Table of Contents
ISRN Education
Volume 2013 (2013), Article ID 958530, 29 pages
http://dx.doi.org/10.1155/2013/958530
Review Article

Curriculum-Based Measurement: A Brief History of Nearly Everything from the 1970s to the Present

College of Education, University of Oregon, Eugene, OR 97403, USA

Received 8 October 2012; Accepted 13 November 2012

Academic Editors: N. Dumais, F. Jimenez, and L. McCall

Copyright © 2013 Gerald Tindal. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. S. Messick, “Standards of validity and the validity of standards in performance assessment,” Educational Measurement, vol. 14, no. 4, pp. 5–8, 1995. View at Publisher · View at Google Scholar
  2. M. Kane, “Validation,” in Educational Measurement, R. Brennan, Ed., pp. 17–64, American Council on Education and Praeger, Westport, Conn, USA, 4th edition, 2006. View at Google Scholar
  3. L. S. Fuchs, “The past, present, and future of curriculum-based measurement research,” School Psychology Review, vol. 33, no. 2, pp. 188–192, 2004. View at Google Scholar · View at Scopus
  4. American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, Standards for Educational and Psychological Testing, Amer Psychological Association, Washington, DC, USA, 1999.
  5. S. Deno and P. Mirkin, Data Based Program Modification: A Manual, Leadership Training Institute for Special Education, Minneapolis, Minn, USA, 1977.
  6. G. Tindal and J. F. T. Nese, “Applications of curriculum-based measures in making multiple decisions with multiple reference points,” in Assessment and Intervention: Advances in Learning and Behavioral Disabilities, M. M. T. Scruggs, Ed., vol. 24, pp. 31–58, Emerald, Bingley, UK, 2011. View at Google Scholar
  7. P. Mirkin, S. Deno, G. Tindal, and K. Kuehnle, “Formative evaluation: continued development of data utilization systems,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1980. View at Google Scholar
  8. B. Meyers, J. Meyers, and S. Deno, “Formative evaluation and teacher decision-making: a follow-up investigation,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1980. View at Google Scholar
  9. S. Deno and P. Mirkin, Data-Based IEP Development: An Approach to Substantive Compliance, Monograph, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1979.
  10. G. Tindal, L. Fuchs, S. Christenson, P. Mirkin, and S. Deno, “The relationship between student achievement and teacher assessment of short or long-term goals,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1981. View at Google Scholar
  11. S. Deno, P. Mirkin, and M. Shinn, Behavioral Perspectives on the Assessment of Learning Disabled Children, Monograph, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1979.
  12. J. R. Jenkins, S. Deno, and P. Mirkin, Measuring Pupil Progress Toward the Least Restrictive Environment, Monograph, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1979.
  13. L. Fuchs and S. Deno, “The relationship between curriculum-based mastery measures and standardized achievement tests in reading,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1981. View at Google Scholar
  14. L. Fuchs, G. Tindal, D. Fuchs, M. Shinn, S. Deno, and G. Germann, “The technical adequacy of a basal reading mastery test: the Holt reading series,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1983. View at Google Scholar
  15. L. Fuchs, G. Tindal, M. Shinn, D. Fuchs, and G. Germann, “Technical adequacy of basal readers' mastery tests: the Ginn 720 series,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1983. View at Google Scholar
  16. G. Tindal, L. Fuchs, D. Fuchs, M. Shinn, S. Deno, and G. Germann, “The technical adequacy of a basal series mastery test: the Scott-Foresman reading program,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1983. View at Google Scholar
  17. G. Tindal, M. Shinn, L. Fuchs, D. Fuchs, S. Deno, and G. Germann, “The technical adequacy of a base reading series mastery test,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1983. View at Google Scholar
  18. D. Fuchs and S. Deno, “Reliability and validity of curriculum-based informal reading inventories,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1981. View at Google Scholar
  19. L. Fuchs, D. Fuchs, and S. Deno, “The nature of inaccuracy among readability formulas,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1983. View at Google Scholar
  20. L. Fuchs and S. Deno, “A comparison of reading placement based on teacher judgment, standardized testing, and curriculum-based assessment,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1981. View at Google Scholar
  21. L. Fuchs, S. Deno, and P. Mirkin, “Direct and frequent measurement and evaluation: effects on instruction and estimates of student progress,” Research Report, Minneapolis, Minn, USA, 1982. View at Google Scholar
  22. L. Fuchs, S. Deno, and P. Mirkin, “Effects of frequent curriculum-based measurement and evaluation on student achievement and knowledge of performance: an experimental study,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1982. View at Google Scholar
  23. L. Fuchs, S. Deno, and A. Roettger, “The effect of alternative data-utilization rules on spelling achievement,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1983. View at Google Scholar
  24. L. Fuchs, C. Wesson, G. Tindal, P. Mirkin, and S. Deno, “Instructional changes, student performances, and teacher preferences: the effects of specific measurement and evaluation procedures,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1982. View at Google Scholar
  25. P. Mirkin and S. Deno, “Formative evaluation in the classroom: an approach to improving instruction,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1979. View at Google Scholar
  26. P. Mirkin, L. Fuchs, G. Tindal, S. Christenson, and S. Deno, “The effect of IEP monitoring strategies on teacher behavior,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1981. View at Google Scholar
  27. B. Sevcik, R. Skiba, G. Tindal et al., “Curriculum-based measurement: effects on instruction, teacher estimates of student progress and student knowledge of performance,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1983. View at Google Scholar
  28. C. Wesson, S. Deno, P. Mirkin et al., “Teaching structure and student achievement effects of curriculum-based measurement: a casual (structural) analysis,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1982. View at Google Scholar
