A strategy is a purposeful action, or sequence of actions, executed in the interest of achieving a goal. The mistaken idea that children do not exhibit strategies prior to school age arose from studies asking preschool and older children to remember a set of items (for review, see Pressley & Hilden, 2006). Preschoolers did no better in remembering the items than they did when merely asked to look at them. Older children asked to remember the items, in contrast, were likely to employ strategies, such as organization or rehearsal. But this finding did not mean that children do not use strategies until they are 7 or 8 years old. An infant who uses a stick to bring a toy within reach is employing a strategy to reach a goal. The important questions are what strategies is a child able to employ, what is the degree of conscious control under which strategies operate, does the child know to apply the strategy or can the child be taught when and how to do so, and can strategies be employed more effectively to aid performance.
Strategies are not autonomous, multi-purpose tools stored away in a toolkit and brought out and applied when needed. Most often, people are unable to say definitively that a child either has or lacks possession of a particular strategy. Instead, strategies are linked to the contexts in which they are employed and the goals they serve. A child may exhibit a strategy in one context and not in another seemingly equivalent one.
Children's memory may differ, for example, when asked to retrieve a list of items from a mock grocery store and when asked to memorize a list of words. Multiple factors, however, are likely to contribute to such differences (Weissberg & Paris, 1986). The use of deliberate strategies, such as rehearsal, is one factor, but additional possibilities need to be weighed. These include the differing goal (and hence motivational) structures linked to the tasks and the differing familiarity of the task materials and the task activity itself. Moreover, these different contributors themselves interact with one another. A powerful memory strategy, for example, is elaboration, in which an association is formed between separate entities by identifying a theme that links them (e.g., the digit sequence 312 is remembered as a telephone area code or a batting average). In order to make use of this strategy, however, the learner needs to be familiar with such content domains.
In classroom settings, teachers need to be sensitive to these contexts of strategy use. A strategy may appear in one context but not another. A child faced with multiplying three times five, for example, may use a successive-addition strategy of laying out three groups of five objects and adding them. When the child later encounters the problem five times three, however, the child may be unable to apply the same strategy. The most common challenge teachers encounter is that students fail to apply a strategy that has been taught explicitly in one context when they later encounter problems for which it is appropriate. Simply learning how to execute the strategy is not enough.
Identifying what strategies a student is using can be difficult. Mental strategies most often are not detectable from overt performance. Asking people how they performed a task or solved a problem is one way of gaining information about strategy use, but not always a reliable one. How someone reports having solved a problem may not be identical or even similar to the mental operations that were actually performed to reach a solution. Asking the person to think aloud while engaged in the task is a better method, but it too can be misleading, because the think-aloud talk can disrupt or otherwise alter performance.
Mostly, cognitive psychologists must employ indirect methods in making inferences about strategy use, for example, by examining performance over different kinds of problems and observing response times or patterns of correctness as a way of testing hypotheses about the strategies the performer used. Nonverbal behavior (such as visual fixation patterns and gesture) may also be informative.
Teachers are in effect researchers-in-practice in the classroom, as they seek to diagnose the strategies that individual students apply to their work. They do best to treat their interpretations as hypotheses and then seek multiple kinds of evidence—by talking to the child about what he is doing as well as observing his work on different kinds of problems—that will either support or dis-confirm such hypotheses. Teachers also need to be sensitive to two kinds of variation. One is the wide individual variation across children in how they approach a problem. Children of similar age and ability within a single classroom are likely to exhibit quite different strategies for the same task, including some that even the teacher may not have previously considered. The other kind of variation, discussed below, is variation in strategy usage within a single child.
