Predicting Expository Text Processing

In this investigation, we examine the contribution of intrinsic content density (ICD) to measures of expository text processing. In Studies 1 and 2, the factor structure of select text density metrics was examined and refined using two text samples (Ns = 150) randomly selected from an expository text corpus. Scores on the ICD measure based on the entire text sample (N = 300) explained unique variance in readability and text easability. In Study 3, ICD predicted adults’ text ratings of interest and ease of comprehension above and beyond established easability measures. Participants’ text familiarity moderated the relation between ICD and ease of comprehension, revealing a density-facilitative effect for participants more familiar with the text content. Finally, in Study 4, measures of text difficulty, processing, and comprehension were obtained from adult readers using 10 researcher-constructed science texts; evidence of descriptive density effects on each measure was obtained. Implications for future research are discussed.

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Work Title Predicting Expository Text Processing
Subtitle Causal Content Density as a Critical Expository Text Metric
Access
Open Access
Creators
  1. D. Jake Follmer
  2. Ping Li
  3. Roy Clariana
License In Copyright (Rights Reserved)
Work Type Article
Publisher
  1. Reading Psychology
Publication Date May 17, 2021
Publisher Identifier (DOI)
  1. https://doi.org/10.1080/02702711.2021.1912867
Deposited November 16, 2021

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