Advertisement

Assessment: Periodic Assessment to Monitor Progress

  • Benjamin SilberglittEmail author
  • David Parker
  • Paul Muyskens
Chapter

Abstract

Monitoring progress is a critical component of understanding the “response” to tier 2 services in a response-to-intervention (RTI) framework. Frequent, formative assessments are needed that indicate change in a student’s rate of growth, as a result of changes to their instructional environment. Frequent progress monitoring within a multi-tiered system of supports first established itself using fluency of oral reading from connected text, with elementary age students. As the RTI framework has grown, monitoring progress has also expanded to other content areas and grade levels. This chapter first provides a conceptual model to help practitioners consider the balance between general outcome measures and specific skill mastery assessments, both of which have become widely used in formative assessment. Research is presented on different approaches to progress monitoring across different grade levels and content areas, within the context of this new model. Next, the chapter explores the current state of research on oral reading fluency (ORF) as a progress monitoring measure. Using ORF as an example, the chapter examines four key issues that are especially relevant to understanding the technical limitations of a progress monitoring assessment: reliability and validity of change, sensitivity of change, linearity of change, and standards and expectations for change. The chapter reviews the current state of research, directions for future research, and implications for practice.

Keywords

Progress Monitoring Oral Reading Fluency Curricular Goal Vocabulary Intervention General Outcome Measurement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Anderson, R. C., & Nagy, W. E. (1992). The vocabulary conundrum. American Educator, 16(4), 14–18, 44–47.Google Scholar
  2. Andren, K. J. (2010). An analysis of the concurrent and predictive validity of curriculum based measures (CBM), the measures of academic progress (MAP), and the New England common assessment program (NECAP) for reading (Doctoral dissertation, University of Southern Maine, 2010). Proquest, Umi Dissertation Publishing, 2011.Google Scholar
  3. Ardoin, S. P., & Christ, T. J. (2008). Evaluating curriculum-based measurement slope estimates using data from triannual universal screenings. School Psychology Review, 37(1), 109–125.Google Scholar
  4. Ardoin, S. P., & Christ, T. J. (2009). Curriculum-based measurement of oral reading: Standard errors associated with progress monitoring outcomes from DIBELS, Aimsweb, and an experimental passage set. School Psychology Review, 38(2), 266–283.Google Scholar
  5. Ardoin, S. P., Christ, T. J., Morena, L. S., Cormier, D. C., & Klingbeil, D. A. (2013). A systematic review and summarization of the recommendations and research surrounding curriculum-based measurement of oral reading fluency (CBM-R) decision rules. Journal of School Psychology, 51(1), 1–18.CrossRefPubMedGoogle Scholar
  6. Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis, 1, 91–97.PubMedCentralCrossRefPubMedGoogle Scholar
  7. Baker, S. K., Smolkowski, K., Katz, R., Hank, F., Seeley, J. R., Kame’enui, E. J., et al. (2008). Reading fluency as a predictor of reading proficiency in low-performing, high-poverty schools. School Psychology Review, 37, 18–37.Google Scholar
  8. Batsche, G., Elliott, J., Graden, J., Grimes, J., Kovaleski, J., Prasse, D., … Tilly, W. D. (2005). Response to intervention: Policy considerations and implementation. Alexandria: National Association of State Directors of Special Education.Google Scholar
  9. Beck, I. L., & McKeown, M. G. (2007). Increasing young low-income children’s oral vocabulary repertoires through rich and focused instruction. The Elementary School Journal, 107(3), 251–271.CrossRefGoogle Scholar