  29. C. Wesson, P. Mirkin, and S. Deno, “Teachers' use of self-instructional materials for learning procedures for developing and monitoring progress on IEP goals,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1982. View at Google Scholar
  30. C. Wesson, R. Skiba, B. Sevcik et al., “The impact of the structure of instruction and the use of technically adequate instructional data on reading improvement,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1983. View at Google Scholar
  31. M. Shinn, R. Good, and S. Stein, “Summarizing trend in student achievement: a comparison of methods,” School Psychology Review, vol. 18, no. 3, pp. 356–370, 1989. View at Google Scholar
  32. R. Skiba and S. Deno, “A correlational analysis of the statistical properties of time-series data and their relationship to student achievement in resource classrooms,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1983. View at Google Scholar
  33. R. Skiba, D. Marston, C. Wesson, B. Sevcik, and S. Deno, “Characteristics of the time-series data collected through curriculum-based reading measurement,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1983. View at Google Scholar
  34. G. Tindal, S. Deno, and J. Ysseldyke, “Visual analysis of time series data: factors of influence and level reliability,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1983. View at Google Scholar
  35. D. Marston, L. Lowry, S. Deno, and P. Mirkin, “An analysis of learning trends in simple measures of reading, spelling, and written expression: a longitudinal study,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1981. View at Google Scholar
  36. R. King, S. Deno, P. Mirkin, and C. Wesson, “The effects of training in the use of formative evaluation in reading: an experimental control comparison,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1983. View at Google Scholar
  37. R. Skiba, C. Wesson, and S. Deno, “The effects of training teachers in the use of formative evaluation in reading: an experimental control comparison,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1982. View at Google Scholar
  38. L. Fuchs, C. Wesson, G. Tindal, P. Mirkin, and S. Deno, “Teacher efficiency in continuous evaluation of IEP goals,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1981. View at Google Scholar
  39. R. King, C. Wesson, and S. Deno, “Direct and frequent measurement of student performance: does it take too much time?” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1982. View at Google Scholar
  40. D. Marston and S. Deno, “Implementation of direct and repeated measurement in the school setting,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1982. View at Google Scholar
  41. D. Marston, G. Tindal, and S. Deno, “Predictive efficiency of direct, repeated measurement: an analysis of cost and accuracy in classification,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1982. View at Google Scholar
  42. P. Mirkin, D. Marston, and S. Deno, “Direct and repeated measurement of academic skills: an alternative to traditional screening referral, and identification of learning disabled students,” Research Reports, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1982. View at Google Scholar
  43. G. Tindal, G. Germann, and S. Deno, “Descriptive research on the Pine County norms: a compilation of findings,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1983. View at Google Scholar
  44. G. Tindal, G. Germann, D. Marston, and S. Deno, “The effectiveness of special education,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1983. View at Google Scholar
  45. L. Fuchs, G. Tindal, and S. Deno, “Effects of varying item domain and sample duration on technical characteristics of daily measures in reading,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1981. View at Google Scholar
  46. M. Shinn, M. Gleason, and G. Tindal, “Varying the difficulty of testing materials: implications for curriculum-based measurement,” The Journal of Special Education, vol. 23, pp. 223–233, 1989. View at Publisher · View at Google Scholar
  47. G. Tindal and S. Deno, “Daily measurement of reading: effects of varying the size of the item pool,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1981. View at Google Scholar
  48. G. Tindal, D. Marston, S. Deno, and G. Germann, “Curriculum differences in direct repeated measures of reading,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1982. View at Google Scholar
  49. S. Deno, D. Marston, P. Mirkin, L. Lowry, P. Sindelar, and J. R. Jenkins, The Use of Standard Tasks to Measure Achievement in Reading, Spelling, and Written Expression: A Normative and Developmental Study, Institute for Research on Learning Disabilities, Minneapolis, Minn, USA, 1982.
  50. S. Deno, P. Mirkin, B. Chiang, and L. Lowry, “Relationships among simple measures of reading and performance on standardized achievement tests,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1980. View at Google Scholar
  51. S. Deno, P. Mirkin, L. Lowry, and K. Kuehnle, “Relationships among simple measures of spelling and performance on standardized achievement tests,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1980. View at Google Scholar
  52. S. Deno, P. Mirkin, and D. Marston, “Relationships among simple measures of written expression and performance on standardized achievement tests,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1980. View at Google Scholar
  53. L. Fuchs, S. Deno, and D. Marston, “Use of aggregation to improve the reliability of simple direct measures of academic performance,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1982. View at Google Scholar
  54. D. Marston and S. Deno, “The reliability of simple, direct measures of written expression,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1981. View at Google Scholar
  55. G. Tindal, D. Marston, and S. Deno, “The reliability of direct and repeated measurement,” Research Report, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1983. View at Google Scholar
  56. J. Videen, S. Deno, and D. Marston, “Correct word sequences: a valid indicator of proficiency in written expression,” Research Reports, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1982. View at Google Scholar
  57. C. Wesson, S. Deno, and P. Mirkin, Research on Developing and Monitoring Progress on IEP Goals: Current Findings and Implications for Practice, Monograph, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1982.
