Skip to main content

Advertisement

SpringerLink
Log in

The unique relation of silent reading fluency to end-of-year reading comprehension: understanding individual differences at the student, classroom, school, and district levels

  • Published:
Reading and Writing Aims and scope Submit manuscript

Abstract

Despite many previous studies on reading fluency (measured by a maze task) as a screening measure, our understanding is limited about the utility of silent reading fluency in predicting later reading comprehension and contextual influences (e.g., schools and districts) on reading comprehension achievement. In the present study we examined: (1) How much variance in reading comprehension scores exist between students, classes, schools, and districts for children in grades 3–10; and (2) whether silent reading fluency measured by a maze task adds a unique contribution to the prediction of spring reading comprehension after accounting for fall spelling and reading comprehension. Results showed that a substantial amount of variance in reading comprehension is attributable to differences among classrooms (21–46 %), particularly in grades 6–10. In addition, approximately 3–5 % of variance in reading comprehension was attributable to differences among schools and districts. Silent reading fluency also explained a unique amount of variance in spring reading comprehension after accounting for students’ performance in reading comprehension and spelling in the fall. Unique variance (pseudo-R 2) varied from 2 to 10 % at the student, class, school, and district levels. These results suggest that a maze task has potential utility as a screening measure of reading comprehension for students in grades 3–10. Furthermore, differences among classrooms, schools, and districts matter for students’ reading comprehension achievement.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Abbott, R., Berninger, V. W., & Fayol, M. (2010). Longitudinal relationships of levels of language in writing and between writing and reading in Grades 1 to 7. Journal of Educational Psychology, 102, 281–298.

    Article  Google Scholar 

  • Aikens, N. L., & Barbain, O. (2008). Socioeconomic differences in reading trajectories: The contribution of family, neighborhood, and school contexts. Journal of Educational Psychology, 100, 235–251.

    Article  Google Scholar 

  • Al Otaiba, S., Kim, Y.-S., Folsom, J., & Puranik, C. (2012). Growth trajectories of writing for typical children and children with language impairment. Montreal, Canada: Paper presented at the Society for Scientific Studies of Reading.

    Google Scholar 

  • Apel, K., & Masterson, J. J. (2001). Theory-guided spelling assessment and intervention. Language, Speech, and Hearing Services in the Schools, 32, 182–195.

    Article  Google Scholar 

  • Apel, K., Masterson, J. J., & Niessen, N. L. (2004). Spelling assessment frameworks. In A. Stone, E. R. Silliman, B. Ehren, & K. Apel (Eds.), Handbook of language and literacy: Development and disorder (pp. 644–660). New York: Guilford Press.

    Google Scholar 

  • Ardoin, S. P., Witt, J. C., Suldo, S. M., Connell, J. E., Koenig, J. L., Resetar, J. L., et al. (2004). Examining the incremental benefits of administering a maze and three versus one curriculum-based measurement reading probes when conducting universal screening. School Psychology Review, 33, 218–233.

    Google Scholar 

  • Arndt, E. J. (2010). Factors affecting the development of second grade spelling at the teacher, student, and word level. Unpublished doctoral dissertation, Florida State University, Tallahassee, FL.

  • Bronfenbrenner, U. (1989). Ecological systems theory. In R. Vasta (Ed.), Annals of child development: Vol. 6. Six theories of child development: Revised formulations and current issues (pp. 187–249). Greenwich, CT: JAI Press.

    Google Scholar 

  • Bronfenbrenner, U. (1994). Ecological models of human development. In International encyclopedia of education (2nd ed., Vol. 3). Oxford: Elsevier.

  • Buros Center for Testing. (2010). Evaluating reading tests for the State of Florida: Dynamic Indicators of Basic Early Literacy Skills, 6th Edition and Florida Assessments for Instruction in Reading. Linconln, NE: Buros Center for Testing.