  10. Berninger, V., & Amtmann, D. (2003). Preventing written expression disabilities through early and continuing assessment and intervention for handwriting and/or spelling problems: Research into practice. In H. L. Swanson, K. Harris, & S. Graham (Eds.), Handbook of learning disabilities (pp. 345–363). New York: Guilford.Google Scholar
  11. Bornstein, M. H., & Haynes, M. O. (1998). Vocabulary competence in early childhood: Measurement, latent, construct, and predictive validity. Child Development, 69, 654–671.CrossRefPubMedGoogle Scholar
  12. 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(1), 128–133.Google Scholar
  13. Christ, T. J., & Hintze, J. M. (2007). Psychometric considerations when evaluating response to intervention. In S. Jimerson, M. Burns, & A. VanDerHeyden (Eds.), Handbook of response to intervention: The science and practice of assessment and intervention. New York: Springer.Google Scholar
  14. Christ, T. J., & Silberglitt, B. (2007). Estimates of the standard error of measurement for curriculum-based measurement of oral reading fluency. School Psychology Review, 36(1), 130–146.Google Scholar
  15. Christ, T. J., Burns, M. K., & Ysseldyke, J. E. (2005). Conceptual confusion within response-to-intervention vernacular: Clarifying meaningful differences. NASP Communique, 34(3), 1, 6–8.Google Scholar
  16. Christ, T. J., Silberglitt, B., Yeo, S., & Cormier, D. (2010). Curriculum based measurement of oral reading (CBM-R): An evaluation of linear expectations for growth. School Psychology Review, 39(3), 447–462.Google Scholar
  17. Christ, T. J., Zopluoglu, C., Monaghen, B. D., & Van Norman, E. R. (2012). Curriculum-based measurement of oral reading: Multi-study evaluation of schedule, duration, and dataset quality on progress monitoring outcomes. Journal of School Psychology, 51, 19–57.CrossRefPubMedGoogle Scholar
  18. Clarke, B., & Shinn, M. (2004). A preliminary investigation into the identification and development of early mathematics curriculum-based measurement. School Psychology Review, 33, 234–248.Google Scholar
  19. Clarke, B., Baker, S., Smolkowski, K., & Chard, D. J. (2008). An analysis of early numeracy curriculum-based measurement: Examining the role of growth in student outcomes. Remedial and Special Education, 29(1), 46–57.CrossRefGoogle Scholar
  20. Coker, D. L., & Ritchey, K., D. (2010). Curriculum based measurement of writing in kindergarten and first grade: An investigation of production and qualitative scores. Exceptional Children, 76, 175–193.CrossRefGoogle Scholar
  21. Cone, J. D. (1989). Is there utility for treatment utility? American Psychologist, 44, 1241–1242CrossRefGoogle Scholar
  22. Deno, S. L. (1985). Curriculum-based measurement: The emerging alternative. Exceptional Children, 52, 219–232.PubMedGoogle Scholar
  23. Deno, S. L. (2003). Developments in curriculum-based measurement. The Journal of Special Education, 37, 184–192CrossRefGoogle Scholar
  24. Deno, S. L., & Mirkin, P. K. (1977) Data-based program modification: A manual. Reston: Council for Exceptional Children.Google Scholar
  25. Eckert, T. L., Ardoin, S. P., Daly, E. J., & Martens, B. K. (2002). Improving oral reading fluency: A brief experimental analysis of combining an antecedent intervention with consequences. Journal of Applied Behavior Analysis, 35(3), 271–281.PubMedCentralCrossRefPubMedGoogle Scholar
  26. Espin, C. A., Shin, J., & Busch, T. W. (2005). Curriculum-based measurement in content areas: Vocabulary matching as an indicator of progress in social studies learning. Journal of Learning Disabilities, 38, 353–363.CrossRefPubMedGoogle Scholar
  27. Evans, M.A., Bell, M., Shaw, D., Moretti, S., & Page, J. (2006). Letter names, letter sounds and phonological awareness: An examination of kindergarten children across letters and of letters across children. Reading and Writing, 19, 959–989. doi:10.1007/s11145-006-9026-x.CrossRefGoogle Scholar
