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Elementary teacher’s knowledge of response to intervention implementation: a preliminary factor analysis

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Abstract

In the USA, many states have adopted response to intervention or multi-tiered systems of supports to provide early intervention. However, there is considerable variability in how states and schools implement RTI. Teachers are responsible for using student data from RTI to inform instructional decisions for students with or at risk for dyslexia, so it is necessary to understand the knowledge they have about the structure of RTI in their individual schools. This study reviews the results of an exploratory factor analysis of a survey aimed at measuring teachers’ knowledge about RTI implementation and their understanding of RTI implementation within their school. The 52-item survey was administered online to 139 general and special education teachers. The three final factors from this factor analytic work were (1) Teacher Knowledge about Tier 1 Implementation, (2) Teacher Knowledge about Leadership and School Systems, and (3) Teacher Knowledge about Data-Based Decision Making. Factor determinacy scores demonstrated that the survey had high internal consistency. On average, teachers’ survey scores were higher on the first two factors and slightly lower on the third factor. Implications of the findings for teachers of students with learning disabilities, including dyslexia, and directions for future research were discussed.

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References

  • Balu, R., Zhu, P., Doolittle, F., Schiller, E., Jenkins, J., & Gersten, R. (2015). Evaluation of response to intervention practices for elementary school reading. NCEE 2016-4000. Washington, DC: National Center for Education Evaluation and Regional Assistance.

    Google Scholar 

  • Barnes, S. K., & Burchard, M. S. (2011). Quality and utility of the multi-tiered instruction self- efficacy scale. Research & Practice in Assessment, 6, 22–42.

    Google Scholar 

  • Bartlett, M. S. (1950). Tests of significance in factor analysis. British Journal of Statistical Psychology, 3(2), 77–85.

    Article  Google Scholar 

  • Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246.

  • Binks-Cantrell, E., Joshi, R. M., & Washburn, E. K. (2012). Validation of an instrument for assessing teacher knowledge of basic language constructs of literacy. Annals of Dyslexia, 62(3), 153–171.

    Article  Google Scholar 

  • Bollen, K. A. (1989). A new incremental fit index for general structural equation models. Sociological Methods & Research, 17(3), 303–316.

    Article  Google Scholar 

  • Bos, C., Mather, N., Dickson, S., Podhajski, B., & Chard, D. (2001). Perceptions and knowledge of preservice and inservice educators about early reading instruction. Annals of Dyslexia, 51, 97–120.

    Article  Google Scholar 

  • Bos, C. S., Mather, N., Narr, R. F., & Babur, N. (1999). Interactive, collaborative professional development in early literacy instruction: Supporting the balancing act. Learning Disabilities Research & Practice, 14(4), 227–238.

    Article  Google Scholar 

  • Carlisle, J. F., Kelcey, B., Rowan, B., & Phelps, G. (2011). Teachers’ knowledge about early reading: Effects on students’ gains in reading achievement. Journal of Research on Educational Effectiveness, 4(4), 289–321.

    Article  Google Scholar 

  • Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1(2), 245–276.

    Article  Google Scholar 

  • Cattell, R. B., & Jaspers, J. (1967). A general plasmode (no. 30-10-5-2) for factor analytic exercises and research. Multivariate behavioral research monographs.

  • Cunningham, A. E., Perry, K. E., Stanovich, K. E., & Stanovich, P. J. (2004). Disciplinary knowledge of K-3 teachers and their knowledge calibration in the domain of early literacy. Annals of Dyslexia, 54(1), 139–167.

    Article  Google Scholar 

  • Edmonds, M., Roberts, G., & Vaughn, S. (2003). Evaluation of the Hawaii Reading Excellence Act Program, 2002–2004. Unpublished interview protocol. Austin, TX: Evaluation Research Services.

    Google Scholar 

  • Every Student Succeeds Act, Pub. l. No. 114–95 § 114 stat. 1177 (2015).

  • Foorman, B. R., & Moats, L. C. (2004). Conditions for sustaining research-based practices in early reading instruction. Remedial and Special Education, 25(1), 51–60.

    Article  Google Scholar 

  • Fuchs, D., & Fuchs, L. S. (2017). Critique of the national evaluation of response to intervention: A case for simpler frameworks. Exceptional Children, 83(3), 255–268.