    Google Scholar 

  • Byrne, B., Coventry, W. L., Olson, R. K., Wadsworth, S. J., Samuelson, S., Petrill, S. A., et al. (2010). “Teacher effects” in early literacy development: Evidence from a study of twins. Journal of Educational Psychology, 102, 32–42.

    Article  Google Scholar 

  • Catts, H. W., Petscher, Y., Schatschneider, C., Bridges, M. S., & Mendoza, K. (2009). Floor effects associated with universal screening and their impact on the early identification of reading disabilities. Journal of Learning Disabilities, 42, 163–176.

    Article  Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Compton, D. L., Fuchs, D., Fuchs, L. S., & Bryant, J. D. (2006). Selecting at-risk readers in first grade for early intervention: A two-year longitudinal study of decision rules and procedures. Journal of Educational Psychology, 98, 394–409.

    Article  Google Scholar 

  • Connor, C. M., Piasta, S. B., Fishman, B., Glasney, S., Schatschneider, C., Crowe, E., et al. (2009). Individualizing student instruction precisely: Effects of child by instruction interactions on first graders’ literacy development. Child Development, 80, 77–100.

    Article  Google Scholar 

  • Edmonds, M. S., Vaughn, S., Wexler, J., Reutebuch, C., Cable, A., Tackett, K. K., et al. (2009). A synthesis of reading interventions and effects on reading comprehension outcomes for older struggling readers. Review of Educational Research, 79, 262–300.

    Article  Google Scholar 

  • Ehri, L. C. (2000). Learning to read and learning to spell: Two sides of a coin. Topics in Language Disorders, 20, 19–36.

    Article  Google Scholar 

  • Espin, C., Wallace, T., Lembke, E., Campbell, H., & Long, J. D. (2010). Creating a progress-monitoring system in reading for middle-school students: Tracking progress toward meeting high-stakes standards. Learning Disabilities Research & Practice, 25, 60–75.

    Article  Google Scholar 

  • Florida Assessments for Instruction in Reading Technical Manuals. (2009). Retrieved http://www.fcrr.org/fair/Technical%20manual%20-%203-12-FINAL_2012.pdf.

  • Florida Department of Education. (2001). FCAT handbook—A resource for educators. Tallahassee, FL: Florida Department of Education.

    Google Scholar 

  • Florida Department of Education. (2005). FCAT briefing book. Tallahassee, FL: Florida Department of Education.

    Google Scholar 

  • Foorman, B., Petscher, Y., & Bishop, M. D. (2012). The incremental variance of morphological knowledge to reading comprehension in grades 3-10 beyond prior reading comprehension, spelling, and text reading fluency. L22earning and Individual Differences, 22, 792–798.

    Google Scholar 

  • Foorman, B., Torgesen, J., Crawford, E., & Petscher, Y. (2009). Assessments to guide reading instruction in K-12: Decisions supported by the new Florida system. Perspectives on Language and Literacy, 35, 13–19.

    Google Scholar 

  • Francis, D. J., Santi, K. L., Barr, C., Fletcher, J. M., Varisco, A., & Foorman, B. F. (2008). Form effects on the estimation of students’ oral reading fluency using DIBELS. Journal of School Psychology, 46, 315–342.

    Article  Google Scholar 

  • Fuchs, L. S., Fuchs, D., & Compton, D. L. (2004). Monitoring early reading development in first grade: Word identification fluency versus nonsense word fluency. Exceptional Children, 71, 7–21.

    Article  Google Scholar 

  • Fuchs, L. S., Fuchs, D., Hosp, M. K., & Jenkins, J. R. (2001). Oral reading fluency as an indicator of reading competence: A theoretical, empirical, and historical analysis. Scientific Studies of Reading, 5, 239–256.

    Article  Google Scholar 

  • Hoover, W. A., & Gough, P. B. (1990). The simple view of reading. Reading and Writing: An Interdisciplinary Journal, 2, 127–160.

