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    Home»Science»Study Challenges a Decades-Old Belief About Why Children Struggle To Read
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    Study Challenges a Decades-Old Belief About Why Children Struggle To Read

    By Ryan McCullar, Texas A&M University College of Education and Human DevelopmentSeptember 1, 2026No Comments3 Mins Read
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    A large analysis of children’s cognitive and reading skills is challenging familiar assumptions about what makes someone a strong reader. Credit: Shutterstock

    New research shows children’s reading ability is driven more by auditory processing and comprehension-knowledge than by intelligence or visual skills.

    For decades, people have largely explained children’s reading struggles the same way. Strong readers were seen as naturally intelligent, while children who had difficulty reading were often viewed as less capable. Many also assumed that reading problems stemmed from the way children visually process words on a page. Under this view, reading success depended mostly on intelligence and visual skills.

    Dr. Daniel Hajovsky, an associate professor in Texas A&M University’s Department of Educational Psychology, led one of the largest studies ever conducted on the link between cognitive abilities and reading. Collaborating with researchers from the University of Kansas, St. John’s University, Montclair State University, and Temple University, Hajovsky examined which mental skills most strongly influence how children learn to read and where those processes may fail.

    The researchers combined 50,000 correlations from 137 cognitive and academic testing batteries into one large analytical model. This allowed them to identify how much individual cognitive abilities contribute to reading and helped explain why earlier studies often reached conflicting conclusions about what drives reading success.

    Study Challenges Long-Held Beliefs About Reading Ability

    The findings challenge several long-standing assumptions. Across the analysis, visual processing showed no meaningful connection to reading ability. General intelligence still played a role, but its influence was much smaller than many previous studies suggested. Instead, the strongest predictors of reading success were abilities that are rarely emphasized in public discussions about reading.

    “One notable finding was that general intelligence was less dominant than in some earlier meta-analyses,” Hajovsky said. “Broad abilities such as comprehension-knowledge and auditory processing played strong, specific roles in reading beyond general intelligence, especially for decoding and comprehension.”

    Auditory processing refers to the ability to hear and separate individual sounds within words. Comprehension knowledge reflects a child’s vocabulary, background knowledge, and understanding of the world. Together, these abilities predicted reading performance more consistently than any other factors measured in the study. Memory, reasoning, and mental processing speed also contributed in important ways.

    Building Reading Skills Through Support and Practice

    The results may help educators better identify the source of a child’s reading difficulties. Different reading challenges often stem from different underlying skills, and the study highlights those connections more clearly.

    For parents, the research suggests that even small efforts at home can support reading development. A child struggling with reading is rarely incapable of learning to read.

    “Strengthening foundational skills at home, even the ones that seem simple, can have meaningful effects on more advanced reading abilities,” Hajovsky said. “Struggles in reading are not a sign of low ability but often reflect one specific skill that needs strengthening within a larger system that works together.”

    According to Hajovsky, children achieve the best reading outcomes when schools, families, and communities support reading development as an interconnected process that builds gradually over time.

    Reference: “Toward a Consensus Model of Cognitive–Reading Achievement Relations Using Meta-Structural Equation Modeling” by Daniel B. Hajovsky, Christopher R. Niileksela, Dawn P. Flanagan, Vincent C. Alfonso, William Joel Schneider and Jacob Robbins, 15 August 2025, Journal of Intelligence.
    DOI: 10.3390/jintelligence13080104

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