Adding to the assessment challenge, strategies must always be considered in relation to a task, a goal, and a situation. Still another challenge comes from the need to consider any strategy in a context of its alternatives. One of the major discoveries psychologists have made about strategies is that multiple alternative strategies applicable to a task typically exist in a learner's repertory. These strategies are of differing degrees of correctness or effectiveness. They also have different probabilities of application (see Figure 1). The instructional goal, then, is to reduce the strength, that is, probability of occurrence, of less effective strategies and increase the strength of more effective ones. New strategies do, of course, appear, but first emergence rarely indicates the beginning of consistent usage. The majority of change is thus of this
shifting-frequency variety. Siegler (2000) proposes an “overlapping waves” model to portray this process. A particular less-than-ideal strategy initially appears infrequently, begins to increase in frequency, enjoys a period of ascendance, and then diminishes in frequency, while another strategy follows this same course but at a later, although overlapping, time. Siegler and his colleagues tracked the course of various strategies children use in performing simple single-digit addition and subtraction problems. When faced with adding nine plus three, a first-grade child may first count one subset, then the other, and then the entire set, to produce the answer, twelve—an unnecessarily burdensome and inefficient strategy. Asked to carry out a series of such calculations, the child may after a time discover a more efficient strategy—which Siegler calls the Min strategy—which involves simply counting up from the first addend, i.e., “ten, eleven, twelve,” and requires enumerating only the second subset. Students may use these two (and several other) strategies as they tackle a set of problems. Over time, however, use of the less efficient strategy diminishes in frequency and use of the more efficient strategy increases.
What is entailed in this change process? Microge-netic studies (Kuhn, 1995; Siegler, 2006), in which an individual is observed engaged in the same or a similar set of problems over an extended period of weeks or months, show that the exercise afforded by this rich problem environment is sufficient to induce strategy change in a majority of cases, enabling researchers to examine its characteristics. One point that has become clear is that two distinct components are involved. The more familiar is the desired increasing strength of the more advanced strategy or strategies. But equally important is inhibition of less advanced strategies. In postulating mechanisms, Siegler (2000, 2006; Siegler & Jenkins, 1989) emphasized the need for associations with the more frequent, less effective strategies to be weakened, as well as associations with more effective strategies strengthened.
Consistent with such a model is the finding that strategies when they first appear may not be used effectively enough to enhance performance. Researchers studying the development of memory strategies have in fact found this to be the case, giving rise to what has been called a utilization deficiency. A strategy such as categorization (of the to-be-remembered items), for example, even (or especially) if it has been explicitly taught, may not be used when a child later is free to approach a memory task as the child chooses, or, if it is used, may fail to improve or even diminish performance. The educational implication is that new strategies must be included in the repertory with sufficient frequency so as to allow them to be practiced, consolidated, and perfected until the user is able to experience their utility.
While similarly emphasizing the relinquishment of less effective strategies as a more formidable obstacle than strengthening new ones, Kuhn and colleagues (Kuhn, 2001; Kuhn & Dean, 2004) proposed that knowledge at a meta-level is as important as that at the performance level and plays a major role in what happens there. The meta-level entails understanding of strategies—recognizing what they do or do not buy one—in relation to task goals. Portrayed in the right side of Figure 1 (Kuhn, 2001) are the strategies that co-exist and are available for use (analogous to Siegler's “overlapping waves” model). In the progress depicted from the upper to the lower half of the diagram in Figure 1, the less effective strategies to the left become less frequent and the more effective strategies to the right more frequent (in this case, yielding a temporary, transitional result of all strategies of roughly equal strategy). Implicated in this change are the meta-level operators that appear in the center of the diagram, representing the individual's understanding of the task goal, understanding of the strategies the individual has available to apply, and awareness of the need to coordinate the two in selecting a strategy. Feedback from the performance level should enhance meta-level understanding, further enhancing performance, in a continuous process.
Kuhn and colleagues have made use of this model in research on the scientific thinking of children and adults, in particular how they coordinate their own preexisting beliefs with new evidence and draw conclusions about the causal roles of various factors in producing an outcome. Even many adults have difficulty bracketing, that is, holding in suspension, their own beliefs in interpreting new evidence. Community college students, for example, were presented data regarding an experiment conducted by a school district on ways to improve reading instruction (Kuhn, Katz, & Dean, 2004). Three factors were investigated: a new reading curriculum, teacher aides, and reduced class size. Among six outcomes students were asked to examine were these two:
- Classrooms with the new reading curriculum and teacher aides reported an outcome of greatly improved.
