (such as Egypt or Rome). Educators have drawn important distinctions between students learning with a pre-made model and students learning through the modeling process. Researchers have argued that engaging students in the modeling process, which involves asking questions, gathering data, building representations (models), interrogating those models, collecting more data, and then reflecting and building arguments based on those models, is the goal of modeling, not necessarily simply using a model to build more robust understandings (Resnick et al, 1996; Feurzeig & Roberts, 1999; Barab et al, 2000). Certainly there is value in these approaches, not just for the robust conceptual understandings they produce, but also because using the modeling process as the core classroom activity is to do science; thus, there is an inherent value to having students learn through modeling (Colella et al, 2001). At the same time, even proponents of modeling-based curricula have noted that learning through most modeling curricula involves learning complex software programming techniques, which frequently requires so much energy learning to use the tool that students have little opportunity to do much with it. Digital games offer an intriguing hybrid space between learning with a model and learning through modeling. As interactive systems, games provide worlds that players can explore and inhabit, creating an interesting hybrid space that is not merely ‘learning with a simulation’ and not entirely designing a simulation. Crucially, games do not set a fixed path of activities that players must accomplish, but rather set up possibility spaces whereby players can create goals and devise creative solutions to those goals (Wright, 2001; LeBlanc, 2005; Squire, 2006). As such, when we play a game such as Civilization III, a primary pleasure is being a part of the game system (Friedman, 1999). As a result, we develop what Gee (2004) calls an ‘embodied empathy’ for the game system; a pathos for what it is like to participate in that system and a sense of how the system operates. In other words, games are as complex (or more so) as many explanatory models, and they tend to produce sophisticated understandings of the game as a model. However, a question for educators is how to usher students from being casual players of games to sophisticated experts who display a design-level understanding of the simulation. Previous studies have suggested that simulation games can be a powerful medium for learning, but a significant investment of intellectual resources is required to learn to play them (although certainly less than most programming languages). The social values of contemporary curricula, which Lemke criticizes as being organized around a metaphor of social control as opposed to personal exploration, further challenge game-based educators as game-based curricula frequently result in divergent learning outcomes. Education within an Interactive Age A key question for educators is how to design interactive learning systems that are appropriate to the information age and contain the kinds of learning (self-directed, personally meaningful, and full of deep conceptual understandings) that Lemke advocates. The goal of such an interactive learning system might be a highly motivated learner who can ask good questions, marshal resources to answer them, and use media to express these understandings (New London Group, 2000). One avenue for educators interested in designing such systems might be to examine naturally occurring ones. Indeed, Internet researchers are beginning to identify examples of such spaces for learning spontaneously forming online (cf. Black, 2005; Lam, 2006; Steinkuehler, 2008). Yet, we are only beginning to understand how they form, flourish, evolve, and expire (or mutate). Examining the web resources around Age of Empires, a popular historical strategy game, Gee (2004) developed the term affinity spaces to capture how learning in the interactive age is frequently organized around attracting activities (such as gaming) as opposed to geographical proximity, social status, race, or class. Certainly, race, gender, and class are mobilized and enacted through such communities; however, in the affinity spaces examined to date, the primary entrance requirements are knowledge, skill, and curiosity about the affinity space. Gee intentionally avoids the term community of practice, arguing that many online spaces, such as the ones occurring around gaming, have less intense social interactions, a higher number of lurkers, and generally less formally The Higher Education of Gaming 7 expressed rules and hierarchies than the canonical examples of communities of practice described in the research literature (cf. Lave & Wenger, 1991). In comparison to communities of practice, affinity spaces have much more relaxed requirements for participation, less codified roles, and more permeable boundaries between participants and non-participants. A key element of such affinity spaces is that they are created and sustained by learners themselves, affording opportunities for learners to design their own contexts for learning. Any motivated, curious user can set up a blog, wiki, or podcast around a topic, and endeavor to create a learning community around an area of interest. As Lemke (1998) notes, the Internet itself was