  58. G. Tindal, G. Germann, S. Deno, and P. Mirkin, The Pine County Model for Special Education Delivery: A Data-Based System, Monograph, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1982.
  59. P. K. Mirkin, L. S. Fuchs, and S. L. Deno, Consideration for Designing a Continuous Evaluation : An Interpretive Review, Monograph, Institute for Research on Learning Disabilities (IRLD), University of Minnesota, Minneapolis, Minn, USA, 1982.
  60. M. R. Shinn, Curriculum-Based Measurement: Assessing Special Children, The Guilford Press, New York, NY, USA, 1989.
  61. M. R. Shinn, Advanced Applications of Curriculum-Based Measurement, Guilford Press, New York, NY, USA, 1998.
  62. G. Tindal and D. Marston, Classroom-Based Assessment: Evaluating Instructional Outcomes, Merrill, Columbus, Ohio, USA, 1990.
  63. E. E. Gickling and V. P. Thompson, “A personal view of curriculum-based assessment,” Exceptional Children, vol. 52, no. 3, pp. 205–218, 1985. View at Google Scholar · View at Scopus
  64. K. Howell, Curriculum-Based Evaluation for Special and Remedial Education: A Handbook for Deciding What to Teach, Merrill Publishing, Columbus, Ohio, USA, 1987.
  65. C. S. Blankenship, “Using curriculum-based assessment data to make instructional decisions,” Exceptional Children, vol. 52, no. 3, pp. 233–238, 1985. View at Google Scholar · View at Scopus
  66. M. R. Shinn, S. Rosenfield, and N. Knutson, “Curriculum-based assessment: a comparison of models,” School Psychology Review, vol. 18, no. 3, pp. 299–316, 1989. View at Google Scholar
  67. C. A. Espin, K. L. McMaster, S. Rose, and M. M. Wayman, A Measure of Success: How Curriculum-Based Measurement has Influenced Education and Learning, University of Minnesota Press, Minneapolis, Minn, USA, 2012.
  68. G. Tindal and J. F. T. Nese, “Within year achievement growth using curriculum based measurement,” in Proceedings of the National Council on Measurement in Education, Vancouver, Canada, April 2012.
  69. L. Fuchs, D. Fuchs, C. Hamlett, L. Walz, and G. Germann, “Formative evaluation of academic progress: how much growth can we expect?” School Psychology Review, vol. 22, pp. 27–48, 1993. View at Google Scholar
  70. S. L. Deno, L. S. Fuchs, D. Marston, and J. Shin, “Using curriculum-based measurement to establish growth standards for students with learning disabilities,” School Psychology Review, vol. 30, no. 4, pp. 507–524, 2001. View at Google Scholar · View at Scopus
  71. S. P. Ardoin and T. J. Christ, “Evaluating curriculum-based measurement slope estimates using data from triannual universal screenings,” School Psychology Review, vol. 37, no. 1, pp. 109–125, 2008. View at Google Scholar · View at Scopus
  72. T. J. Christ, “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, vol. 35, no. 1, pp. 128–133, 2006. View at Google Scholar · View at Scopus
  73. T. J. Christ, B. Silberglitt, S. Yeo, and D. Cormier, “Curriculum-based measurement of oral reading: an evaluation of growth rates and seasonal effects among students served in general and special education,” School Psychology Review, vol. 39, no. 3, pp. 447–462, 2010. View at Google Scholar · View at Scopus
  74. S. B. Graney, K. N. Missall, R. S. Martínez, and M. Bergstrom, “A preliminary investigation of within-year growth patterns in reading and mathematics curriculum-based measures,” Journal of School Psychology, vol. 47, no. 2, pp. 121–142, 2009. View at Publisher · View at Google Scholar · View at Scopus
  75. J. R. Jenkins, J. J. Graff, and D. L. Miglioretti, “Estimating reading growth using intermittent CBM progress monitoring,” Exceptional Children, vol. 75, no. 2, pp. 151–163, 2009. View at Google Scholar · View at Scopus
  76. J. Jenkins and K. Terjeson, “Monitoring reading growth: goal setting, measurement frequency, and methods of evaluation,” Learning Disabilities Research & Practice, vol. 26, no. 1, pp. 28–35, 2011. View at Google Scholar
  77. J. F. T. Nese, G. Biancarosa, D. Anderson, C. F. Lai, J. Alonzo, and G. Tindal, “Within-year oral reading fluency with CBM: a comparison of models,” Reading and Writing, vol. 25, no. 4, pp. 887–915, 2012. View at Publisher · View at Google Scholar · View at Scopus
  78. S. Raudenbush, A. Bryk, Y. Cheong, and R. Congdon, HLM 6: Hierarchical Linear and NonLinear Modeling, Scientific Software International, Lincolnwood, Ill, USA, 2004.
  79. S. Raudenbush and A. Bryk, Hierarchical Linear Models: Applications and Data Analysis Methods, Sage Publications, Thousand Oaks, Calif, USA, 2nd edition, 2002.