  28. Foegen, A., Jiban, C., & Deno, S. (2007). Progress monitoring measures in mathematics a review of the literature. The Journal of Special Education, 41(2), 121–139.CrossRefGoogle Scholar
  29. Fuchs, L. S. (2004). The past, present, and future of curriculum-based measurement research. School Psychology Review, 33, 188–192.Google Scholar
  30. Fuchs, L. S., & Deno, S. L., (1991). Paradigmatic distinctions between instructionally relevant measurement models. Exceptional Children, 57, 488–500.Google Scholar
  31. Fuchs, L. S., & Deno, S. L., (1992). Effects of curriculum within curriculum-based measurement. Exceptional Children, 58, 232–243.Google Scholar
  32. Fuchs, L. S., & Deno, S. L. (1994). Must instructionally useful performance assessment be based in the curriculum? Exceptional Children, 61, 15–24.Google Scholar
  33. Fuchs, L., & Fuchs, D. (1998). Treatment validity: A unifying concept for reconceptualizing the identification of learning disabilities. Learning Disabilities Research & Practice, 13, 204–219.Google Scholar
  34. Fuchs, D., & Fuchs, L. S. (2006). Introduction to response to intervention: What, why, and how valid is it? Reading Research Quarterly, 41(1), 93–99.CrossRefGoogle Scholar
  35. Fuchs, L. S., Deno, S. L., & Mirkin, P. K. (1984). The effects of frequent curriculum-based measurement and evaluation on student achievement, pedagogy, and student awareness of learning. American Educational Research Journal, 21, 449–460.CrossRefGoogle Scholar
  36. Fuchs, L. S., Allinder, R. M., & Fuchs, D. (1990). Drawing measurement samples from the curriculum. Effects of instructional planning and student achievement. Unpublished manuscript. based reading practices for response to intervention. Baltimore: Paul H. Brookes Publishing Co.Google Scholar
  37. Fuchs, L. S., Fuchs, D., Hamlett, C. L., & Ferguson, C. (1992). Effects of expert based system consultation within curriculum-based measurement using a reading maze task. Exceptional Children, 58, 436–450.Google Scholar
  38. 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
  39. Good, R. H., Kaminski, R. A., Dewey, E. N., Wallin, J., Powell-Smith, K. A., & Latimer, R. J. (2013). DIBELS Next Technical Manual. Eugene: Dynamic Measurement Group.Google Scholar
  40. Graney, S. B., Missall, K. N., MaRtInez, R. S., & Bergstrom, M. (2009). A preliminary investigation of within-year growth patterns in reading and mathematics curriculum-based measures. Journal of School Psychology, 47, 121–142.CrossRefPubMedGoogle Scholar
  41. Hintze, J. M., & Silberglitt, B. (2005). A longitudinal examination of the diagnostic accuracy and predictive validity of R-CBM and high stakes testing. School Psychology Review, 34, 372–386.Google Scholar
  42. Hintze, J. M., Christ, T. J., & Methe, S. A. (2006). Curriculum-based assessment. Psychology in the Schools, 43, 45–56.Google Scholar
  43. Hojnoski, R. L., Silberglitt, B., & Floyd, R. G. (2009). Sensitivity to growth over time of the preschool numeracy indicators with a sample of preschoolers in head start. School Psychology Review, 38, 402–418.Google Scholar
  44. Jenkins, J. R., & Fuchs, L. S. (2012). Curriculum-based measurement: The paradigm, history and legacy. In C. Espin, K. McMaster, S. Rose, & M. Wayman (Eds.), A measure of success: The influence of curriculum-based measurement on education. University of MN Press, Minneapolis.Google Scholar
  45. Loftus, S., Coyne, M. D., McCoach, D. B., Zipoli, R., Kapp, S., & Pullen, P. (2010). Effects of a supplemental vocabulary intervention on the word knowledge of kindergarten students at-risk for language and literacy difficulties. Learning Disabilities Research & Practice, 25(3), 124–136.CrossRefGoogle Scholar
  46. Marston, D. (1989). A curriculum-based measurement approach to assessing academic performance: What is it and why do it. In M. Shinn (Ed.), Curriculum-based measurement: Assessing special children (pp. 18–78). New York: Guilford.Google Scholar
