Predicting propositional logic inferences in text comprehension

Abstract

Three experiments investigated whether the propositional logic reasoning model of Braine, Reiser, and Rumain (1984) can account for propositional logic inferences made in text comprehension. The operative part of the model consists of a set of inference schemas together with a routine for using them to draw inferences. In Experiment 1 subjects read stories and performed two tasks: the first asked them to indicate whether a final sentence made sense in the context of the story; the second asked them whether a piece of information was presented in the story or needed to be inferred. In Experiment 2 we omitted the first task and replicated the second task. Results showed that (a) subjects had no difficulty making the inferences necessary to judge the sensibleness of the final sentence and (b) subjects often believed that information derived from model-predicted inferences had been presented to them in the story, although subjects rarely believed that information derived from other logically valid inferences had been presented in the text. In Experiment 3 subjects were presented with abstract versions of the logical form of the stories and were asked to write whatever follows from the premises. It turned out that the inferences that subjects think follow from only the meaning of the logical particles correspond closely to the ones that they draw reading the stories, and both are well predicted by the model investigated. We argue that any complete account of the inferences people make in discourse comprehension must include some propositional logic inferences, and, more particularly, that the inference-schema model we examined provides a precise starting hypothesis about the propositional logic inference generator used in text comprehension.