Effectiveness of Positive Hypothesis Testing in Inductive and Deductive Rule Learning.

Abstract

In a positive hypothesis test a person generates or examines evidence that is expected to have the property of interest if the hypothesis is correct, whereas in a negative hypothesis test a person generates or examines evidence that is not expected to have the property of interest if the hypothesis is correct. Two experiments assessed the effectiveness of positive versus negative hypothesis tests on inductive and deductive rule learning problems. In Experiment 1 problem solvers induced a rule by proposing hypotheses and selecting evidence in the eight conditions of a factorial design defined by instructions to use a positive or negative hypothesis test on each of trials 1-5, 6-10, and 11-15. Instructions to use positive tests resulted in more examples, fewer strategic hypotheses, and a higher weighted score for five types of hypotheses than instructions to use negative tests. In Experiment 2 problem solvers identified 1 of a possible 1296 correct rules in the deductive rule learning game Mastermind. When problems were classified in the 16 possible combinations of positive or negative hypothesis tests on trials 2, 3, 4, and 5 there were fewer trials to solution for positive tests on each of the four trials and fewer trials to solution with increasing positive tests. We conclude that positive hypothesis tests are generally more effective than negative hypothesis tests in both inductive and deductive rule learning. Copyright 1999 Academic Press.