The role of knowledge in discourse comprehension: A construction-integration model.

Abstract

In contrast to expectation-based, predictive views of discourse comprehension, a model is developed in which the initial processing is strictly bottom-up. Word meanings are activated, propositions are formed, and inferences and elaborations are produced without regard to the discourse context. However, a network of interrelated items is created in this manner, which can be integrated into a coherent structure through a spreading activation process. Data concerning the time course of word identification in a discourse context are examined. A simulation of arithmetic word-problem under-standing provides a plausible account for some well-known phenomena in this area. Discourse comprehension, from the viewpoint of a computa-tional theory, involves constructing a representation of a dis-course upon which various computations can be performed, the outcomes of which are commonly taken as evidence for com-prehension. Thus, after comprehending a text, one might rea-sonably expect to be able to answer questions about it, recall or summarize it, verify statements about it, paraphrase it, and SO on.