How Computer Games Help Children Learn – Chapter 4

Shaffer, D. (2006). How Computer Games Help Children Learn. New York: Palgrave Macmillan.

The negotiation game described in the chapter seems similar to a case-based scenario that Shaffer described elsewhere (in his Phi Delta Kappan article) as being more applicable for practitioners than novices. Shaffer spends a lot of time exploring the concept of the values of a profession and argues that games begin with personal interests but transforms those to professional interests as “players take on the values needed to master the game.”

A new requirement for games–the need to impose obstacles that are neither too easy (boring) or too hard (frustrating)–is described as a condition of flow. In the vocabulary of video games, levels should be barely achievable.However, Shaffer acknowledges that for players to even try to overcome obstacles, they must care.  Motivation makes players care.

Making a game fun provides intrinsic motivation. While Shaffer doesn’t offer a full exploration of fun, he argues that fun is playing by the rules and that fun offers self-efficacy–players feel they are able to master the game–and control. His conclusion is unsubstantiated but logical: what keeps players motivated is creating value for the values of the profession (which in most professions means “stepping outside yourself and see things as others” see them).


How Computer Games Help Children Learn – Chapter 1

Shaffer, D. (2006). How Computer Games Help Children Learn. New York: Palgrave Macmillan.

The Debating Game described in Chapter 1 exposed many familiar aspects of games, but also raised issues that require further consideration:

  • Rules define games (and play) and yet “what matters is presenting an interpretation and defending it” (which seems identical with Bloom’s evaluation level). This dichotomy and the need for authenticity suggests that writing the rules is the most difficult aspect of game creation.
  • Some roles make players care about winning; other roles make players care about self-efficacy. Because roles (and thus end-states) differ, rules vary with roles. This role-rule pairing (actually multiple pairings) create the narrative, another difficult task for the game creator.
  • We play out our real life situations in game roles and rules, and yet fantasy seems a key motivational element in most games (and especially the idea that in games, we can do things we can’t do in real life).
  • The definition of epistemic games as requiring “you to think in a particular way about the world” seems at odds with rules, unless the rule is to think like an historian (like an economist, etc.) which makes writing rules even more difficult.

The characterization of school as a game to teach you how to think like a factory worker suddenly made standardized tests make sense.


The difference between intrinsic and extrinsic motivation was already clear to me, although I liked the authors’ delineation that motivation (not just intrinsic, though, in my opinion) “exists in  the relation between individuals and activities.” The distinction that intrinsic motivation is enhanced by a sense of competence only if accompanied by autonomy makes sense although it seems limited; similarly, despite the research cited, I’m not sure that all extrinsic rewards, threats, deadlines, and competition undermine intrinsic motivation. The parallel that autonomy also influences extrinsic motivation implies (obliquely) that competence also influences extrinsic motivation; later in the article, the authors theorize that both relatedness and supports for competence (optimal challenges and relevant feedback) support the internalization of motivation.

The continuum of extrinsic influences seems less a series of 4 distinct types and more a smooth gradient (although three distinctions seem clear: reward/punishment, ego/approval, and self-endorsement). The most applicable idea was somewhat hidden: the potential for intrinsic motivation increases with age, and that learners become more internally regulated over time. If true, this suggests that relying on intrinsic motivation will not be as effective with young learners.

Learner Analysis

Learner needs are couched in terms of the design phases:

  • Define – determine learner needs and understand the implications for instructional materials
  • Design – define audience
  • Demonstrate – monitor prototype
  • Develop – determine ability of materials to meet learners’ needs during formative evaluation
  • Deliver – collect learners’ responses

I especially liked the distinction that (a) learner’s information needs impact goals and outcomes, while (b) learners’ characteristics impact strategy and activities (although this is a little simplified since information needs also impact activities, and characteristics also impact outcomes).

The needs assessment starts the spiral of design while the summative evaluation concludes it. Defining the needs assessment as the process of identifying the gap between the current and ideal situations seems reasonable but more content-focused than learner-centric.

The stratification of understanding learner characteristics reflects the practical orientation of this chapter, although the instructional implications of each characteristic is somewhat redundant; the breakdown (for me) that was more clear:

  • Prior knowledge
    • Speed of presentation
    • Redundancy
    • Level of detail
  • Motivation
    • Relevancy convincing
    • Type of feedback
    • Reinforcement types
  • Abilities
    • Learner control
    • Level of concreteness
    • Response mode
    • Difficulty of practice
  • Learning context
    • Media
    • Collaborative vs. individualistic
  • Application context
    • References and tools
    • Context of practice
    • Successful practice (level)

The concept that each learner has preferred methods of learning and communicating enhanced previous coverage (basic course) of learning styles; I especially appreciated the clarification that the preferences can change depending on subject, delivery environment and motivation level. The idea that learner characteristic assessment is like market segmentation gives me a powerful metaphor for working with corporate clients. I also liked the idea that contrived analysis (via brainstorming) can contribute to understanding learners (as sufficiently as?) derived (from data collection) analysis. However, the statement that 10-12 people (if they reflect the audience) is a sufficient sample suggests that formal analysis is not as difficult as I imagined. The concept that data can be collected from a variety of sources–interviews, focus groups, surveys, direct observation, and research literature–offers multiple tools. I also liked the combination of narrative (qualitative) and percentage (quantitative) reporting.

The final section tying learner analysis to the five phases and the ASC cycle was obvious; the actual application to food safety training was more useful (to me).

Motivation in Alien Rescue

Although written to describe an educational simulation (Alien Rescue), the article provides specific information about PBL design:

  • understanding is created through interaction with environment;
  • cognitive conflict (misperception?) is a stimulus for learning  and determines the organization and nature of what is learned (determines how instructors create the organization for learners, or determines how learners themselves organize learning in their internal schema?);
  • knowledge evolves through social negotiation

Intrinsic motivation sources:

  • Problem-solving
  • Information processing
  • Play
  • Voluntary acting
  • Socializing (ignored in previous research)

are mapped to the game-like qualities of Alien Rescue:

  • Authentic situations (personally meaningful role-plays, ideally adapted to individual ability)
  • Challenges (intermediate levels of surprise and incongruence)
  • Control (autonomy, as well as Maslow’s security need)
  • Fun
  • Confidence
  • Fantasy (fictional narrative)
  • Identity
  • Interactivity
  • Novelty
  • Sensory engagement
  • Socialization (the group, as well as the individual’s identity development within that group)

Students did not like ceding control to the expert mentor;  an interesting question is whether they would equally dislike ceding control to another student player. If not, the idea that peer collaboration can scaffold learning through the zone of proximal development might resolve control disaffection.