  80. R. Brennan, Generalizability Theory, Springer, New York, NY, USA, 2001.
  81. R. Linn and E. Burton, “Performance-based assessment: implications of task specificity,” Educational Measurement, vol. 13, pp. 5–8, 1994. View at Google Scholar
  82. J. M. Hintze, E. J. Daly, and E. S. Shapiro, “An investigation of the effects of passage difficulty level on outcomes of oral reading fluency progress monitoring,” School Psychology Review, vol. 27, no. 3, pp. 433–445, 1998. View at Google Scholar · View at Scopus
  83. J. M. Hintze and T. J. Christ, “An examination of variability as a function of passage variance in CBM progress monitoring,” School Psychology Review, vol. 33, no. 2, pp. 204–217, 2004. View at Google Scholar · View at Scopus
  84. J. M. Hintze, S. V. Owen, E. S. Shapiro, and E. J. Daly, “Research design and methodology section—generalizability of oral reading fluency measures: application of g theory to curriculum-based measurement,” School Psychology Quarterly, vol. 15, no. 1, pp. 52–68, 2000. View at Google Scholar · View at Scopus
  85. B. C. Poncy, C. H. Skinner, and P. K. Axtell, “An investigation of the reliability and standard error of measurement of words read correctly per minute using curriculum-based measurement,” Journal of Psychoeducational Assessment, vol. 23, no. 4, pp. 326–338, 2005. View at Publisher · View at Google Scholar · View at Scopus
  86. T. J. Christ and S. P. Ardoin, “Curriculum-based measurement of oral reading: passage equivalence and probe-set development,” Journal of School Psychology, vol. 47, no. 1, pp. 55–75, 2009. View at Publisher · View at Google Scholar · View at Scopus
  87. S. P. Ardoin and T. J. Christ, “Curriculum-based measurement of oral reading: standard errors associated with progress monitoring outcomes from DIBELS, AIMSweb, and an experimental passage set,” School Psychology Review, vol. 38, no. 2, pp. 266–283, 2009. View at Google Scholar · View at Scopus
  88. D. J. Francis, K. L. Santi, C. Barr, J. M. Fletcher, A. Varisco, and B. R. Foorman, “Form effects on the estimation of students' oral reading fluency using DIBELS,” Journal of School Psychology, vol. 46, no. 3, pp. 315–342, 2008. View at Publisher · View at Google Scholar · View at Scopus
  89. T. Christ, “Curriculum-based measurement of oral reading: multi-study evaluation of schedule, duration and dataset quality on progress monitoring outcomes,” Journal of School Psychology, vol. 78, no. 3, 2012. View at Google Scholar
  90. D. C. Briggs, “Synthesizing causal inferences,” Educational Researcher, vol. 37, no. 1, pp. 15–22, 2008. View at Publisher · View at Google Scholar
  91. National Institute for Literacy, Developing Early Literacy: Report of the National Early Literacy Panel (A Scientific Synthesis of Early Literacy Development and Implications for Intervention), Washington, DC, USA, 2008.
  92. R. C. Anderson, E. H. Hiebert, J. A. Scott, and I. A. G. Wilkinson, Becoming a Nation of Readers: The Report of the Commission on Reading, National Institute of Education, Washington, DC, USA, 1985.
  93. National Institutes of Child Health and Human Development, “Report of national reading panel: teaching children to read: an evidence-based assessment of the scientific literature on reading and its implications for reading instruction,” Report of the Subgroups, Washington, DC, USA, 2000. View at Google Scholar
  94. No Child Left Behind, Committee on Education and Labor, Government Printing Office, Washington, DC, USA, 1st edition, 2001.
  95. M. J. Adams, Beginning to Read: Thinking and Learning about Print, MIT Press, Cambridge, Mass, USA, 1990.
  96. L. S. Fuchs, D. Fuchs, and D. L. Compton, “Monitoring early reading development in first grade: word identification fluency versus nonsense word fluency,” Exceptional Children, vol. 71, no. 1, pp. 7–21, 2004. View at Google Scholar · View at Scopus
  97. K. D. Ritchey and D. L. Speece, “From letter names to word reading: the nascent role of sublexical fluency,” Contemporary Educational Psychology, vol. 31, no. 3, pp. 301–327, 2006. View at Publisher · View at Google Scholar · View at Scopus
  98. K. D. Ritchey, “Assessing letter sound knowledge: a comparison of letter sound fluency and nonsense word fluency,” Exceptional Children, vol. 74, no. 4, pp. 487–506, 2008. View at Google Scholar · View at Scopus
  99. P. G. Aaron, R. Malatesha Joshi, R. Gooden, and K. E. Bentum, “Diagnosis and treatment of reading disabilities based on the component model of reading: an alternative to the discrepancy model of LD,” Journal of Learning Disabilities, vol. 41, no. 1, pp. 67–84, 2008. View at Publisher · View at Google Scholar · View at Scopus
  100. D. Starch, “The measurement of efficiency in reading,” The Journal of Educational Psychology, vol. 6, no. 1, pp. 1–24, 1915. View at Publisher · View at Google Scholar
  101. V. L. Anderson and M. A. Tinker, “The speed factor in reading performance,” Journal of Educational Psychology, vol. 27, no. 8, pp. 621–624, 1936. View at Publisher · View at Google Scholar · View at Scopus
