Assessing Students’ Skills Using a Nontraditional Approach

  • Christine E. Neddenriep
  • Brian C. Poncy
  • Christopher H. Skinner


Currently, within the field of school psychology, a shift in service delivery models is occurring. Whereas school psychology had been dominated by a refer-test-report (and place) delivery model (Reschly & Yssedyke, 2002), recent legislation has facilitated a change in service delivery to include a response to intervention (RtI) model (Brown-Chidsey & Steege, 2005). Practicing within this service delivery model both allows and requires school psychologists to expand their range of skills and the services they offer (Oakland & Cunningham, 1999), specifically increasing their use of nontraditional assessment measures. This need to increase school psychologists’ competencies in nontraditional assessment measures within a problem-solving, outcome-driven model provides the context for this chapter.


Reading Fluency Progress Monitoring Oral Reading Fluency Nonsense Word Fluency Phoneme Segmentation Fluency 
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  1. Bergan, J. R., & Kratochwill, T. R. (1990). Behavioral consultation and therapy. New York: Plenum.Google Scholar
  2. Brown-Chidsey, R., & Steege, M. W. (2005). Response to intervention. New York: Guilford.Google Scholar
  3. Christ, T. J. (2006). Short term estimates of growth using curriculum-based measurement of oral reading fluency: Estimating standard error of the slope to construct confidence intervals. School Psychology Review, 35, 128–133.Google Scholar
  4. Christ, T. J., & Silberglitt, B. (2007). Estimates of the standard error of measurement for curriculum-based measures of oral reading fluency. School Psychology Review, 36, 130–146.Google Scholar
  5. Colón, E. P., & Kranzler, J. H. (2006). Effect of instructions on curriculum-based measurement of reading. Journal of Psychoeducational Assessment, 24, 318–328.CrossRefGoogle Scholar
  6. Daly, E. J., Chafouleas, S., & Skinner, C. H. (2005). Interventions for reading problems. New York: Guilford.Google Scholar
  7. Deno, S. L. (1989). Curriculum-based measurement and special education services: A fundamental and direct relationship. In M. R. Shinn (Ed.), Curriculum-based measurement: Assessing special children (pp. 1–17). New York: Guilford.Google Scholar
  8. Deno, S. L. (2002). Problem solving as “best practice.”. In A. Thomas & J. Grimes (Eds.), Best practices in school psychology IV (pp. 37–56). Bethesda, MD: National Association of School Psychologists.Google Scholar
  9. Deno, S. L. (2005). Problem solving assessment. In R. Brown-Chidsey (Ed.), Assessment for intervention (pp. 10–40). New York: Guilford.Google Scholar
  10. Deno, S. L., Marston, D., & Mirkin, P. (1982). Valid measurement procedures for continuous evaluation of written expression. Exceptional Children, 48, 368–371.Google Scholar
  11. Deno, S. L., & Mirkin, P. K. (1977). Data-based problem modification: A manual. Reston: Council for Exceptional Children.Google Scholar
  12. Deno, S. L., Mirkin, P. K., & Chiang, B. (1982). Identifying valid measures of reading. Exceptional Children, 49, 36–45.PubMedGoogle Scholar
  13. Derr-Minneci, T. F., & Shapiro, E. S. (1992). Validating curriculum-based measurement in reading from a behavioral perspective. School Psychology Quarterly, 7, 2–16.CrossRefGoogle Scholar
  14. Fagan, T. K., & Wise, P. S. (2000). School psychology: Past, present, and future (2nd ed.). Bethesda, MD: National Association of School Psychologists.Google Scholar
  15. Forness, S. R., Kavale, K. A., Blum, I. M., & Lloyd, J. W. (1997). Mega-analysis of meta-analyses: What works in special education and related services. Teaching Exceptional Children, 29(6), 4–9.Google Scholar
