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Creativity understending innovation in problem solving science invention and the arts - Weisberg R.W.

Weisberg R.W. Creativity understending innovation in problem solving science invention and the arts - Wiley & sons , 2006. - 641 p.
ISBN-10: 0-471-73999-5
Download (direct link): understandinginnovation2006.pdf
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318
The Question of Insight in Problem Solving
friend may occasionally catch each other in contradictions as each tries to explain the policies of a favored candidate. One of you may ask, “How will your candidate be able to carry out all those new policies and still reduce taxes? Isn’t there a contradiction there?”
Thus, one can understand Abbott’s ostensible leap of insight as an example of the analytic process of realizing that something is impossible; the suddenness of that realization brought with it an Aha! experience. Perkins concluded that it was not necessary to assume that leaps of insight are brought about by anything beyond what we can call ordinary analytic thought processes. Sometimes we use reasoning in order to work out the consequences of some state of affairs, and other times we can realize the consequences directly, without reasoning anything out. As a parallel situation, Perkins points to our understanding of jokes: Sometimes we get a joke directly, as we hear the punch line, whereas other times we have to have the logic of the joke explained to us. Getting a joke as we hear it involves realization of the same sort that plays a role in leaps of insight. Perkins’s findings and theorizing present a challenge for the Gestalt view that solutions to insight problems are brought about through a mechanism that is basically different from that involved in more ordinary analytical thinking, because he demonstrated that the insights involved in problem solving might be the result of small analytic steps rather than large perceptually based leaps.
More recently, Perkins (e.g., 2000) seems to have changed his perspective on the thinking processes involved in achieving insight as indexed by solution of insight problems. He has proposed that analytic problems are “reasonable” problems, since they can be solved through reasoning and other analytic methods. Insight problems, in contrast, are “unreasonable,” because they cannot be solved using conventional reasoning. One must, in Perkins’s view, approach such problems (and, presumably, real-world situations that demand insight) using “breakthrough” thought processes, those that can deal with the unique structure of insight problems. Details of Perkins’s analysis are presented in Perkins (2000).
It is also noteworthy that the participants who provided the protocols in Table 6.4 were able to solve the Antique Coin problem without reaching an impasse and without restructuring the problem. This result can make us sensitive to the need for detailed analysis of a problem situation before we draw firm conclusions about the underlying cognitive processes. If a researcher had based an analysis of the Antique Coin problem on the presence or absence of an Aha! experience (using Metcalfe’s [1987] feeling-of-warmth ratings, say), he or she would have concluded, ipso facto, that Abbott solved the problem through restructuring and that analysis was not involved. However, more detailed examination of the information avail-
319
Creativity: Understanding Innovation
able in the protocols indicates that such a conclusion would be mistaken. Thus, any inferences that one draws concerning processes underlying the solution of problems depend critically on the sensitivity of the measures one has used to assess performance. In order to conclude, for example, that restructuring has occurred during solution of a problem, it is necessary to go beyond simply measuring time to solve the problem and even, as we have just seen, measuring the presence or absence of an Aha! experience. Weisberg (1995) has discussed in more detail the difficulty of determining the processes involved in solving a given problem, as well as the related difficulty of determining whether a given problem is solved through insight or analysis.
Further Evidence for Analytic-Based Solution of Insight Problems
In support of Perkins (1981), Fleck and Weisberg (2006) provided additional evidence that insight problems—specifically, the Triangle problem (Figure 6.1D)—can be solved through application of weak methods, without restructuring. A large majority of participants tested by Fleck and Weisberg solved the problem, often through one of two types of heuristically based analysis. Some solved it through numerical analysis, saying something like this: “The rows now have four, three, two, and one coins. How can I change it so that they will have one, two, three, and four? I can’t move three coins from the top row, because that will not produce what I need. Maybe I can move two coins from the top, but where should they go? The row with two coins could take two more. . . .” This line of reasoning resulted in several solutions. These people were using logical analysis to try to deduce the solution from the information given in the problem, combined with a hill-climbing strategy, in which they tried to change the current problem state into one that was closer in appearance to the goal.
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