  102. D. LaBerge and S. J. Samuels, “Toward a theory of automatic information processing in reading,” Cognitive Psychology, vol. 6, no. 2, pp. 293–323, 1974. View at Google Scholar · View at Scopus
  103. R. Good, D. Simmons, and E. Kame'enui, “The importance and decision-making utility of a continuum of fluency-based indicators of foundational reading skills for third-grade high-stakes outcomes,” Scientific Studies of Reading, vol. 5, no. 3, pp. 257–288, 2001. View at Publisher · View at Google Scholar
  104. R. H. Good, J. Gruba, and R. A. Kaminski, “Best practices in using Dynamic Indicators of Basic Early Literacy Skills (DIBELS) in an outcomes-driven model,” in Best Practices in School Psychology IV, A. Thomas and J. Grimes, Eds., pp. 679–700, National Association of School Psychologists, Washington, DC, USA, 2001. View at Google Scholar
  105. R. H. Good and R. A. Kaminski, “Assessment for instructional decisions: toward a proactive/prevention model of decision-making for early literacy skills,” School Psychology Quarterly, vol. 11, no. 4, pp. 326–336, 1996. View at Google Scholar · View at Scopus
  106. H. L. Rouse and J. W. Fantuzzo, “Validity of the dynamic indicators for basic early literacy skills as an indicator of early literacy for urban kindergarten children,” School Psychology Review, vol. 35, no. 3, pp. 341–355, 2006. View at Google Scholar · View at Scopus
  107. N. Clemens, E. Shapiro, and F. Thoemmes, “Improving the efficacy of first grade reading screening: an investigation of word identification fluency with other early literacy indicators,” School Psychology Quarterly, vol. 26, no. 3, pp. 231–244, 2011. View at Publisher · View at Google Scholar
  108. S. Hagan-Burke, M. Burke, and C. Crowder, “The convergent validity of the dynamic indicators of basic and early literacy skills and the test of word reading efficiency for the beginning of first grade,” Assessment for Effective Intervention, vol. 31, no. 4, pp. 1–15, 2006. View at Publisher · View at Google Scholar
  109. Y. Y. Lo, C. Wang, and S. Haskell, “Examining the impacts of early reading intervention on the growth rates in basic literacy skills of at-risk urban kindergarteners,” The Journal of Special Education, vol. 43, no. 1, pp. 12–28, 2009. View at Publisher · View at Google Scholar · View at Scopus
  110. U. Yesil-Dagli Ummuhan, “Predicting ELL students' beginning first grade English oral reading fluency from initial kindergarten vocabulary, letter naming, and phonological awareness skills,” Early Childhood Research Quarterly, vol. 26, no. 1, pp. 15–29, 2011. View at Publisher · View at Google Scholar · View at Scopus
  111. L. C. Ehri, S. R. Nunes, D. M. Willows, B. V. Schuster, Z. Yaghoub-Zadeh, and T. Shanahan, “Phonemic awareness instruction helps children learn to read: evidence from the National Reading Panels meta-analysis,” Reading Research Quarterly, vol. 36, no. 3, pp. 250–287, 2001. View at Publisher · View at Google Scholar · View at Scopus
  112. S. Stage, J. Sheppard, M. Davidson, and M. Browning, “Prediction of first-graders' growth in oral reading fluency using kindergarten letter fluency,” Journal of School Psychology, vol. 39, pp. 225–237, 2001. View at Publisher · View at Google Scholar
  113. H. Yopp, “A test for assessing phonemic awareness in young children,” The Reading Teacher, vol. 49, no. 1, pp. 20–29, 1995. View at Google Scholar
  114. D. L. Linklater, R. E. O'Connor, and G. J. Palardy, “Kindergarten literacy assessment of English Only and English language learner students: an examination of the predictive validity of three phonemic awareness measures,” Journal of School Psychology, vol. 47, no. 6, pp. 369–394, 2009. View at Publisher · View at Google Scholar · View at Scopus
  115. D. L. Speece, K. D. Ritchey, D. H. Cooper, F. P. Roth, and C. Schatschneider, “Growth in early reading skills from kindergarten to third grade,” Contemporary Educational Psychology, vol. 29, no. 3, pp. 312–332, 2004. View at Publisher · View at Google Scholar · View at Scopus
  116. C. Juel, “Learning to read and write: a longitudinal study of 54 children from first through fourth grades,” Journal of Educational Psychology, vol. 80, no. 4, pp. 437–447, 1988. View at Google Scholar · View at Scopus
  117. J. M. T. Vloedgraven and L. Verhoeven, “Screening of phonological awareness in the early elementary grades: an IRT approach,” Annals of Dyslexia, vol. 57, no. 1, pp. 33–50, 2007. View at Publisher · View at Google Scholar · View at Scopus
  118. M. Twain, “Simplified spelling,” in Letters from the Earth: Uncensored Writings, B. DeVoto, Ed., HarperCollins, New York, NY, USA, 1942. View at Google Scholar
  119. L. Fuchs and D. Fuchs, “Determining adequate yearly progress from kindergarten through grade 6 with curriculum-based measurement,” Assessment for Effective Intervention, vol. 29, no. 4, pp. 25–37, 2004. View at Publisher · View at Google Scholar