- Classrooms with the new reading curriculum, teacher aides, and reduced class size reported an outcome of greatly improved.
Application of a control of variables strategy (in which all variables but the one being investigated are held constant) would dictate the conclusion that reduced class size played no role in the outcome.
Although some students did apply this strategy and come to the appropriate conclusion, a good number did not. One common response reflected the inference strategy that anything present in the context played a role in the outcome. For example, in one student's words: “Yes (class size makes a difference) because this class had it and they improved.”
Other students, despite explicit instructions to interpret the presented data, ignored it and relied on their own preexisting knowledge, leading them to offer responses like this one: “Yes (class size makes a difference) because the numbers of children are small so they can learn faster and better.”
To apply the more advanced, scientifically correct strategy individuals need to have good metastrategic control over their own thinking. In a problem like this one, this control makes it possible to monitor and manage the dual representations of the evidence and one's own knowledge state, as well as the cognitive strategies that are involved in coordinating them.
How can teachers promote strategy development? The evidence suggests that a rich problem environment, in which students are given frequent and dense opportunities to engage problems requiring more advanced strategies will in a majority of cases lead to improvement in strategy use (Kuhn et al., 1995; Dean & Kuhn, 2007). Teachers can assist by supporting students' inclinations to take charge of their own learning. This points leads back to the contextual message with which this discussion began. If students develop their own firm understandings of what they are undertaking to learn in a particular situation and why, they are more likely to take charge of finding the most effective ways to enable them to accomplish the job (Kuhn, 2005). This meta-level awareness and management in turn enhances the likelihood of transfer of strategies to new contexts.
The directions in which individual development progresses are consistent with the growing metastrategic capabilities that older children begin to display (Kuhn & Franklin, 2006). Older children and adolescents are less pliable than young children. They are more likely to question, and they want to try things their way. Expressed differently, they want to assume control of what they do. Growing cognitive and social skills make them more able to do so, and the indications are that in academic settings teachers should give them the space to try their own approaches to problems, to collaborate with others and to revise their strategies as warranted, and to gain from the experience that doing so affords.
Dean, D., & Kuhn, D. (2007). Direct instruction vs. discovery: The long view. Science Education, 91, 384–397.
Kuhn, D. (2001). Why development does (and doesn't) occur: Evidence from the domain of inductive reasoning. In R. Siegler & J. McClelland (Eds.), Mechanisms of cognitive development: Neural and behavioral perspectives. Mahwah, NJ: Erlbaum.
Kuhn, D. (2005). Education for thinking. Cambridge, MA: Harvard University Press.
Kuhn, D., & Dean, D. (2004). Metacognition as a conceptual bridge between cognitive psychology and educational practice. Theory into Practice, 43, 268–273.
Kuhn, D., & Franklin, S. (2006). The second decade: What develops (and how)? In W. Damon & R. Lerner (Series Eds.) & D. Kuhn & R. Siegler (Eds.), Handbook of Child Psychology: Vol. 2. Cognition, Perception, and Language (6th ed.). Hoboken, NJ: Wiley.
Kuhn, D., Katz, J., & Dean, D. (2004). Developing reason. Thinking and Reasoning, 10. 197–219.
Siegler, R. S. (2000). The rebirth of children's learning. Child Development, 71, 26–35.
Siegler, R. S. (2006). Microgenetic studies of learning. In W. Damon & R. Lerner (Series Eds.) & D. Kuhn & R. Siegler (Eds.), Handbook of Child Psychology: Vol. 2. Cognition, Perception, and Language (6th ed.). Hoboken, NJ: Wiley.
Siegler, R. S., & Jenkins, E. A. (1989). How children discover new strategies. Hillsdale, NJ: Erlbaum.
Weissberg, J., & Paris, S. (1986). Young children's remembering in different contexts. Child Development, 57, 1123–1129.
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