created through such distributed communities as groups of researchers gathered to pursue questions of intellectual interest. Digital literacy, then, from this perspective, involves not just learning to make meaning with digital media, but also knowing how to leverage and even create social networks to further one’s learning. In many respects, education in an interactive age might be thought of as realizing the goal of progressives, in that education is no longer preparation for life, but is life. To date, most projects seeking to build communities in the service of virtual learning (particularly around digital games or game activities) have employed design-based research methodologies to explore new pedagogies with digital media with little sustained examination of existing online communities (or affinity spaces). Recently, Internet researchers have begun to examine how such affinity spaces operate as spaces for learning. Rebecca Black (2005) has begun to investigate the function of fanfiction communities as spaces to further writers’ identities as authors of fanfiction, focusing particularly on the literacy practices that participants engage in which further their development as authors. Black notes that fanfiction sites (perhaps necessarily) exist outside of the confines of school, drawing on their fans’ cultural resources, personal identities, and interests, and serving as sites where participants can develop identities as competent fanfiction writers within a supportive, yet critical, community. Steinkuehler’s (2006) ethnography of Lineage II players suggests the many functions that massively multiplayer online games play. They are worlds that players create for one another as sites for retribalization; they are third spaces where players socialize in spaces that are neither work nor home; and they allow players to explore identities less organized by their geographical location, social class, or ethnicity. Online games as cultural spaces certainly have their ideologies; as Steinkuehler argues, the cultural space of Lineage II (as one example) is organized around mericratic principles. Steinkuehler shows how, through joint collaborative activities, players mentor one another not just in how to play the game, but also in how to become particular kinds of players who adopt particular values and stances toward the (game) world. As players form guilds, they create lasting social structures with deeper trajectories for participation. Steinkuehler argues that these function as new kinds of literacy spaces where text is used (often but a few lines of text at a time) to forge new identities and social relationships hitherto unavailable. Research Context: Apolyton University This study seeks to add to the growing work on games and game cultures by providing an ethnographic account of an online community of high-performing game players around the turnbased simulation/strategy game Civilization III. The particular community studied here, Apolyton University, is a self-organizing group of players developing their own courses, curricula, and instructional activities to better understand the game Civilization III. This study seeks to document how such communities form and function, as well as use players’ experiences to theorize the nature of expert gaming expertise, particularly how players draw upon it to think about history and current events. Specifically, we are investigating the following questions: (1) How do such communities form, evolve, and expire? (2) What participant structures evolve, and how do they contribute to learning? (3) What kinds of learning occur through participation in such communities? (4) How do participants think of the game as a world history simulation? Understanding how AU functions and what understandings develop through participation in it might help us design better learning environments. Kurt D. Squire & Levi Giovanetto 8 Civilization III as Historical Simulation Civilization III is the third installment of the Civilization series, designed by legendary game designer Sid Meier and heralded as perhaps the most important strategy series in computer gaming. Players lead their band of people from the dawn of civilizations (4000bc) to the present day (roughly 2050ad). The gameplay consists of examining geographical resources to determine where to locate cities, prioritizing technology research, deciding what types of improvements to build in cities, and negotiating with other civilizations. As a result, players wrestle with choices such as emphasizing military technology over domestic services (guns vs. butter), whether to participate in alliances or remain isolated, and how best to manage their resources. The gameplay is notoriously complex. The game model contains thousands of variables, the interface contains several strands of complex information, and mastery over the game takes hundreds of hours of play. Although Civilization III was not designed for educational purposes, many educators have discussed its pedagogical potentials. On the surface level, Civilization III contains hundreds of concepts, names, and figures that students must become familiar with simply to play the game. The 256-page Civilopedia embedded within the game reads as a glossary for a high school or college textbook, introducing the player to concepts such as monarchy, monotheism, or