  120. L. S. Fuchs, D. Fuchs, and D. L. Compton, “Monitoring early reading development in first grade: word identification fluency versus nonsense word fluency,” Exceptional Children, vol. 71, no. 1, pp. 7–21, 2004. View at Google Scholar · View at Scopus
  121. R. Parker, G. Tindal, and J. Hasbrouck, “Countable indices of writing quality: their suitability for screening-eligibility decisions,” Exceptionality, vol. 2, pp. 1–17, 1991. View at Publisher · View at Google Scholar
  122. R. I. Parker, G. Tindal, and J. Hasbrouck, “Progress monitoring with objective measures of writing performance for students with mild disabilities,” Exceptional Children, vol. 58, no. 1, pp. 61–73, 1991. View at Google Scholar · View at Scopus
  123. G. Tindal and R. Parker, “Assessment of written expression for students in compensatory and special education programs,” The Journal of Special Education, vol. 23, no. 2, pp. 169–183, 1989. View at Publisher · View at Google Scholar
  124. G. Tindal and R. Parker, “Identifying measures for evaluating written expression,” Learning Disabilities Research and Practice, vol. 6, pp. 211–218, 1991. View at Google Scholar
  125. K. A. Gansle, A. M. VanDerHeyden, G. H. Noell, J. L. Resetar, and K. L. Williams, “The technical adequacy of curriculum-based and rating-based measures of written expression for elementary school students,” School Psychology Review, vol. 35, no. 3, pp. 435–450, 2006. View at Google Scholar · View at Scopus
  126. K. L. McMaster and H. Campbell, “New and existing curriculum-based writing measures: technical features within and across grades,” School Psychology Review, vol. 37, no. 4, pp. 550–566, 2008. View at Google Scholar · View at Scopus
  127. K. A. Gansle, G. H. Noell, A. M. VanDerHeyden et al., “An examination of the criterion validity and sensitivity to brief intervention of alternate curriculum-based measures of writing skill,” Psychology in the Schools, vol. 41, no. 3, pp. 291–300, 2004. View at Google Scholar · View at Scopus
  128. C. Espin, B. Scierka, and S. Skare, “Criterion-related validity of curriculum-based measures in writing for secondary school students,” Reading & Writing Quarterly, vol. 15, no. 1, pp. 5–27, 1999. View at Google Scholar
  129. C. Espin, J. Shin, S. L. Deno, S. Skare, S. Robinson, and B. Benner, “Identifying indicators of written expression proficiency for middle school students,” The Journal of Special Education, vol. 34, no. 3, pp. 140–153, 2000. View at Google Scholar · View at Scopus
  130. J. W. Weissenburger and C. A. Espin, “Curriculum-based measures of writing across grade levels,” Journal of School Psychology, vol. 43, no. 2, pp. 153–169, 2005. View at Publisher · View at Google Scholar · View at Scopus
  131. C. Espin, T. Wallace, H. Campbell, E. S. Lembke, J. D. Long, and R. Ticha, “Curriculum-based measurement in writing: predicting the success of high-school students on state standards tests,” Exceptional Children, vol. 74, no. 2, pp. 174–193, 2008. View at Google Scholar · View at Scopus
  132. B. Diercks-Gransee, J. W. Weissenburger, C. L. Johnson, and P. Christensen, “Curriculum-based measures of writing for high school students,” Remedial and Special Education, vol. 30, no. 6, pp. 360–371, 2009. View at Publisher · View at Google Scholar · View at Scopus
  133. C. A. Espin, S. De La Paz, B. J. Scierka, and L. Roelofs, “The relationship between curriculum-based measures in written expression and quality and completeness of expository writing for middle school students,” The Journal of Special Education, vol. 38, no. 4, pp. 208–217, 2005. View at Google Scholar · View at Scopus
  134. S. Fewster and P. D. Macmillan, “School-based evidence for the validity of curriculum-based measurement of reading and writing,” Remedial and Special Education, vol. 23, no. 3, pp. 149–156, 2002. View at Google Scholar · View at Scopus
  135. J. M. Amato and M. W. Watkins, “The predictive validity of CBM writing indices for eighth-grade students,” The Journal of Special Education, vol. 44, no. 4, pp. 195–204, 2011. View at Publisher · View at Google Scholar · View at Scopus
  136. K. McMaster and C. Espin, “Technical features of curriculum-based measurement in writing: a literature review,” The Journal of Special Education, vol. 41, no. 2, pp. 68–84, 2007. View at Google Scholar · View at Scopus
  137. A. Foegen and S. L. Deno, “Identifying growth indicators for low-achieving students in middle school mathematics,” The Journal of Special Education, vol. 35, no. 1, pp. 4–16, 2001. View at Google Scholar · View at Scopus
  138. M. Calhoon, “Curriculum-based measurement for mathematics at the high school level: what we do not know and what we need to know,” Assessment for Effective Intervention, vol. 33, pp. 234–239, 2008. View at Publisher · View at Google Scholar
  139. L. Fuchs, D. Fuch, and S. Courey, “Curriculum-based measurement of mathematics competence: from competence to concepts and applications to real life problem solving,” Assessment for Effective Intervention, vol. 30, no. 2, pp. 33–46, 2005. View at Publisher · View at Google Scholar