  47. McGlinchey, M. T., & Hixson, M. D. (2004). Using curriculum-based measurement to predict performance on state assessments in reading. School Psychology Review, 33, 193–203.Google Scholar
  48. McMaster, K., & Espin, C. (2007). Technical features of curriculum-based measurement in writing a literature review. The Journal of Special Education, 41(2), 68–84.CrossRefGoogle Scholar
  49. McMaster, K. L., Du, X., & Petursdottir, A. (2009). Technical features of curriculum-based measures for beginning writers. Journal of Learning Disabilities, 42, 41–60.CrossRefPubMedGoogle Scholar
  50. McMaster, K. L., Du, X., Yeo, S., Deno, S. L., Parker, D., & Ellis, T. (2011). Curriculum-based measures of beginning writing: Technical features of the slope. Exceptional Children, 77, 185–206.CrossRefGoogle Scholar
  51. Messick, S. (1981). Constructs and their vicissitudes in educational and psychological measurement. Psychological Bulletin, 89, 575–588.CrossRefGoogle Scholar
  52. Messick, S. (1994). The interplay of evidence and consequences in the validation of performance assessments. Educational Researcher, 23(2), 13–23.CrossRefGoogle Scholar
  53. Missall, K. N., Reschly, A., Betts, J., McConnell, S., Heistad, D., Pickart, M., et al. (2007). Examination of the predictive validity of preschool early literacy skills. School Psychology Review, 36, 433–452.Google Scholar
  54. Nagy, W., E., & Anderson, R., C. (1984). How many words are there in printed school English? Reading Research Quarterly, 19, 304–330.CrossRefGoogle Scholar
  55. National Center on Response to Intervention. (2010). Brief #3. Common progress monitoring graph omissions: Making instructional decisions. Washington, DC: US Department of Education, Office of Special Education Programs. http://www.RtI4success.org. Accessed 14 May 2010.Google Scholar
  56. National Center on Response to Intervention. (2010). Progress monitoring tools Chart: Reading and Math. http://www.RtI4success.org/chart/progressMonitoring/PMToolsChart_04-20-10a.pdf. Accessed 14 May 2010.
  57. National Center on Intensive Intervention. (2013). Academic progress monitoring tool. http://www.intensiveintervention.org/chart/progress-monitoring. Accessed 20 Dec 2013.
  58. National Reading Panel. (2000). 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. Bethesda: National Institute of Child Health and Human Development.Google Scholar
  59. Northwest Evaluation Association. (2011). RIT Scale Norms Study. Portland: NWEA.Google Scholar
  60. Northwest Evaluation Association. (2013). Measures of academic progress. Portland: NWEA.Google Scholar
  61. Pearson. (2012). AIMSweb progress monitoring and improvement system. http://www.aimsweb.com/. Accessed 29 Dec 2012.
  62. Pullen, P. C., Tuckwiller, E. D., Konold, T. R., Maynard, K. L., & Coyne, M. (2010). A tiered intervention model for early vocabulary instruction: The effects of tiered instruction for young students at risk for reading disability. Learning Disabilities Research & Practice, 25, 110–122.CrossRefGoogle Scholar
  63. RAND Reading Study Group. (2002). Reading for understanding: Toward an R & D program in reading comprehension. Santa Monica: RAND.Google Scholar
  64. Reschly, A. L., Busch, T. W., Betts, J., Deno, S. L., & Long, J. (2009). Curriculum-based measurement oral reading as an indicator of reading achievement: A meta-analysis of the correlational evidence. Journal of School Psychology, 47, 427–469.CrossRefPubMedGoogle Scholar
  65. Schatschneider, C., Wagner, R. K., & Crawford, E. C. (2008). The importance of measuring growth in response to intervention models: Testing a core assumption. Learning and Individual Differences, 18(3), 308–315.PubMedCentralCrossRefPubMedGoogle Scholar
  66. Shapiro, E. S. (2013). Commentary on progress monitoring with CBM-R and decision making: Problems found and looking for solutions. Journal of School Psychology, 51(1), 59–66.CrossRefPubMedGoogle Scholar
