Effective Heuristics for Hypothesis Testing : An Empirical Discussion Using a Computer Simulation Method

抄録

Hypothesis testing processes have been studied for several decades in the psychology of science. Previous studies suggent that a strategy to collect data which conforms to one's current hypothesis (i.e., positive strategy) is useful for successful hypothesis testing in many situations that people face in scientific learning. It was also suggested that entertaining alternative hypotheses is useful for successful hypothesis testing. In order to inventigate the effectiveness of these strategies, we used a production system model that can solve the Wason's 2-4-6 task, and executed many simulations in which the parameters of the model were systematically varied. It is assumed that this approach compensates for the limitations of psychological experimentation. The summary of the simulations is as follows : The positive test strategy works well when the terget concept is specific. On the other hand, it prevents subjects from finding a correct target when the target concept is general. Diagnostic test strategy (i.e., entertaining alternative hypotheses and producing instances which distinguish the competing hypotheses) is always effective for finding a correct concept.