    Google Scholar 

  • Fuchs, D., Fuchs, L. S., & Stecker, P. M. (2010). The “blurring” of special education in a new continuum of general education placements and services. Exceptional Children, 76(3), 301–323.

    Google Scholar 

  • Gersten, R., Compton, D., Connor, C.M., Dimino, J., Santoro, L., Linan-Thompson, S., & Tilly, W.D. (2008). Assisting students struggling with reading: Response to intervention and multi-tier intervention for reading in the primary grades. A practice guide. (NCEE 2009-4045). Washington, DC: National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education. Retrieved from http://ies.ed.gov/ncee/wwc/publications/practiceguides/.

  • Gersten, R., Jayanthi, M., & Dimino, J. (2017). Too much, too soon? Unanswered questions from national response to intervention evaluation. Exceptional Children, 83(3), 244–254.

    Google Scholar 

  • Glorfeld, L. W. (1995). An improvement on Horn’s parallel analysis methodology for selecting the correct number of factors to retain. Educational and Psychological Measurement, 55(3), 377–393.

    Article  Google Scholar 

  • Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179–185.

    Article  Google Scholar 

  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.

    Article  Google Scholar 

  • Individuals with Disabilities Education Act, 20 U.S.C. § 34 CFR 300.307 (2004).

  • Jenkins, J. R., Schiller, E., Blackorby, J., Kalb Thayer, S., & Tilly, W. D. (2013). Response to intervention in reading: Architecture and practices. Learning Disabilities Quarterly, 36(1), 36–46.

    Article  Google Scholar 

  • Jöreskog, K. G. (1993). Testing structural equation models. Sage Focus Editions, 154, 294–294.

    Google Scholar 

  • Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20(1), 141–151.

    Article  Google Scholar 

  • Lawley, D. N., & Maxwell, A. E. (1963). Factor analysis as a statistical model. London: Butterworths Mathematical Texts.

    Google Scholar 

  • Linn, R. L. (1968). A Monte Carlo approach to the number of factors problem. Psychometrika, 33(1), 37–71.

    Article  Google Scholar 

  • McCutchen, D., Abbott, R. D., Green, L. B., Beretvas, S. N., Cox, S., Potter, N. S., & Gray, A. L. (2002). Beginning literacy: Links among teacher knowledge, teacher practice, and student learning. Journal of Learning Disabilities, 35(1), 69–86.

    Article  Google Scholar 

  • McCutchen, D., Harry, D. R., Cox, S., Sidman, S., Covill, A. E., & Cunningham, A. E. (2002). Reading teachers’ knowledge of children’s literature and English phonology. Annals of Dyslexia, 52(1), 205–228.

    Article  Google Scholar 

  • Means, B., Padilla, C., DeBarger, A., & Bakia, M. (2009). Implementing data-informed decision making in schools: Teacher access, supports and use. Washington, D.C.: US Department of Education.

    Google Scholar 

  • Mellard, D., McKnight, M., & Jordan, J. (2010). RtI tier structures and instructional intensity. Learning Disabilities Research & Practice, 25, 217–225.

    Article  Google Scholar 

  • Mellard, D. F., McKnight, M., & Woods, K. (2009). Response to intervention screening and progress-monitoring practices in 41 local schools. Learning Disabilities Research & Practice, 24, 186–195.

    Article  Google Scholar 

  • Moats, L. C. (1994). The missing foundation in teacher education: Knowledge of the structure of spoken and written language. Annals of Dyslexia, 44(1), 81–102.

    Article  Google Scholar 

  • Moats, L. C., & Foorman, B. R. (2003). Measuring teachers’ content knowledge of language and reading. Annals of Dyslexia, 53(1), 23–45.

    Article  Google Scholar 

  • Muliak, S. A. (1972). The foundations of factor analysis. New York: McGraw-Hill.

    Google Scholar 

  • Muthen, L. K., & Muthen, B. O. (1998). Mplus [computer software]. Los Angeles, CA: Muthén & Muthén.

    Google Scholar 

  • National Reading Panel (U.S.), & National Institute of Child Health and Human Development (U.S.). (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: Reports of the subgroups. Washington, D.C.: National Institute of Child Health and Human Development, National Institutes of Health.

    Google Scholar 

  • Oregon Reading First: Pilot surveys. (2003). Unpublished survey instruments. Austin, TX: Evaluation Research Services.

