journal article Jun 28, 2021

The Contribution of Text Characteristics to Reading Comprehension: Investigating the Influence of Text Emotionality

Reading Research Quarterly Vol. 57 No. 2 pp. 649-667 · Wiley
Abstract
ABSTRACTIn the current study, we examined relations between text features (e.g., word concreteness, referential cohesion) and reading comprehension using multilevel logistic models. The sample was 158 native English‐speaking students between 8 years, 8 months and 11 years, 2 months of age with a wide range of reading ability. In line with the simple view of reading, decoding ability and language comprehension were associated with reading comprehension performance. Text characteristics, including indices of word frequency, number of pronouns, word concreteness, and deep cohesion, also predicted unique variance in reading comprehension performance over and above the simple view’s components. Additionally, the emotional charge of text (i.e., lexical ratings of arousal) predicted reading comprehension beyond traditional person‐level and text‐based characteristics. These findings add to a small but growing body of evidence suggesting that it is important to consider emotional charge in addition to person‐level and text‐based characteristics to better understand reading comprehension performance.
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References
130
[2]
Mixed-effects modeling with crossed random effects for subjects and items

R.H. Baayen, D.J. Davidson, D.M. Bates

Journal of Memory and Language 10.1016/j.jml.2007.12.005
[5]
Barnes M.A. (1996)
[8]
Modeling Local Coherence: An Entity-Based Approach

Regina Barzilay, Mirella Lapata

Computational Linguistics 10.1162/coli.2008.34.1.1
[9]
Bates D. Maechler M. Bolker B. &Walker S.(2015).lme4: Linear mixed‐effects models using ‘Eigen’ and S4 (R package version 1.1‐7) [Computer software]. Retrieved fromhttps://CRAN.R‐project.org/package=lme4
[10]
Bates D. Maechler M. &Dai B.(2008).lme4: Linear mixed‐effects models using S4 classes (R package version 0.999375‐28) [Computer software]. Retrieved fromhttps://CRAN.R‐project.org/package=lme4
[13]
Biber D. (2001)
[15]
Bourg T. (1996)
[16]
Bradley M.M. (1999)
[34]
Activation of Background Knowledge for Inference Making: Effects on Reading Comprehension

Carsten Elbro, Ida Buch-Iversen

Scientific Studies of Reading 10.1080/10888438.2013.774005
[35]
The role of coherence and cohesion in text comprehension: an event-related fMRI study

Evelyn C. Ferstl, D.Yves von Cramon

Cognitive Brain Research 10.1016/s0926-6410(01)00007-6
[42]
Gernsbacher M.A. (1997)
[45]
Gernsbacher M.A. (1996)
[47]
Grounding language in action

Arthur M. Glenberg, Michael P. Kaschak

Psychonomic Bulletin & Review 10.3758/bf03196313
[49]
Coh-Metrix: Analysis of text on cohesion and language

Arthur C. Graesser, Danielle S. McNamara, Max M. Louwerse et al.

Behavior Research Methods, Instruments, & Comp... 10.3758/bf03195564

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References
Details
Published
Jun 28, 2021
Vol/Issue
57(2)
Pages
649-667
License
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Funding
Eunice Kennedy Shriver National Institute of Child Health and Human Development Award: 3RO1 HD044073‐14S1
Cite This Article
Sage E. Pickren, Maria Stacy, Stephanie N. Del Tufo, et al. (2021). The Contribution of Text Characteristics to Reading Comprehension: Investigating the Influence of Text Emotionality. Reading Research Quarterly, 57(2), 649-667. https://doi.org/10.1002/rrq.431