  16. Fuchs, L. S. (1989). Evaluating solutions: Monitoring progress and revising intervention plans. In M. R. Shinn (Ed.), Curriculum-based measurement: Assessment special children (pp. 153–181). New York: Guilford.Google Scholar
  17. Fuchs, L. S., & Deno, S. L. (1992). Effects of curriculum within curriculum-based measurement. Exceptional Children, 58, 232–243.Google Scholar
  18. Fuchs, L. S., & Fuchs, D. (1986). Effects of systematic formative evaluation: A meta-analysis. Exceptional Children, 53, 199–208.PubMedGoogle Scholar
  19. Fuchs, L. S., & Fuchs, D. (1992). Identifying a measure for monitoring student reading progress. School Psychology Review, 21, 45–58.Google Scholar
  20. Fuchs, L. S., Fuchs, D., & Hamlett, C. L. (1989). Effects of instrumental use of curriculum-based measurement to enhance instructional programs. Remedial and Special Education, 10(2), 43–52.CrossRefGoogle Scholar
  21. Fuchs, L. S., Fuchs, D., Hamlett, C. L., Walz, L., & Germann, G. (1993). Formative evaluation of academic progress: How much growth can we expect? School Psychology Review, 22, 27–48.Google Scholar
  22. Fuchs, L. S., Fuchs, D., & Maxwell, L. (1988). The validity of informal reading comprehension measures. Remedial and Special Education, 9(2), 20–28.CrossRefGoogle Scholar
  23. Goldstein, H., Arkell, C., Ashcroft, S. C., Hurley, O. L., & Lilly, S. M. (1975). Schools. In N. Hobbs (Ed.), Issues in the classification of children. San Francisco: Jossey-Bass.Google Scholar
  24. Good, R. H., III, & Kaminski, R. A. (Eds.). (2002). Dynamic Indicators of Early Literacy Skills (6th ed.). Eugene, OR: Institute for the Development of Educational Achievement.Google Scholar
  25. Hintze, J. M., & Christ, T. J. (2004). An examination of variability as a function of passage variance in CBM progress monitoring. School Psychology Review, 33, 204–217.Google Scholar
  26. Hintze, J. M., Owen, S. V., Shapiro, E. S., & Daly, E. J. (2000). Generalizability of oral reading fluency measures: Application of g theory to curriculum-based measurement. School Psychology Quarterly, 15, 52–68.CrossRefGoogle Scholar
  27. Howell, K. W., & Nolet, V. (2000). Curriculum-based evaluation: Teaching and decision making (3rd ed.). Belmont, CA: Wadsworth.Google Scholar
  28. Kampwirth, T. J. (2006). Collaborative consultation in the schools: Effective practices for students with learning and behavior problems (3rd ed.). Upper Saddle River, NJ: Prentice Hall.Google Scholar
  29. Kavale, K. (1990). The effectiveness of special education. In T. B. Gutkin & C. R. Reynolds (Eds.), The handbook of school psychology (2nd ed., pp. 868–898). New York: John Wiley.Google Scholar
  30. Marston, D. B. (1989). A curriculum-based measurement approach to assessing academic performance: What it is and why do it. In M. R. Shinn (Ed.), Curriculum-based measurement: Assessment special children (pp. 18–78). New York: Guilford.Google Scholar
  31. Neddenriep, C. E., Hale, A. D., Skinner, C. H., Hawkins, R. O., & Winn, B. (2007). A preliminary investigation of the concurrent validity of reading comprehension rate: A direct, dynamic measure of reading comprehension. Psychology in the Schools, 44, 373–388.CrossRefGoogle Scholar
  32. Oakland, T., & Cunningham, J. (1999). The futures of school psychology: Conceptual models for its development and examples of their applications. In C. R. Reynolds & T. B. Gutkin (Eds.), The handbook of school psychology (3rd ed., pp. 34–53). New York: Wiley.Google Scholar
  33. Poncy, B. C., Skinner, C. H., & Axtell, P. K. (2005). An investigation of the reliability and standard error of measurement of words read correctly per minute. Journal of Psychoeducational Assessment, 23, 326–338.CrossRefGoogle Scholar
  34. Powell-Smith, K. A., & Bradley-Klug, K. L. (2001). Another look at the “C” in CBM: Does it really matter if curriculum-based measurement reading probes are “curriculum-based? Psychology in the Schools, 38, 299–312.CrossRefGoogle Scholar
