Chapter Summary

In this chapter, we have considered several aspects of skilled thinking. The emphasis in this chapter has been on the role that various forms of specific knowledge play in problem solving.

• The Gestalt school argued in opposition to associationist psychologists that thinking was productive rather than merely reproductive. They performed many experiments to demonstrate that problem solving could be productively successful and reproductively a failure; making use of concepts like insight, restructuring, and fixation.

• Newell and Simon's (1972) problem-space theory emerged from the information-processing revolution. At bases it characterises problem solving as a constrained and guided search through a space of alternative mental possibilities. This search is guided by various heuristic methods or rules of thumb that co-ordinate the application of various operators (moves) used for transforming one state into another. This theory has been used successfully to predict problemsolving behaviour in puzzle problems, like the Tower of Hanoi, the missionaries-cannibals problem, and water-jug problems. Computational models have been constructed for many of these problems that simulate subjects' behaviour.

• From an evaluative standpoint, the strength of the problem-space approach has been its predictive success, but its main weakness has been the narrowness of the problem situations to which it has been applied. Fortunately, later research has widened the scope of the theory.

• Problem-space theory has been extended to re-interpret the findings of the Gastalt school. Some puzzles, like the Luchins' water-jugs problems, can be dealt with quite directly using problemspace theory. Other problems, like the two-string problem and the candle problem, have required some extension of the theory to characterise notions like insight, restructuring, and fixation.

• Chess expertise appears to depend on knowledge about specific board positions, about how to evaluate such positions, and schemas encoding types of board position. Expert players have more of this knowledge than novices and this accumulated wisdom is manifest in the speed with which they can encode board positions (normal or random) and how they treat such positions.

• In physics, expertise again depends on schemata that encode the important theorems in the discipline. There are also strategic differences in the way expert physicists deploy this knowledge, working forward from a problem statement to a solution rather than backwards from a solution to the givens in the problem statement.

• In programming, people develop schemata that encode programming plans depending on the specific programming language they are learning. These domain-specific plans can sometimes conflict with existing plans about how we do things in the world and may be transferred to be applied in learning a second programming language.

• Overall, expertise research has been a successful research area. It has developed many specific accounts of important thinking skills, which have been used in education. It has also delivered a consistent story that fits in well with accounts of other thinking behaviour and which can be captured readily in several cognitive architectures.

• Novices learn to be experts by forming chunks of knowledge, by developing declarative knowledge, and moving from declarative to procedural knowledge. The ACT theory is an integrated cognitive architecture that has been used to simulate these types of learning.

• Until recently, cognitive neuropsychological accounts of thinking behaviour were not well developed (see Eysenck & Keane, 1995). However, considerable advances have been made in localising various types of thinking in the prefrontal cortex. The current suggestion is that several regions in this area are responsible for the fundamental task of integrating complex relational information, a process that is basic to all higher thought processes.

Business Correspondence

Business Correspondence

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