How Computer Games Help Children Learn – Chapter 5

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

This chapter starts to get into learning theory.  The two major schools are succinctly defined:

  1. symbolic – knowledge developed in solving one problem can be used to solve other analogous problems
  2. schematic – facts (declarative) and problem-solving rules/strategies (procedural) knowledge are combined to solve problems

These views are contrasted with situated cognition: a view that all activity (including thinking) is part of a community of practice where newcomers learn through legitimate peripheral perception. However, I suspect that the views can be merged: declarative facts and procedural strategies can be developed through legitimate peripheral perception and refined through symbolic problem-solving pattern-matching within a community of practice that provides feedback.

Game details amplified the epistemological concept:

  • a profession is learned (and practiced) within  a specific place and time (environmental component)
  • the public reflection-on-action process created the personal process of reflection-in-action
  • each person worked on a small part (which made a complex task explicit) but saw the whole process; this instructor-crafted delineation linked the social space and the problem space

By the end of the game, users were able to:

  • offer suggestions (not simply respond)
  • think of audience (not simply the task)
  • justify choices (not simply choose)
  • see the larger impact (not simply the immediate solution)

In short, players felt like journalists “even though they had come to understand how complex and difficult” being a journalist is. The goal was not necessarily to train players to be a specific professional but to be the kind of people who can think like professionals.

The discussion of the relationship between real identity and virtual identity enacted through projective identity was somewhat confusing; how does projective identity differ from virtual? However, it led to the valuable conclusion that games give players a realistic image of a possible self. By showing that epistemic games transferred not just identity but “the collection of professional skills, knowledge, identity, values” (the epistemic frame), Shaffer extends the value of games beyond the game itself.

Shaffer defines a frame as the organizational rules and premises which exist partly in the mind of the players and partly in the structure of the game; the frame is like a pair of glasses that allows participants to filter solutions as irrelevant and leads to an increasingly accurate reflection-in-action. The epistemic frame is the “grammar” of the local culture of a community of practice, and is “what we get when we internalize the community and carry it with us”

Shaffer claims that epistemic frames are a level of description between and across the schema-based and community-based views; while this claim is not expanded, he does expand on the relationship between epistemic frames and community by noting the common qualities:

  • interpretive
  • stable
  • transient
  • generative
  • ubiquitous
  • epistemological

The distinction between simulations and games was instructive:

  • simulations do not have epistemic frames
  • games create a virtual world using a simulation
  • the epistemic frame “is a property of the communities we inhabit in and around that virtual world”
  • epistemic games create the epistemic frame of a community by recreating the process by which individuals develop that community

Conditions-based Theory

Ragan, Tillman J. and Smith, Patricia L. (2004) “Conditions Theory and Models for Designing Instruction.” In D. H. Jonassen (Ed.), Handbook of research on educational communications and technology. Mahwah, NJ: Lawrence Erlbaum Associates. 623-649.

The incredible value of this article is in so clearly summing up Gagnés work and relating it to other theories: learning outcomes vary across contents, contexts, and learners; distinctive cognitive processing demands can be supported by different methods, strategies, and conditions. An early discussion of the background for Gagné noted that instructional design effectiveness varied among rote learning, skill learning and problem solving; however, the authors express doubt in a hierarchy of skills (and report that aside from the intellectual category, Gagné later moved away from his original taxonomic chain).

Rule-using (intellectual) skills are stored in hierarchical structures: verbal learning stored as propositional networks or schemata; rules stored as “if…then” productions; problem-solving are interconnections of schemata and productions. Gagné differentiated problem-solving (and concept formation) from other types in that PBL does not include any portion of the solution in the problem itself. One of Gagné’s contributions was to tie external events or instruction to internal events of learning; the latter he suggested were most impacted by prior knowledge; manner of long-term encoding; and requirement for retrieval and transfer to new problems.

The article’s coverage of multiple additions to Gagne’s work was equally clear. Merrill’s Component Display Theory categorizes learning objectives as a performance level (remember, use, or find) and a content type (fact, concept, principle, or procedure). Five operations (based 4 memory structures: associative, episodic, image, and algorithmic) can be conducted on subject matter:

  1. identity (facts)
  2. inclusion (concepts)
  3. intersection (concepts)
  4. order (procedures)
  5. cause (principles)

Reigeluth’s Elaboration Theory proposes three structures: conceptual (parts, kinds, matrices); procedural (order, decision); and theoretical (descriptive, prescriptive). Smith and Ragan argue that a middle ground exists between instruction-supplied and learner-initiated events. Tennyson describes three storage processes (declarative, procedural, and conceptual) and three retrieval processes (differentiating, integrating, and creating). Declarative knowledge is stored as associative networks or schemata; procedural knowledge is related to intellectual skills; and contextual (is this the same as conceptual?) knowledge is related to problem-solving. Finally, Ellen Gagné contributes the idea that declarative knowledge can be represented by propositions, images, linear orderings, or schemata (composed of the first three, while procedural knowledge is represented as a production system.

After agreeing with the fundamental premises (of conditions-based theory, the article demonstrate the lack of a proven link between learning categories and external conditions:

  • competition may be superior when a task is simple, but cooperative goal structures are more effective in problem-solving
  • explicit organization affected achievement although sequence modification did not
  • punishment is more effective than reward for discrimination learning
  • introductory students benefited more from direct guidance while advanced students performed better with more opportunities for autonomy
  • novice learners need more explicit learning guidance in employing cognitive strategies

The call for additional research is apropos although the need for additional knowledge of the relationship between internal learner conditions and subsequent learning is complicated by the difficulty in determining those internal (private) conditions.

