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Updated: Mar 18, 2026

Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding
Published on: October 11, 2018
A computational modeling of semantic knowledge in reading comprehension: Integrating the landscape model with latent
Menahem Yeari1,2, Paul van den Broek3
1Bar Ilan University, Ramat-Gan, Israel. Menahem.Yeari@biu.ac.il.
Abstract:
It is a well-accepted view that the prior semantic (general) knowledge that readers possess plays a central role in reading comprehension. Nevertheless, computational models of reading comprehension have not integrated the simulation of semantic knowledge and online comprehension processes under a unified mathematical algorithm. The present article introduces a computational model that integrates the landscape model of comprehension processes with latent semantic analysis representation of semantic knowledge. In three sets of simulations of previous behavioral findings, the integrated model successfully simulated the activation and attenuation of predictive and bridging inferences during reading, as well as centrality estimations and recall of textual information after reading. Analyses of the computational results revealed new theoretical insights regarding the underlying mechanisms of the various comprehension phenomena.
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