five

Descriptive Statistics.

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Descriptive_Statistics_/29407116
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This study explores the predictive validity of early and mid-year literacy assessments—Letter Naming Fluency (LNF), Letter Sound Fluency (LSF), and Phoneme Segmentation Fluency (PSF)—for end-of-year Word Reading Fluency (WRF) in kindergarten and grade 1 Arabic-speaking students. Using a longitudinal design, 412 students were assessed at three intervals (fall, mid-year, and year-end) to examine how these foundational literacy skills contribute to predicting WRF and identifying at-risk readers. Results from multiple regression analyses indicate that both LNF and LSF are significant predictors of end-of-year WRF across both fall and mid-year assessments, with mid-year measures demonstrating enhanced predictive accuracy. In contrast, PSF showed limited predictive value in comparison to LNF and LSF. Accuracy analyses revealed that mid-year assessments, particularly LNF and LSF, were more reliable in identifying at-risk students compared to fall assessments. Mid-year assessments correctly identified 64–73% of at-risk readers, emphasizing their value in early detection and intervention. These findings underline the importance of dynamic, multi-point assessments in improving educational practices and outcomes, particularly for students at risk of reading difficulties. The study highlights the critical role of foundational literacy skills in early reading development and provides actionable insights to enhance intervention strategies during key stages of literacy acquisition.
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2025-06-25
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