Differentiation as measured by the Classroom Practices Survey: a validity study updating the original instrument
The Classroom Practices Survey assesses educators’ use of differentiated instruction with students achieving at average and high levels. The purposes of this study were to investigate if the Classroom Practices Survey (1) yields reliable and valid data from the groups for which it was originally designed and (2) can be used to evaluate teachers’ differentiation practices for students who achieve at low levels. Participants included 648 elementary teachers who completed the Classroom Practices Survey for students achieving at high, average and low levels. Confirmatory factor analyses revealed that the original six-factor model was not supported by the current data. Model fit was improved with a four-factor model, but did not reach the recommended values for good model fit. Further research and possibly modifications are needed before this tool is used by researchers and schools. This study highlights the importance of periodically evaluating instruments and revising them if necessary.
KeywordsClassroom Practices Survey (CPS) Differentiated instruction Validity
This research was funded by the United States Department of Education, The Javits Gifted and Talented Students Education Program (Award #S206A140011).
- American Educational Research Association, American Psychological Association and the National Council on Measurement in Education. (2014). Standards for educational and psychological testing. Washington, DC: Author.Google Scholar
- Archambault, F. X., Jr., Westberg, K. L., Brown, S., Hallmark, B. W., Emmons, C., & Zhang, W. (1993). Regular classroom practices with gifted students: Results of a national survey of classroom teachers. Storrs, CT: The National Research Center on the Gifted and Talented.Google Scholar
- Brown, T. (2015). Confirmatory Factor Analysis for Applied Research. New York: Guiford Press.Google Scholar
- Council of Chief State School Officers. (2013). InTASC model core teaching standards and learning progressions for teachers. Retrieved from: https://ccsso.org/sites/default/files/2017-12/2013_INTASC_Learning_Progressions_for_Teachers.pdf.
- Edwards, C. J., Carr, S., & Siegel, W. (2006). Influences of experiences and training on effective teaching practices to meet the needs of diverse learners in schools. Education, 126, 580–592.Google Scholar
- Gentry, M., Paul, K. A., McIntosh, J., Fugate, C. M., & Jen, E. (2014). Total school cluster grouping and differentiation: A comprehensive research-based plan for raising student achievement and improving teacher practices. Waco, TX: Prufrock Press.Google Scholar
- Gentry, M., Rizza, M. G., & Owen, S. V. (2002). Examining perceptions of challenge and choice in classrooms: The relationship between teachers and their students and comparisons between gifted students and other students. Gifted Child Quarterly, 46(2), 145–155. https://doi.org/10.1177/001698620204600207.CrossRefGoogle Scholar
- Hunsaker, S. L., & Shepherd, P. (2010). Policy perspectives on gifted education. In S. Hunsaker (Ed.), Identification: The theory and practice of identifying students for gifted and talented education services (pp. 121–141). Mansfield Center, CT: Creative Learning Press.Google Scholar
- Mammadov, S. (2014). A need to rethink about national consensus on preparing teachers of the gifted: A policy brief. The William and Mary Educational Review, 2(2), 15–18.Google Scholar
- McDonald, R. P. (1999). Test theory: A unified approach. Mahwah, NJ: Erlbaum.Google Scholar
- Medina, J. (2008). Brain rules: 12 principles for surviving and thriving at work, home, and school. Seattle, WA: Pear Press.Google Scholar
- Muthén, L. K., & Muthén, B. O. (1998–2014). Mplus, v.7.2. Los Angeles, CA: Muthén & Muthén.Google Scholar
- National Association for Gifted Children. (2008). The role of assessments in identifying gifted individuals. http://www.nagc.org/sites/default/files/Position%20Statement/Assessment%20Position%20Statement.pdf. Accessed 10 Jan 2018.
- National Association for Gifted Children. (2010a). Pre-K to Grade 12 Gifted Programming Standards. http://www.nagc.org/sites/default/files/standards/K-12%20programming%20standards.pdf. Accessed 10 Jan 2018.
- National Association for Gifted Children. (2010b). Guiding questions to apply the Pre-K to Grade 12 Gifted Programming Standards. https://www.nagc.org/resources-publications/resources/national-standards-gifted-and-talented-education/pre-k-grade-12-7. Accessed 10 Jan 2018.
- National Association for Gifted Children and Council for Exceptional Children, The Association for the Gifted. (2013). NAGC—CEC Teacher preparation standards in gifted and talented education. http://www.nagc.org/sites/default/files/standards/NAGC-%20CEC%20CAEP%20standards%20%282013%20final%29.pdf. Accessed 10 Jan 2018.
- National Association for Gifted Children and Council of State Directors of Programs for the Gifted. (2015). 2014–2015 state of the states in gifted education: Policy and practice data. https://www.nagc.org/sites/default/files/key%20reports/2014-2015%20State%20of%20the%20States%20(final).pdf. Accessed 10 Jan 2018.
- Renzulli, J. S., & Reis, S. M. (2004). Curriculum compacting: A research-based differentiation strategy for culturally diverse talented students. https://gifted.uconn.edu/schoolwide-enrichment-model/compacting_for_at_risk/. Accessed 10 Jan 2018.
- Sousa, D. A., & Tomlinson, C. A. (2010). Differentiation and the brain: How neuroscience supports the learner-friendly classroom. Bloomington, IN: Solution Tree Press.Google Scholar
- Tomlinson, C. A. (2014). Differentiated classroom: Responding to the needs of all learners. Alexandria, VA: ASCD.Google Scholar
- Tomlinson, C. A., Callahan, C. M., Moon, T. R., Tomchin, E. M., Landrum, M., Imbeau, M., et al. (1995). Preservice teacher preparation in meeting the needs of gifted and other academically diverse students. Storrs, CT: The National Research Center on the Gifted and Talented, University of Connecticut.Google Scholar
- Yu, C. Y. (2002). Evaluating cutoff criteria of model fit indices for latent variable models with binary and continuous outcomes. Unpublished doctoral dissertation, University of California, Los Angeles.Google Scholar