    Article  Google Scholar 

  • Hox, J. J. (2010). Multilevel analysis: Techniques and applications (2nd ed.). New York: Routledge.

    Google Scholar 

  • Jenkins, J. R., Fuchs, L. S., van den Broek, P., Espin, C., & Deno, S. L. (2003). Sources of individual differences in reading comprehension and reading fluency. Journal of Educational Psychology, 95, 719–729.

    Article  Google Scholar 

  • Jenkins, J. R., Hudson, R. F., & Johnson, E. S. (2007). Screening for at-risk readers in a response to intervention framework. School Psychology Review, 36, 582–600.

    Google Scholar 

  • Jenkins, J. R., & Jewell, M. (1993). Examining the validity of two measures for formative teaching: Reading aloud and maze. Exceptional Children, 59, 421–432.

    Google Scholar 

  • Joshi, R. M., & Aaron, P. G. (2000). The component model of reading: Simple view of reading made a little more complex. Reading Psychology, 21, 85–97.

    Article  Google Scholar 

  • Kim, Y.-S. (2010). Componential skills of spelling in Korean. Scientific Studies of Reading, 14, 137–158.

    Article  Google Scholar 

  • Kim, Y.-S., Petscher, Y., Schatschneider, C., & Foorman, B. (2010). Does growth rate in oral reading fluency matter for reading comprehension? Journal of Educational Psychology, 102, 652–667.

    Article  Google Scholar 

  • Kim, Y.-S., Wagner, R. K., & Foster, L. (2011). Relations among oral reading fluency, silent reading fluency, and reading comprehension: A latent variable study of first-grade readers. Scientific Studies of Reading, 15, 338–362.

    Article  Google Scholar 

  • Kim, Y.-S., Wagner, R., & Lopez, D. (2012). Developmental relations between reading fluency and reading comprehension: A longitudinal study from grade one to two. Journal of Experimental Child Psychology, 113, 93–111.

    Article  Google Scholar 

  • Kolen, M. J., & Brennan, R. L. (2004). Test equating, scaling, and linking. New York, NY: Springer.

  • LaBerge, D., & Samuels, S. J. (1974). Toward a theory of automatic information processing in reading. Cognitive Psychology, 62, 293–323.

    Article  Google Scholar 

  • Logan, G. D. (1988). Automaticity and reading: Perspectives from the instance theory of automatization. Reading and Writing Quarterly: Overcoming Learning Difficulties, 13, 123–146.

    Article  Google Scholar 

  • McMaster, K. L., Wayman, M., & Cao, M. (2006). Monitoring the reading progress of secondary-level English learners: Technical features of oral reading and maze tasks. Assessment for Effective Intervention, 31, 17–32.

    Article  Google Scholar 

  • Mehta, P. D., Foorman, B. R., Branum-Martin, L., & Taylor, W. P. (2005). Literacy as a unidimensional multilevel construct: Validation, sources of influence, and implications in a longitudinal study in grades 1–4. Scientific Studies of Reading, 9, 85–116.

    Article  Google Scholar 

  • Muthén, B., & Satorra, A. (1989). Multilevel aspects of varying parameters in structural models. Invited paper for the conference, Multilevel analysis of educational data, Princeton, NJ, April 1987. In D. R. Bock (Ed.), Multilevel analysis of educational data (pp. 87–99). San Diego, CA: Academic Press.

  • Nagy, W., Berninger, V. W., & Abbott, R. D. (2006). Contributions of morphology beyond phonology to literacy outcomes of upper elementary and middle-school students. Journal of Educational Psychology, 98, 134–147.

    Article  Google Scholar 

  • National Early Literacy Panel (NELP). (2009). Developing early literacy: Report of the national early literacy panel. Washington, DC: National Institute for Literacy. Downloaded from http://www.nifl.gov/publications/pdf/NELPReport09.pdf.

