Reviewing Evidence on the Relations Between Oral Reading Fluency and Reading Comprehension for Adolescents

Abstract

In this article, I systematically review evidence on the relations between oral reading fluency (ORF) and reading comprehension (RC) for adolescents with limited reading proficiency (ALRP) in Grades 6 to12. I organized findings from 23 studies into five themes: (a) unclear role of ORF in the simple view of reading model for ALRP, (b) ALRP have distinct reader profiles, (c) ORF consists of more than automaticity, (d) the role of ORF varies, and (e) oral reading automaticity has tenuous predictive value for ALRP. Results suggest that knowledge of an adolescent’s ORF, as commonly defined and assessed, provides helpful information about an adolescent’s reader profile, but is not sufficient to evaluate instructional needs nor measure progress. I conclude the article with a discussion on implications for researchers, assessment developers, practitioners, and school administrators.

Word Recognition and Fluency Activities’ Effects on Reading Comprehension: An Iranian EFL Learners’ Experience

“…To put it in other words, instruction in both decoding skills and rate-building activities enhanced text comprehension among experimental subjects. is finding is in line with the theoretical foundation underpinning this study [19,27,29,30,[45][46][47][48], 100).…”

“…However, Ribeiro et al (2016) had argued that reading fluency is the strongest predictor of reading comprehension, but this experiment provided evidence that fluency in reading is by no means a better practice than word recognition activities, at least at the preintermediate level of language proficiency. Successful L2 comprehension depends on both large vocabulary size and rapid vocabulary access; accordingly, L2 learners need to allocate a significant portion of their learning time to enhance their reading fluency [45][46][47][48]. Because insufficient decoding skills hinder comprehension among a majority of L2 learners [54], the results obtained from this investigation can be regarded as a practical solution.…”

“…According to a majority of L2 acquisition studies, optimal L2 text comprehension is dependent not only on vocabulary size but also on L2 vocabulary access rate, and L2 learners should devote significant time to improving their fluency [45][46][47][48]. However, a common finding in research across grade levels is that a large proportion of those struggling with comprehending issues have decoding skills that are below average [49][50][51].…”

Word- and Text-Level Processes Contributing to Fluent Reading of Word Lists and Sentences

“…By depth we mean specific assessment of underlying word- and/or text-level processes (e.g., individual word recognition and sequential processing; see e.g., Nomvete and Easterbrooks, 2020 , for text-level suggestions) with the aim to identify specific deficiencies. By increasing breadth we mean mapping reading fluency through measures that have educational and societal relevance (i.e., covering connected text) and fit literacy progress as reading becomes more advanced, with the aim to make instructional decisions (see Washburn, 2022 , for an overview). Combined, the resulting information can provide input for further improvement of literacy instruction throughout education and foster tailored assessment and interventions for struggling readers.…”

Monitoring Reading Component Skills during a Word‐Level Intervention for Adolescents with Limited Reading Proficiency

“…That is, the SVR does not explicitly include ORF, and the study to develop the Complete View of Reading relied on ORF (measured as accuracy and rate only) as the outcome variable. ORF comprises more than accuracy and rate, yet practitioners and researchers commonly assess ORF as words read correctly per minute which excludes prosody, or expressive reading (see Washburn, 2022, for a summary). Several studies suggest that if ORF is measured solely by accuracy and rate to predict reading comprehension, its predictive power is limited or confounded by extraneous variables (e.g., Cirino et al., 2013; Clemens et al., 2017; Cutting et al., 2009).…”