How sentences from a discourse are recognized or verified can be explained by combining theories of item recognition derived from list-learning experiments with hypotheses about the representation of text in memory within the framework of the construction-integration model of discourse comprehension. The implications of such a theory of sentence recognition are worked out for two experimental situations. In the first experiment, subjects read brief texts and were then tested for recognition with verbatim old sentences, paraphrases, inferences, and contextually related and unrelated new distractor sentences after delays from 0 to 4 days. Differential decay rates for the wording and meaning of the text and for situational information were observed. The theory provides a good quantitative account of the data. In the second experiment, the speed-accuracy trade-off in sentence verification for two subject groups with different prior knowledge was studied for old verbatim sentences and inferences. Qualitative predictions derived from the theory with the parameter estimates from the first study were in agreement with the data. Readers without an adequate situational understanding (novices) were found to make quick judgments based on surface and textbase characteristics of the test sentences, while experts in addition utilized their situation model successfully, which required more processing time. © 1990 Academic Press, inc.A large number of experiments on recognition memory exist for lists of words or pictures. Several models of recognition memory are available today which account very well for most of the phenomena observed in these experiments. Can these theories also account for experimental data when the materials used are not lists of items, but coherent discourse? By combining the essential features of current models of recognition memory developed for list- learning studies with a model of discourse comprehension and assumptions about the representation of discourse in memory, a model of sentence recognition and sentence verification can be obtained that accounts for major features of sentence-recognition data. Thus, we do not propose developing a new model for sentence memory. Instead, we shall combine existing models of listlearning and text-comprehension processes to derive a theoretical analysis of sentence recognition and verification.We begin by comparing three current models of item recognition (Gillund & Shiffrin, 1984;Hintzman, 1988;Murdock, 1982) and determine their common essential features, to be used for modelling sentence memory. We will then review some notions

No abstract

No abstract

No abstract