Proceedings of the Annual Meeting of the Cognitive Science Society

Dual space models of problem solving (e.g., Simon & Lea, 1974; Klahr & Dunbar, 1988) assume that the problem space for a task consists of two spaces: an hypothesis space and an experiment space. In hypothesis space, hypotheses about rules governing the task are generated, which can then be tested in experiment space. However, experiment space can be searched by applying the operators even without knowledge about the task. W e predicted that people searching hypothesis space would learn more about the task. To test this claim, two experiments were performed in which subjects had to learn to control a system consisting of three input variables that had unknown links to three output variables. Subjects first explored the task, then they had to reach goal states for the output variables. In both experiments subjects were presented with an hypothesis about one of the links, which should foster search of hypothesis space. In Experiment 1, hypothesis instruction improved performance and we showed that it had a similar effect to a manipulation of goal specificity, suggesting that both factors improve learning by encouraging search in hypothesis space. In Experiment 2 subjects were given a correct hypothesis or an incorrect hypothesis. Both groups performed better than an appropriate control. Thus instructions that encourage hypothesis testing appear to improve learning in problem solving.