  67. Shapiro, E. S., Keller, M. A., Lutz, J. G., Santoro, L. E., & Hintze, J. M. (2006). Curriculum-based measures and performance on state assessment and standardized tests: Reading and math performance in Pennsylvania. Journal of Psychoeducational Assessment, 24(1), 19–35.CrossRefGoogle Scholar
  68. Shapiro, E. S., Hilt-Panahon, A., Gischlar, K. L., Devlin, K., Leichman, E., & Bwles, S. (2012). An analysis of consistency between team decisions and reading assessment data within an RTI Model. Remedial and Special Education, 33, 335–347.CrossRefGoogle Scholar
  69. Shin, J., Deno, S. L., & Espin, C. (2000). Technical adequacy of maze task for curriculum-based measurement of reading growth. Journal of Special Education, 34, 164–173.CrossRefGoogle Scholar
  70. Shinn, M. R. (1989). Identifying and defining academic problems: CBM screening and eligibility procedures. In M. R. Shinn (Ed.), Curriculum-based measurement: Assessing special children (pp. 90–129). New York: Guilford.Google Scholar
  71. Silberglitt, B. (2009). Curriculum Based Measurement of Oral Reading (CBM-R): An Evaluation of Growth Rates and Season Effects among Students Served in General and Special Education (Unpublished Manuscript).Google Scholar
  72. Silberglitt, B., & Hintze, J. M. (2007). How much growth can we expect? A conditional analysis of R-CBM growth rates by level of performance. Exceptional Children, 74(1), 71–84.CrossRefGoogle Scholar
  73. Silberglitt, B., Burns, M. K., Madyn, N. H., & Lail, K. E. (2006). Relationship of reading fluency assessment data with state accountability test scores: A longitudinal comparison of grade levels. Psychology in the Schools, 43, 527–536.CrossRefGoogle Scholar
  74. Stage, S. A., & Jacobsen, M. D. (2001). Predicting student success on a state-mandated performance-based assessment using oral reading fluency. School Psychology Review, 30, 407–419.Google Scholar
  75. Stahl, S. A., & Nagy, W. E. (2006). Teaching word meanings. Mahwah: ErlbaumGoogle Scholar
  76. Stecker, P. M., Fuchs, L. S., & Fuchs, D. (2005). Using curriculum-based measurement to improve student achievement: Review of research. Psychology in the Schools, 42, 795–819.CrossRefGoogle Scholar
  77. Stecker, P. M., Fuchs, D., & Fuchs, L. S. (2008). Progress monitoring as essential practice within response to intervention. Rural Special Education Quarterly, 27(4), 10–17.Google Scholar
  78. Tindal, G., Marston, D., & Deno, S. (1983). The reliability of direct and repeated measurement (Research Report No. 109). Minneapolis: University of Minnesota, Institute for Research on Learning Disabilities.Google Scholar
  79. Tucker, J. A. (1985). Curriculum-based assessment: An introduction. Exceptional Children, 52, 199–204.PubMedGoogle Scholar
  80. University of Oregon Center on Teaching and Learning. (2012). 2012-2013 DIBELS data system update part I: DIBELS next composite score (Technical Brief No. 1202). Eugene: University of Oregon.Google Scholar
  81. Vannest, K. J., Parker, R., & Dyer, N. (2011). Progress monitoring in grade 5 science for low achievers. The Journal of Special Education, 44(4), 221–233.CrossRefGoogle Scholar
  82. Wanzek, J., Roberts, G., Linan-Thompson, S., Vaughn, S., Woodruff, A. L., & Murray, C. S. (2010). Differences in relationship of oral reading fluency and high-stakes measures of reading comprehension. Assessment for Effective Instruction, 35(2), 67–77.CrossRefGoogle Scholar
  83. Wayman, M. M., Wallace, H. I., Wiley, S., Ticha, R., & Espin, C. (2007). Literature synthesis on Curriculum-Based Measurement in reading. Journal of Special Education, 41, 85–120.CrossRefGoogle Scholar
  84. Wiley, H. I., & Deno, S. L. (2005). Oral reading and maze measures as predictors of success for English learners on a state standards assessment. Remedial and Special Education, 26, 207–214.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Benjamin Silberglitt
    • 1
    Email author
  • David Parker
    • 2
  • Paul Muyskens
    • 1
  1. 1.TIESSaint PaulUSA
  2. 2.ServeMinnesotaMinneapolisUSA

Personalised recommendations