Leonardo da Vinci. The custom maps included in the game not only represent the Earth’s physical geography, but also an embedded argument for how physical and cultural features co-evolve. As players make choices, they are forced to ‘deal’ with the realities of the simulation: cities grow more quickly in river valleys, civilizations with complex trade networks grow richer and develop technology more quickly, and focusing on military production to the exclusion of social services leads to a decline in civic happiness, cultural growth, expansion, and technological development. As players wrestle with choices within the game, they develop narratives of their play that can be the basis for understanding historical and global events. Perhaps most importantly, the tacit message behind Civilization III (the message behind the medium) is that of historical malleability. Our current global conditions are not the result of an inevitable unfolding of events, but the result of human actions within guiding rules and constraints; rules that can be modeled and understood. Thus, Civilization III makes an intriguing site for study because it is taking a common phenomenon (world history) that we typically understand through narratives but dealing with it as a simulation. Indeed, although historical modeling and simulation is a young field at the cutting edge of historical research (cf. Staley, 2003), it is an experience that millions of children and adults are being exposed to via Civilization. Much as Paul Starr (1994) mused about the consequences of millions of children growing up playing SimCity, we might wonder what the long-term consequences are for the study of history when millions of children are exposed to world history primarily through simulation. To date, there have been no studies of this phenomenon. Scholars such as Sherry Turkle (2003) have interviewed children playing SimCity, expressing concern that they develop simplistic causal models for how cities operate. What has not been studied is how developed (or expert) gamers conceptualize the game system, particularly within interpretive communities in which their understandings are negotiated. From a sociocultural perspective, we might anticipate that it is within these communities that norms are developed and realized, meanings negotiated, and perspectives legitimized. Apolyton University as Self-organizing Learning Community In the spring of 2004, while working on research using Civilization III in after-school programs, we were introduced to Apolyton University, an online community of game players dedicated to improving their collective Civilization playing skills.[1] AU is a subset of http://Apolyton.net, one of the largest online affinity spaces for Civilization players. As one founding member describes it: Apolyton University is a school of strategy, where students sharpen their Civ3 [Civilization III] skills and share their experiences in a series of thematic games. When playing an Apolyton University game, gaining and sharing knowledge is more important than getting a high score, or even winning the game. Participants are encouraged to share their strategy after the game, and even to try several attempts. (http://apolyton.net/dir/index.php?cat=5&t=sub_pages) The Higher Education of Gaming 9 This description captures several key features of AU that both characterize it as a learning community and set it apart from traditional schooling. First, the core activities are defined as sharpening skills and sharing experiences, as opposed to mastering a particular body of content or fulfilling a set of requirements. Second, gaining and sharing knowledge is more important than high scores. Not only are high scores (e.g. grades) less important than learning, but sharing knowledge is privileged. Participants are assumed to be valued producers of knowledge, and opportunities to share what one has learned are seen as a vital, integral part of learning. Last, experimentation and mastery are valued over getting it right the first time. No one here cares how long or how many attempts it takes to solve a problem. Learning, not regulation, is the goal. AU, as of this writing, consisted of six initial ‘group mini games’, which are introductions to the community, and 23 ‘courses’, designed, developed, and posted by members (see Figure 1). In each course, players download a custom game file, which they play through at their own pace. Players then take notes and post their strategies throughout the game, which range from a paragraph to a few pages in length, with screenshots (see Figure 2). These notes become the basis for discussion, with players analyzing one another’s games and commenting on themes cutting across games. This practice of taking and posting notes evolved into what the community calls ‘during action reports’ (DARs) – reports that players post every 40 turns so as to break the game into more manageable chunks. In sum, the community consisted of 19,302 posts by 74 registered members with perhaps another 100 lurkers (estimated through analyses of ‘reads’ per post). Participants monitored the forums fairly closely; we calculated the median response time for feedback on a post to be between two and five hours. Figure 1. List of Apolyton University courses. Kurt D. Squire & Levi Giovanetto 10 Figure 2. Typical During Action Report post.