  • National Institute of Child Health and Human Development. (2000). Report of the National Reading Panel. Teaching children to read: An evidence-based assessment of the scientific research literature on reading and its implications for reading instruction (NIH Publication No. 00-4769). Washington, DC: U.S. Government Printing Office.

  • Perfetti, C. A. (1985). Reading ability. New York: Oxford Press.

    Google Scholar 

  • Perfetti, C. A. (1992). The representation problem in reading acquisition. In L. C. Ehri, R. Treiman, & P. B. Gough (Eds.), Reading acquisition (pp. 145–174). Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Perfetti, C. A., & Hart, L. (2001). The lexical bases of comprehension skill. In D. Gorfien (Ed.), On the consequences of meaning selection (pp. 67–86). Washington, DC: American Psychological Association.

    Google Scholar 

  • Petscher, Y., & Foorman, B. R. (2011). Summary of the predictive relationship between the FAIR and FCAT in grades 3–10: 2010–2011. Tallahassee, Florida: Florida Center for Reading Research.

    Google Scholar 

  • Petscher, Y., & Kim, Y.-S. (2011). The utility and accuracy of oral reading fluency score types in predicting reading comprehension. Journal of School Psychology, 49, 107–129.

    Article  Google Scholar 

  • Reutzel, D. R. (2009, April 14). Reading fluency: What every SLP and teacher should know. The ASHA Leader.

  • Ridel, B. W. (2007). The relation between DIBELS, reading comprehension, and vocabulary in urban first-grade students. Reading Research Quarterly, 42, 546–567.

    Article  Google Scholar 

  • Roehrig, A. D., Petscher, Y., Nettles, S. M., Hudson, R. F., & Torgesen, J. K. (2008). Not just speed reading: Accuracy of the DIBELS oral reading fluency measure for predicting high-stakes third grade reading comprehension outcomes. Journal of School Psychology, 46, 343–366.

    Article  Google Scholar 

  • SAS Institute Inc. (2011). Base SAS ® 9.3 procedures guide. Cary, NC: SAS Institute Inc.

    Google Scholar 

  • Spybrook, J., Raudenbush, S.W., Congdon, R., & Martinez, A. (2009). Optimal design for longitudinal and multilevel research: Documentation for the optimal design software V.2.0.

  • Taylor, J., Roehrig, A. D., Soden Hensler, B., Connor, C. M., & Schatschneider, C. (2010). Teacher quality moderates the genetic effects on early reading. Science, 328, 512–514.

    Article  Google Scholar 

  • Treiman, R., & Bourassa, D. C. (2000). The development of spelling skill. Topics in Language Disorders, 20, 1–18.

    Article  Google Scholar 

  • Wayman, M. M., Wallace, T., Wiley, H. I., Ticha, R., & Espin, C. A. (2007). Literature synthesis on curriculum-based measurement in reading. Journal of Special Education, 41, 85–120.

    Article  Google Scholar 

  • Weigel, D. J., Martin, S. S., & Bennett, K. K. (2005). Ecological influences of the home and the child-care center on preschool-age children’s literacy development. Reading Research Quarterly, 40, 205–233.

    Article  Google Scholar 

  • Wiley, H., & Deno, S. (2005). Oral reading and maze measures as predictors of success for English language learners on a state standards assessment. Remedial and Special Education, 26, 207–214.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Florida Center for Reading Research and Florida State University, 1114 W. Call Street, Tallahassee, FL, 32306, USA

    Young-Suk Kim, Yaacov Petscher & Barbara Foorman

Authors
  1. Young-Suk Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yaacov Petscher
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Barbara Foorman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Young-Suk Kim.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kim, YS., Petscher, Y. & Foorman, B. The unique relation of silent reading fluency to end-of-year reading comprehension: understanding individual differences at the student, classroom, school, and district levels. Read Writ 28, 131–150 (2015). https://doi.org/10.1007/s11145-013-9455-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11145-013-9455-2

Keywords

Search

Navigation