Abstract
The complexity of text comprehension demands a computational approach to describe the cognitive processes involved. In this article, we present the computational implementation of the landscape model of reading. This model captures both on-line comprehension processes during reading and the off-line memory representation after reading is completed, incorporating both memory-based and coherence-based mechanisms of comprehension. The overall architecture and specific parameters of the program are described, and a running example is provided. Several studies comparing computational and behavioral data indicate that the implemented model is able to account for cycle-by-cycle comprehension processes and memory for a variety of text types and reading situations.
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This project was supported by Grants SC-91-2413-H-194-022 and NSC-92-2413-H-194-026 from the National Science Council of Taiwan to Y.T., by a Golestan fellowship from the Netherlands Institute for Advanced Study in the Humanities and Social Sciences to P.v.d.B., by a Robert and Corrie Beck Fellowship from the College of Education and Human Development at the University of Minnesota to P.K., and by the Center for Cognitive Sciences at the University of Minnesota through Grant HD-07151 from the National Institute of Child Health and Human Development. We thank Eric-Jan Wagenmakers and two anonymous reviewers for their comments on an earlier version of this article.
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Tzeng, Y., van den Broek, P., Kendeou, P. et al. The computational implementation of the landscape model: Modeling inferential processes and memory representations of text comprehension. Behavior Research Methods 37, 277–286 (2005). https://doi.org/10.3758/BF03192695
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DOI: https://doi.org/10.3758/BF03192695