  140. T. Christ, S. Sculin, A. Tolbize, and C. Jiban, “Implication of recent research: curriculum-based measurement of math computation,” Assessment for Effective Intervention, vol. 33, pp. 198–205, 2008. View at Publisher · View at Google Scholar
  141. A. Foegen, C. Jiban, and S. Deno, “Progress monitoring measures in mathematics. A review of the literature,” The Journal of Special Education, vol. 41, no. 2, pp. 121–139, 2007. View at Google Scholar · View at Scopus
  142. M. K. Burns, A. M. VanDerHeyden, and C. L. Jiban, “Assessing the instructional level for mathematics: a comparison of methods,” School Psychology Review, vol. 35, no. 3, pp. 401–418, 2006. View at Google Scholar · View at Scopus
  143. T. J. Christ and O. Vining, “Curriculum-based measurement procedures to develop multiple-skill mathematics computation probes: evaluation of random and stratified stimulus-set arrangements,” School Psychology Review, vol. 35, no. 3, pp. 387–400, 2006. View at Google Scholar · View at Scopus
  144. L. S. Fuchs, D. Fuchs, D. L. Compton, J. D. Bryant, C. L. Hamlett, and P. M. Seethaler, “Mathematics screening and progress monitoring at first grade: implications for responsiveness to intervention,” Exceptional Children, vol. 73, no. 3, pp. 311–330, 2007. View at Google Scholar · View at Scopus
  145. C. Jiban and S. Deno, “Using math and reading curriculum-based measurements to predict state mathematics test performance: are simple one-minute measures technically adequate?” Assessment for Effective Intervention, vol. 32, pp. 78–89, 2007. View at Publisher · View at Google Scholar
  146. P. Seethaler and L. Fuchs, “Using curriculum-based measurement to monitor kindergarteners' mathematics development,” Assessment for Effective Intervention, vol. 36, no. 4, pp. 219–229, 2011. View at Publisher · View at Google Scholar
  147. E. Shapiro, L. Edwards, and N. Zigmond, “Progress monitoring of mathematics among students with learning disabilities,” Assessment for Effective Intervention, vol. 30, no. 2, pp. 15–32, 2005. View at Publisher · View at Google Scholar
  148. B. Clarke, S. Baker, K. Smolkowski, and D. J. Chard, “An analysis of early numeracy curriculum-based measurement: examining the role of growth in student outcomes,” Remedial and Special Education, vol. 29, no. 1, pp. 46–57, 2008. View at Publisher · View at Google Scholar · View at Scopus
  149. D. Chard, B. Clarke, S. Baker, J. Otterstedt, D. Braun, and R. Katz, “Using measures of number sense to screen for difficulties in mathematics: preliminary findings,” Assessment for Effective Intervention, vol. 30, no. 2, pp. 3–14, 2005. View at Publisher · View at Google Scholar
  150. E. Lembke, A. Foegen, T. Whittaker, and D. Hampton, “Establishing technically adequate measures of progress in early numeracy,” Assessment for Effective Intervention, vol. 33, no. 4, pp. 206–214, 2008. View at Publisher · View at Google Scholar
  151. R. Martinez, K. Missal, S. Graney, O. Aricak, and B. Clarke, “Technical adequacy of early numeracy curriculum-based measurement in kindergarten,” Assessment for Effective Intervention, vol. 34, pp. 116–125, 2009. View at Publisher · View at Google Scholar
  152. A. M. VanDerHeyden, C. Broussard, and A. Cooley, “Further development of measures of early math performance for preschoolers,” Journal of School Psychology, vol. 44, no. 6, pp. 533–553, 2006. View at Publisher · View at Google Scholar · View at Scopus
  153. J. Leh, A. Jitendra, G. Caskie, and C. Griffin, “An evaluation of curriculum-based measurement of mathematics word problem solving measures monitoring third-grade students' mathematics competence,” Assessment for Effective Intervention, vol. 32, pp. 90–99, 2007. View at Publisher · View at Google Scholar
  154. L. Fuchs, D. Fuchs, and D. Compton, “The early prevention of mathematics difficulty: its power and limitations,” Journal of Learning Disabilities, vol. 45, no. 3, Article ID 269, p. 257, 2012. View at Publisher · View at Google Scholar
  155. A. Foegen, “Technical adequacy of general outcome measures for middle school mathematics,” Assessment for Effective Intervention, vol. 25, pp. 175–203, 2000. View at Publisher · View at Google Scholar
  156. A. Foegen, “Progress monitoring in middle school mathematics: options and issues,” Remedial and Special Education, vol. 29, no. 4, pp. 195–207, 2008. View at Publisher · View at Google Scholar · View at Scopus
  157. L. S. Fuchs, C. L. Hamlett, and D. Fuchs, Monitoring Basic Skills Progress: Basic Math Computation, 2nd edition, 1998.
  158. L. S. Fuchs, C. L. Hamlett, and D. Fuchs, Monitoring Basic Skills Progress: Basic Math Concepts and Applications, 1999.
  159. E. Lembke and P. Stecker, Curriculum-Based Measurement in Mathematics: An Evidence-Based Formative Assessment Procedure, RMC Research Corporation, Center on Instruction, Portsmouth, UK, 2007.
  160. C. Espin and G. Tindal, “Curriculum-based measurement for secondary students,” in Advanced Applications of Curriculum-Based Measurement, M. R. Shinn, Ed., Guilford Press, New York, NY, USA, 1998. View at Google Scholar