Direct(ing) instruction

I liked the idea in this chapter of Wiggins that direct instruction is only one aspect of causing learning, and that design is perhaps more important. I especially appreciated the amplification of uncovering as way to provide hierarchy; that seemed to tie in with Ellen Gagne’s network/system ideas. I expected Wiggins to extend the concept of “textbook as information tool” to Google; I see my kids using Google to look up facts (dangerous, but I see the value) which could be a valid and innovative approach if they relied on the Internet for facts to keep their minds free for big ideas (I doubt they actually do that–they are probably keeping their minds free for social activities). That would tie in with Rousseau’s observation that the (unlearned) child sees objects (facts) but not the relationships that link those; the linking requires experience. Google provides the facts; immersive problems would provide the linking experience.

I loved the very practical suggestion to pull statements out of textbooks and turn them into questions, but I found myself wanting examples of how to provide appropriate (not over) simplification. Two strategy-application pairings provided clarity: direct instruction with discrete knowledge that asks students to hear and answer (seems like S-R); constructivist methods with ill-defined problems (prone to misunderstanding) that asks students to reflect and extend. The third pairing–guided practice with revision–seemed like a separate concept that would work in either case. The same was true in the discussion on timing: direct instruction and facilitated instruction seem distinct types while performance applies to both. This was somewhat implied later in the admonition to, “use knowledge quickly”; whether it’s declarative or conceptual knowledge, learners should apply it as soon as possible.

The guidelines were excellent although I have to think how these can be applied in an online course:

  • Less talk
  • Less front-loading
  • Pre- and post-reflection
  • Use models

The established knowledge versus new knowledge chart made sense although I would have liked more explicit application to design. To some extent this was developed later in the chapter when the idea that factual knowledge (but only what’s necessary to get started) must be learned and then applied to a more complex (and conceptual) performance; then more facts are learned and applied to an increasingly authentic performance task. At this point, I expected Wiggins to draw the connection between factual mastery and automaticity. I disagree that direct instruction occurs only while learners perform and after they perform; it occurs before as well (it’s just that we can’t spend too much time up-front on direct instruction; the learners need to jump in quickly).

The techniques were useful although duplicative (at least in intent); the ones I found most useful were:

  • Summary
  • One-minute essay
  • Analogy prompt
  • Visual  representation
  • Misconception check

Small groups/worlds

I looked at the Pellegrino article again and still find it directly applicable to what I do in higher ed. His triad of curriculum (scope and sequence), instruction (the teaching) and assessment is right on the money (and ties this article closely to the Bates model). I also started to see common themes emerge:

1. students come with existing knowledge structures which are sometimes inaccurate (the Wiggins’ misperception idea);
2. students must have deep factual and procedural knowledge, understand those facts and procedures in the context of a conceptual framework, and then be able to retrieve and apply the facts and procedures from an organization structured within memory. Pellegrino states (note: check this out since as he doesn’t cite any research directly) that the ability to notice patterns (Wiggins) or draw analogies to other problems (Bloom) is “more closely intertwined with factual and procedural knowledge than was once believed.”
3. metacognition–basically an internal dialogue or reflection–teaches students to take control of their own learning by defining goals and monitoring their progress.

Pellegrino’s four goals of instruction resonated as well:

1. Design meaningful problems;
2. Build scaffolds to help students solve those problems;
3. Give students opportunities for practice using feedback, revision, and reflection activities; and
4. “Promote collaboration and distributed expertise, as well as independent learning.”

Pellegrino amplified this last point  by suggesting teachers have learners work in small groups on complex problems. I recently read an article about an experiment Robert Goldstone, a cognitive psychologist at Indiana conducted that suggested small groups with a few weak connections to other groups are ideal for solving complex problems; large groups with a lot of connections (aka Facebook and wikipedia, aka The Wisdom of Crowds) are best for solving simple problems. I wonder if this maps at all to Dunbar’s Number?

Interestingly, Pellegrino identified a key characteristic of technology-based environments as offering learner control, a point our class made several weeks ago during our discussion!

How do I remember? Let me count 3 ways.

I found the Gagné chapter pretty cool. I’d heard of the 9 events but didn’t realize the underpinnings of the 3 types of knowledge (in memory).

  1. Propositions are declarative and form into networks; they are composed of argument (general)-relation (narrower) pairs although it took me a while to “count” them correctly. What was interesting is that we remember them as ideas not as exact sentences–maybe because we take in the sentence and then adapt it to our schema based on our history. They are easier to acquire but slower to retrieve. Propositions are organized in hierarchies and underlie the ability to reproduce information.
  2. Productions are procedural and form into systems; they are composed of if (condition)-then (reaction) pairs and are more reactive with the environment. They are slower to acquire but faster to retrieve (automatic) because they don’t need to be brought back into short-term memory. Productions are organized into if-then pairs and underlie the ability to operate on information.
  3. Images are different from both and pack more information into a smaller space. Images are used to represent spatial information because of ST memory limits. Images are continuous (analog) while propositions (and procedures?) are discrete (digital).

Here are some things I questioned:

  • 45% correct if 2 ideas are in working memory at the same time vs. 35% if the 2 ideas are separated: doesn’t seem like a huge difference but is used to justify bringing recalled knowledge into short-term memory and immediately connecting it to new knowledge.
  • Declarative knowledge is useful for novel situations while procedural knowledge is important for familiar ones; this seems incongruous with Wiggins’ contention that PBL is best for new situations (or perhaps PBL builds declarative knowledge).
  • Images may be represented  in long-term memory as propositions or as images and propositions; they could be represented only as images (is there research on whether image recall is as fast as procedural recall?).