  35. Reschly, D. J., & Yssedyke, J. E. (2002). Paradigm shift: The past is not the future. In A. Thomas & J. Grimes (Eds.), Best practices in school psychology IV (pp. 3–36). Bethesda, MD: National Association of School Psychologists.Google Scholar
  36. Shapiro, E. S. (2004). Academic skills problem: Direct assessment and intervention (3rd ed.). New York: Guilford.Google Scholar
  37. Shinn, M. R. (Ed.). (1989). Curriculum-based measurement: Assessing special children. New York: Guilford.Google Scholar
  38. Shinn, M. R. (2002). Best practices in using curriculum-based measurement in a problem-solving model. In A. Thomas & J. Grimes (Eds.), Best practices in school psychology IV (pp. 671–698). Bethesda, MD: National Association of School Psychologists.Google Scholar
  39. Shinn, M. R., & Bamonto, S. (1998). Advanced applications of curriculum-based measurement: “Big ideas” and avoiding confusion. In M. R. Shinn (Ed.), Advanced applications of curriculum-based measurement (pp. 1–31). New York: Guilford.Google Scholar
  40. Shinn, M. R., Good, R. H., III, & Parker, C. (1999). Noncategorical special education services with students with severe achievement deficits. In D. J. Reschly, W. D. Tilly III, & J. P. Grimes (Eds.), Special education in transition: Functional assessment and noncategorical programming (pp. 81–105). Longmont: Sopris West.Google Scholar
  41. Skinner, C. H. (1998). Preventing academic skills deficits. In T. S. Watson & F. Gresham (Eds.), Handbook of child behavior therapy: Ecological considerations in assessment, treatment, and evaluation (pp. 61–83). New York: Plenum.Google Scholar
  42. Skinner, C. H., Belfiore, P. B., & Watson, T. S. (1995/2002). Assessing the relative effects of interventions in students with mild disabilities: Assessing instructional time. Journal of Psychoeducational Assessment, 20, 345-356.15. (Reprinted from Assessment in Rehabilitation and Exceptionality, 2, 207-220, 1995)Google Scholar
  43. Skinner, C. H., Hurst, K. L., Teeple, D. F., & Meadows, S. O. (2002). Increasing on-task behavior during mathematics independent seat-work in students with emotional disorders by interspersing additional brief problems. Psychology in the Schools, 39, 647–659.CrossRefGoogle Scholar
  44. Skinner, C. H., Neddenriep, C. E., Bradley-Klug, K. L., & Ziemann, J. M. (2002). Advances in curriculum-based measurement: Alternative rate measures for assessing reading skills in pre- and advanced readers. Behavior Analyst Today, 3, 270–281.Google Scholar
  45. Tilly, W. D. (2002). Best practices in school psychology as a problem-solving enterprise. In A. Thomas & J. Grimes (Eds.), Best practices in school psychology IV (pp. 21–36). Bethesda, MD: National Association of School Psychologists.Google Scholar
  46. Witt, J. C., Daly, E. J., III, & Noell, G. H. (2000). Functional assessments: A step-by-step guide to solving academic and behavior problems. Longmont, CO: Sopris West.Google Scholar
  47. Ysseldyke, J. E., Algozzine, B., Shinn, N., & McGue, M. (1982). Similarities and differences between underachievers and students labeled learning-disabled. The Journal of Special Education, 16, 73–85.CrossRefGoogle Scholar
  48. Ysseldyke, J. E., & Marston, D. (1999). Origins of categorical special education services in schools. In D. J. Reschly, W. D. Tilly III, & J. P. Grimes (Eds.), Special education in transition: Functional assessment and noncategorical programming (pp. 1–18). Longmont, CO: Sopris West.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Christine E. Neddenriep
    • 1
  • Brian C. Poncy
  • Christopher H. Skinner
  1. 1.The University of Wisconsin-WhitewaterWhitewaterUSA

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