Oral Reading Fluency Research

Dr. Gerald Tindal

Published on: September 5, 2023

Currently, teachers recognize the significance of fostering fluent reading skills for students, blending appropriate speed, accuracy, and expression in their reading. Although the link between reading fluency and comprehension is widely acknowledged, it’s particularly critical for struggling readers. Their reading is so labored that, it is difficult for them to extract meaning beyond understanding a few words. The most widely used Curriculum-Based Measurement (CBM) assesses oral reading fluency (ORF) and considerable research has accumulated since this form of measurement was initiated. ORF measurement entails students reading an unpracticed passage aloud for one minute, with errors deducted from the total words read to determine words correct per minute (WCPM), which can then serve as an effective indicator of overall reading competence. Yet, it has taken more than 40 years for this current practice to emerge. This release provides a summary of the research done in this time period.

The first CBM study to be published on oral reading fluency was in 1982[1] (long after an initial informal investigation[2]). It was the result of a program of research originally planned by Drs. Stan Deno and Phyllis Mirkin under the auspices of Data Based Program Modification. This original work called for the development of easy to implement assessment systems that teachers could use in the classroom to evaluate the effects of their instruction. It literally became the footprint for Response to Intervention (RTI) and Multi-Tiered Support Systems (MTSS), which are prominent today. Using this conceptual schema, Deno and his team of researchers began validating a series of measures in reading and writing, and later in mathematics. In reading, they settled on oral reading fluency (ORF) as the primary measure. Unlike many previous reading measures (e.g., informal reading inventories and error checklists), ORF was rate based and one minute became the standard time, allowing easy calculation of words read correctly per minute (WCPM). In this initial series of three studies, ORF was compared to measures of reading words in isolation, reading words in context (underlined), oral reading, cloze, and word meaning. A positive relation was documented among these measures. Furthermore, a significant relation was also documented between ORF and students’ performance on traditional standardized tests.

Oral reading fluency (ORF) research has evolved since this study, as documented in two summaries, one published in 2013[3] and the latter published in 2017[4]. These publications document how the decades of research on ORF has shifted in methodology and practice and summarize three broad areas: technical adequacy, growth with student populations, and finally institutionalization of ORF assessment systems in practice.

• Technical Adequacy. In the early ORF research, the focus was on validating the measurement system. Research also delved into factors influencing measurement reliability. For example, text passages influence performance estimates more so than teacher scorers. Recent studies have also explored the relation between ORF and other reading skills, highlighting the importance of fluency in comprehension. ORF performance has consistently been highly related to other, more formal measures of achievement, including state testing systems. This latter finding has become important in using fall ORF performance to predict later performance on a state test in the spring. Finally, many studies have been done on classification of students at risk, given the importance of ORF as a screener. This line of research has typically addressed sensitivity (classifying the right students who are indeed at risk) and specificity (not falsely classifying students at risk who are not at risk).

• Growth and Student Populations. Deno’s team at the University of Minnesota explored growth, observing different rates of improvement across grades. Other studies from the Fuchs research team at Vanderbilt revealed varying weekly growth rates in WCPM within and across grade levels. In recent years, nuances in growth patterns also have been uncovered. For example, growth from fall to winter has frequently been reported to be more significant than from winter to spring. The increase in ORF growth also has demonstrated an increase of about one word read correct per minute (WCPM) per week. Early studies primarily sampled students from specific regions or school districts, documenting the influence of factors like student demographics and eligibility for special education or free/reduced lunch, English language learners, and low socioeconomic status. While some differences have been observed in specific populations, the overall consistency in ORF performance and growth rates indicated the robustness of ORF as an assessment tool that is sensitive to many different student populations. In general, the findings have shown that students’ ORF performance and growth rates have been consistent across studies, despite variations in methodology and population characteristics.

Classroom Practices. Although the technical understanding of ORF has increased, broader contextualization and application of insights to instructional settings have remained crucial for a comprehensive understanding of its implications for educational practice. Probably the most important practice has been goal setting, with a clear indication that when teachers set ORF goals, achievement is better than when no goals are set. Other questions related to instruction quality, curriculum alignment, and other contextual factors. The most significant methodological change, however, has been a shift from informal researcher-crafted measures to standardized passages and the adoption of sophisticated scaling and growth models for analysis. For example, researchers have increasingly used passages from formal measurement tools such as DIBELS©, AIMS Web©, and easyCBM© to document changes in ORF over time. Most of this research, however, has focused primarily on benchmark or seasonal measurements (fall, winter, spring) rather than frequent progress monitoring.

Together, these studies on technical adequacy, growth and student populations, and classroom practices have highlighted the durability of ORF assessment across different variables and methodologies, reflecting consistent growth patterns in ORF across grade levels and students. Overall, ORF research has contributed to the understanding of reading development, informing educational practices and interventions.

[1] Deno, S. L., Mirkin, P. K., & Chiang, B. (1982). Identifying valid measures of reading. Exceptional Children 49(1), 36-47.

[2] Starch, D. (1915).The measurement of efficiency in reading. The Journal of Educational Psychology, 6(1), 1-24.

[3] Tindal, G. (2013). Curriculum-based measurement: A brief history of nearly everything from the 1970s to the present. ISRN Education (International Scholarly Research Network) 2013, 29. doi:10.1155/2013/958530

[4] Tindal, G. (2017). Oral Reading Fluency: Outcomes from 30 Years of Research. University of Oregon: Behavioral Research and Teaching. Research Report 1701.

Dr. Gerald Tindal

Dr. Tindal is currently Professor Emeritus and the Director of Behavioral Research and Teaching (BRT) – University of Oregon. He is the former Castle-McIntosh-Knight Professor in the College of Education and past Department Head of Educational Methodology, Policy, and Leadership. His research focuses on alternate assessments, integrating students with disabilities in general education classrooms, curriculum-based measurement for screening students at risk, monitoring student progress, and evaluating instructional programs. Dr. Tindal conducts research on large scale testing and development of alternate assessments. This work includes investigations of teacher decision-making on test participation, test accommodations, and extended assessments of basic skills. He publishes and reviews articles in many special education journals and has written extensively on curriculum-based measurement and large-scale testing. He has also taught scores of courses on assessment systems, data driven decision-making, research design, and program evaluation.

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