    Google Scholar 

  • Phelps, G., & Schilling, S. (2004). Developing measures of content knowledge for teaching reading. The Elementary School Journal, 105(1), 31–48.

    Article  Google Scholar 

  • Piasta, S. B., Connor, C. M., Fishman, B. J., & Morrison, F. J. (2009). Teachers’ knowledge of literacy concepts, classroom practices, and student reading growth. Scientific Studies of Reading, 13(3), 224–248.

    Article  Google Scholar 

  • Raykov, T., & Marcoulides, G. A. (2012). A first course in structural equation modeling. Routledge.

  • Sijtsma, K. (2009). On the use, the misuse, and the very limited usefulness of Cronbach’s alpha. Psychometrika, 74(1), 107–120.

    Article  Google Scholar 

  • Spear-Swerling, L., & Brucker, P. O. (2003). Teachers’ acquisition of knowledge about English word structure. Annals of Dyslexia, 53(1), 72–103.

    Article  Google Scholar 

  • Spear-Swerling, L., & Brucker, P. O. (2004). Preparing novice teachers to develop basic reading and spelling skills in children. Annals of Dyslexia, 54(2), 332–364.

    Article  Google Scholar 

  • Spear-Swerling, L., & Cheesman, E. (2012). Teachers’ knowledge base for implementing response-to-intervention models in reading. Reading and Writing, 25(7), 1691–1723.

    Article  Google Scholar 

  • Tatham, R. L., Hair, J. F., Anderson, R. E., & Black, W. C. (1998). Multivariate data analysis. Prentice Hall, New Jersey. Titman, S. and R. Wessels, 1(1988), 1–19.

  • Texas Reading First Baseline Surveys. (2004). Unpublished survey instruments. Houston, TX: Center for Academic and Reading Skills at the University of Texas Health Science Center.

    Google Scholar 

  • Thompson, B., & Daniel, L. G. (1996). Factor analytic evidence for the construct validity of scores: A historical overview and some guidelines.

  • Torgesen, J. K. (2007). Using an RTI model to guide early reading instruction: Effects on identification rates for students with learning disabilities. (FCRR Technical Report # 7). Retrieved from http://www.fcrr.org/science/pdf/torgesen/Response_intervention_Florida.pdf.

  • Tourangeau, K., Lê, T., Nord, C., & Sorongon, A. G. (2009). Early childhood longitudinal study, kindergarten class of 1998–99 (ECLS-K), eighth-grade methodology report (NCES 2009–003). Washington, DC: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education.

    Google Scholar 

  • Velicer, W. F. (1976). Determining the number of components from the matrix of partial correlations. Psychometrika, 41(3), 321–327.

    Article  Google Scholar 

  • Vujnovic, R. K., Fabiano, G. A., Morris, K. L., Norman, K., Hallmark, C., & Hartley, C. (2014). Examining school psychologists’ and teachers’ application of approaches within a response to intervention framework. Exceptionality, 22(3), 129–140.

    Article  Google Scholar 

  • Washington (RTI) 2 and HB 2136 Survey of RTI knowledge, values and use for building administrators. (2011). Unpublished survey instruments. Evaluation Research Services: Austin, TX.

  • Wilcox, K. A., Murakami-Ramalho, E., & Urick, A. (2013). Just-in-time pedagogy: Teachers’ perspectives on the response to intervention framework. Journal of Research in Reading, 36(1), 75–95.

    Article  Google Scholar 

  • Zirkel, P. A., & Thomas, L. B. (2010). State laws for RTI: An updated snapshot. Teaching Exceptional Children, 42(3), 56–63.

    Article  Google Scholar 

  • Zwick, W. R., & Velicer, W. F. (1986). Comparison of five rules for determining the number of components to retain. Psychological Bulletin, 99(3), 432–442.

    Article  Google Scholar 

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Correspondence to Stephanie Al Otaiba.

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Appendix

Appendix

Table 7 Survey of Teachers’ Knowledge about RTI Implementation
Table 8 Descriptive statistics for Survey of Teachers’ Knowledge about RTI Implementation

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Al Otaiba, S., Baker, K., Lan, P. et al. Elementary teacher’s knowledge of response to intervention implementation: a preliminary factor analysis. Ann. of Dyslexia 69, 34–53 (2019). https://doi.org/10.1007/s11881-018-00171-5

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