A Comparison of Two Path Models for Predicting Reading Fluency

Abstract

Federal mandates such as No Child Left Behind and the Individuals With Disabilities Education Improvement Act of 2004 are prompting elementary schools to carefully monitor early literacy outcomes. The shift toward monitoring early literacy outcomes requires the identification of valid sublexical fluency measures. In the current study, sublexical fluency measures that focus on phonological awareness, phoneme decoding, letter naming, and automatic word recognition are used to predict reading fluency. Results of two path models are discussed within the context of reading acquisition and a prevention-oriented approach.