Context-Embedded Learning Part II: Learning By Doing (Prensky and Gee)

This is part of the Context-Embedded Learning section of my dissertation lit review:

Modern video game scholars have argued that video and computer games can help provide such a context for learning. Prensky (2001), for instance, highlighted several relevant concepts; games have rules, goals, outcomes/feedback, conflict/competition/challenge/opposition, problem solving, interaction, representation, and story (p. 106), including character (p. 134, 118-127). Regarding goals specifically, Prensky suggests elsewhere that the goals must be “worthwhile” (2005a, p. 9), or specifically “worth it to [students]” (2005, p. 4), to be effective. When he covers game design, he considers the way in which a game must be balanced so that “the game is neither too hard nor too easy at any point” (Prensky, 2001, p. 133). A well-designed game, particularly an RPG or MMORPG, can also include elements of exploration and discovery as well (p. 136). In his projection of the future of digital games, Prensky (2001) predicts that games will be “much more realistic, experiential, and immersive” and include “more and better storytelling and characters” (p. 404).

Prensky later wrote about five levels of learning by doing. The first of these was the How level; as Prensky (2006) explained, “the most explicit kind of learning in video and computer games is how to do something” (p. 64). The second level is learning What to do (and what not to do) in any particular instance (p. 65). The third level of learning is the Why level; “strategy – the why of a game – depends on, and flows from, the rules” (p. 67). Why lessons include cause and effect, long term wining versus short term goals, order from seeming chaos, second-order consequences, complex system behaviors, counter intuitive results, using obstacles as motication, and the value of persistence (p. 67-68). The fourth level, Where “is the context level, which encompasses the huge amount of cultural and environmental learning that goes on in video and computer games” (Prensky, 2006, p. 68). Finally, there is the Whether level, in which “players learn to make value-based and moral decisions – decisions about whether doing something is right or wrong” (p. 69).

Like Prensky, Gee discussed ways in which video games can provide a context for learning. Gee (2003), a linguist and cognitive scientist asserted that “words, symbols, images, and artifacts have meanings that are specific to… particular situations (contexts)” (p. 24). He argued that a good game can provide a “context within which to understand and make sense of what one is going to do” (Gee, 2004, p. 64). He also suggested that “the theory of learning in good video games is close to… the best theories of learning in cognitive science” (Gee, 2003, p. 7).

Gee (2003) focused on the way that video games can provide a learning environment that is “set up to encourage active and critical, not passive, learning” (p. 49). He believed that active critical learning was based on experiencing (seeing, feeling, and operating on) the world in new ways (p. 23), and on being able to not only “understand and produce meanings” in the domain being learned, but also being able to “think about the domain at a ‘meta’ level as a complex system of interrelated parts” (p. 23).

Even at a more basic level, Gee (2003) believed that “basic skills are not learned in isolation or out of context; rather… a basic skill is discovered bottom up by engaging with the domain” (p. 137). Gee also suggested that learners should get “lots of practice in a context where the practice is not boring (i.e. in a virtual world that is compelling to learners on their own terms and where the learners experience ongoing success)” (p. 71).

Gee offered the following recipe for providing students with a context for learning.

“The recipe is simple: Give people well designed visual and embodied experiences of a domain, through simulations or in reality (or both). Help them use these experience to build simulations in their heads through which they can think about and imaginatively test out future actions and hypotheses. Let them act and experience consequences, but in a protected way when they are learners. Then help hem to evaluate their actions and the consequences of their actions (based on the values and identities they have adopted as participants in the domain) in ways that lead them to build better simulations for better future action. Though this recipe could be a recipe for teaching science in a deep way, it is [also] a recipe for an engaging and fun game. It should be the same in school.” (Gee, 2005, p. 63)

Gee (2005a) also expected good games to allow learners to practice skills “until they are nearly automatic, then [to have] those skills fail in ways that cause the learners to have to think again and learn anew” (p. 27) in cycles of expertise. In addition, virtual contexts can provide a greater amplification of input for the learner; in other words, “for a little input, learners get a lot of output” (Gee, 2003, p. 67). Because of these elements, and because of the tireless replayability of a game (as opposed to a teacher who may quickly tire of explaining things more than once), games can offer learners “a context where the practice is not boring” (p. 71) so that “they spend lots of time on task” (p. 71). Learners should also be given “ample opportunity to practice, and support for, transferring what they have learned earlier to later problems, including problems that require adapting and transforming that earlier learning” (p. 138).

I’m seeking feedback on this writing, so please let me know what you think in the comments.

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