Figure 1418

A network representation of a declarative chunk from Anderson's ACT architecture. This chunk represents a piece of knowledge encoding the fact that 5 and 6 add up to 11.

Proceduralisation is the process that transforms declarative knowledge into production knowledge. Usually, problem solvers initially attempt to solve, say, a maths or programming problem, from a textbook. In these solution attempts, the novice will generate a number of subgoals using a combination of weak methods (like hill climbing or means-ends analysis) and declarative knowledge from instruction. During repeated problem-solving episodes, a particular piece of declarative knowledge will occur repeatedly in the context of a particular subgoal. When this happens, a new production rule is created that has the declarative knowledge as a pattern (its IF-part) and the executed action as its action (its THEN-part). This declarative-procedural change should result in a concurrent reduction in verbalisation by the problem solver. Correlatively, there is an increase in the automaticity of the problem-solving behaviour (see also Chapter 5). Reductions in verbalisation have been demonstrated repeatedly in the literature (Anderson, 1982; Sweller, 1983; Sweller, Mawer, & Ward, 1983).

Stated simply, Anderson's view of learning is based on the accrual and tuning of small units of knowledge —knowledge that combines to produce complex cognition. The environment plays a critical role in the learning process, in that it establishes the configuration of simple objects that aid the learning of chunks and also drives the formation of production rules. The importance of this step is that it re-emphasises the importance of analysing the nature of the environment as an essential step to understanding cognition, an emphasis that has been somewhat lost since the demise of behaviourism in the cognitive revolution (Anderson, 1990).

Learning from your mistakes

Finally, intuitively, we also learn from our mistakes. Most theories of skill learning stress the importance of successful problem solving to the learning process. However, we also learn from episodes in which we fail. Ohlsson (1996) has proposed a theory of skill learning from performance errors. In this theory, errors occur because people use knowledge that is overly general; their encoded knowledge does not capture a distinction that is in the task environment. So, novice chess players may have so general a conception of threatening board positions that they miss many situations when they are under attack. The theory also stresses the subjective nature of errors, characterising them as conflicts between what the learner believes ought to be true and what is perceived to be the case. The learning that occurs results in a specialisation of the knowledge structures being used, so that they come to be applied under more appropriate conditions in the future.

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