Proceedings of the Annual Meeting of the Cognitive Science Society

Information-processing models for comprehension typically regard text as the depository of a single determinate meaning, placed in it by the writer. Conversely, a reader-based approach views meaning as constituted by the interactions between an individual and a text. From a computational standpoint, reader-based understanding suggests abandoning models which depend on a priori rules of interpretation and limiting the design of an algorithm to the quantitative aspects of text comprehension. I propose that the perception of subject matter be viewed as a race process where the generation of bridging inferences and expectations is partly controlled by quantitative factors (such as the delay for memory retrieval) which emphasize the invisible but omnipresent role of time during reading.