A new tool for measuring and understanding individual differences in the component processes of reading comprehension.

Brenda Ann Marie Hannon, Meredyth Daneman·2001·Journal of Educational Psychology

Abstract

grantor: University of Toronto

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  3. Working memory, short-term memory, and general fluid intelligence: A latent-variable approach.
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Cited by (6)

  1. Children's Reading Comprehension Ability: Concurrent Prediction by Working Memory, Verbal Ability, and Component Skills.
    Cain, Kate, Oakhill, Jane, Bryant, Peter · 2004 · Journal of Educational Psychology
  2. Why does working memory capacity predict variation in reading comprehension? On the influence of mind wandering and executive attention.
    McVay, Jennifer C., Kane, Michael J. · 2012 · Journal of Experimental Psychology: General
  3. A meta-analysis on the relation between reading and working memory
    Peng, Peng, Barnes, Marcia, Wang, CuiCui, Wang, Wei, Li, Shan, Swanson, H. Lee, Dardick, William, Tao, Sha · 2018 · Psychological Bulletin
  4. Prior knowledge, reading skill, and text cohesion in the comprehension of science texts
    Ozuru, Yasuhiro, Dempsey, Kyle, McNamara, Danielle S. · 2009 · Learning and Instruction
  5. Diagnosis and Treatment of Reading Disabilities Based on the Component Model of Reading: An Alternative to the Discrepancy Model of LD
    Aaron, P.G., Joshi, R. Malatesha, Gooden, Regina, Bentum, Kwesi E. · 2008 · Journal of Learning Disabilities

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This page
CoChat. (2026). Citation check: A new tool for measuring and understanding individual differences in the component processes of reading comprehension. https://app.cochat.ai/papers/10.1037//0022-0663.93.1.103
The paper
Hannon, B. A. M., & Daneman, M. (2001). A new tool for measuring and understanding individual differences in the component processes of reading comprehension. Journal of Educational Psychology. https://doi.org/10.1037//0022-0663.93.1.103

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.