  161. R. Quirk, The Linguist and the English Language, Arnold, London, UK, 1974.
  162. D. Corson, “The learning and use of academic english words,” Language Learning, vol. 47, no. 4, pp. 671–718, 1997. View at Google Scholar · View at Scopus
  163. C. Espin and S. Deno, “Content-specific and general reading disabilities of secondary-level students: identification and educational relevance,” The Journal of Special Education, vol. 27, pp. 321–337, 1993. View at Publisher · View at Google Scholar
  164. C. Espin and S. Deno, “Performance in reading from content area text as an indicator of achievement,” Remedial and Special Education, vol. 14, no. 6, pp. 47–59, 1993. View at Google Scholar
  165. C. Espin and S. Deno, “Curriculum-based measures for secondary students: utility and task specificty of text-based reading and vocabulary measures for predicting performance on content-area tasks,” Diagnostique, vol. 20, no. 1–4, pp. 121–142, 1994. View at Google Scholar
  166. C. A. Espin and A. Foegen, “Validity of general outcome measures for predicting secondary students performance on content-area tasks,” Exceptional Children, vol. 62, no. 6, pp. 497–514, 1996. View at Google Scholar · View at Scopus
  167. C. Espin, T. Busch, J. Shin, and R. Kruschwitz, “Curriculum-based measurement in the content areas: validity of vocabulary matching as an indicator of performance in social studies,” Learning Disabilities, vol. 16, pp. 142–151, 2001. View at Publisher · View at Google Scholar
  168. C. A. Espin, J. Shin, and T. W. Busch, “Curriculum-based measurement in the content areas: vocabulary matching as an indicator of progress in social studies learning,” Journal of Learning Disabilities, vol. 38, no. 4, pp. 353–363, 2005. View at Google Scholar · View at Scopus
  169. C. Espin, T. Wallace, E. Lembke, H. Campbell, and J. Long, “Creating a progress-monitoring system in reading for middle school students: tracking progress toward meeting high-stakes standards,” Learning Disabilities Research and Practice, vol. 25, pp. 60–75, 2010. View at Publisher · View at Google Scholar
  170. V. Nolet and G. Tindal, “Special education in content area classes: development of a model and practical procedures,” Remedial and Special Education, vol. 14, no. 1, pp. 36–48, 1993. View at Publisher · View at Google Scholar
  171. G. Roid and T. M. Haladyna, A Technology for Test-Item Writing, Academic Press, Orlando, Fla, USA, 1982.
  172. G. Tindal and V. Nolet, “Curriculum-based measurement in middle and high schools: critical thinking skills in content areas,” Focus on Exceptional Children, vol. 27, no. 7, pp. 1–22, 1995. View at Google Scholar
  173. S. Engelmann and D. Carnine, Theory of Instruction: Principles and Applications, Irvington Publishers, New York, NY, USA, 1982.
  174. T. Twyman, J. McCleery, and G. Tindal, “Using concepts to frame history content,” Journal of Experimental Education, vol. 74, no. 4, pp. 331–349, 2006. View at Google Scholar · View at Scopus
  175. T. Twyman and G. Tindal, “Reaching all of your students in social studies,” Teaching Exceptional Children, vol. 1, no. 5, article 1, 2005. View at Google Scholar
  176. T. Twyman, L. R. Ketterlin-Geller, J. D. McCoy, and G. Tindal, “Effects of concept-based instruction on an English language learner in a rural school: a descriptive case study,” Bilingual Research Journal, vol. 27, no. 2, pp. 259–274, 2003. View at Google Scholar
  177. S. Embretson and S. Reise, Item Response Theory for Psychologists, Lawrence Erlbaum Associates, Mahwah, NJ, USA, 2000.
  178. T. Twyman and G. Tindal, “Extending curriculum-based measurement into middle/secondary schools: the technical adequacy of the concept maze,” Journal of Applied School Psychology, vol. 24, no. 1, pp. 49–67, 2007. View at Publisher · View at Google Scholar · View at Scopus
  179. J. E. Heimlich and S. D. Pittelman, Semantic Mapping: Classroom Applications, International Reading Association, Newark, Del, USA, 1986.
  180. F. P. Hunkins, Teaching Thinking Through Effective Questioning, Christopher-Gordon Publisher, Boston, Mass, USA, 1989.
  181. G. Tindal and V. Nolet, “Serving students in middle school content classes: a heuristic study of critical variables linking instruction and assessment,” The Journal of Special Education, vol. 29, no. 4, pp. 414–432, 1996. View at Google Scholar · View at Scopus
  182. V. Nolet and G. Tindal, “Curriculum-based collaboration,” Focus on Exceptional Children, vol. 27, no. 3, pp. 1–12, 1994. View at Google Scholar
  183. V. Nolet and G. Tindal, “Instruction and learning in middle school science classes: implications for students with disabilities,” The Journal of Special Education, vol. 28, no. 2, pp. 166–187, 1994. View at Publisher · View at Google Scholar
  184. G. Tindal, V. Nolet, and G. Blake, Focus on Teaching and Learning in Content Classes, University of Oregon Behavioral Research and Teaching, Eugene, Ore, USA, 1992.
  185. V. Nolet, G. Tindal, and G. Blake, Focus on Assessment Learning in Content Classes, University of Oregon Behavioral Research and Teaching, Eugene, Ore, USA, 1993.
  186. L. Ketterlin-Geller and G. Tindal, Concept-Based Instruction: Science, University of Oregon Behavioral Research and Teaching, Eugene, Ore, USA, 2002.
  187. T. Twyman, L. Ketterlin-Geller, and G. Tindal, Concept-Based Instruction: Social Science, University of Oregon Behavioral Research and Teaching, Eugene, Ore, USA, 2002.
  188. M. McDonald, L. Ketterlin-Geller, and G. Tindal, Concept-Based Instruction: Mathematics, University of Oregon Behavioral Research and Teaching, Eugene, Ore, USA, 2002.
  189. G. Tindal, J. Alonzo, and L. Ketterlin-Geller, Concept-Based Instruction: Language Arts, University of Oregon Behavioral Research and Teaching, Eugene, Ore, USA, 2002.
  190. S. Berkeley, W. N. Bender, L. Gregg Peaster, and L. Saunders, “Implementation of response to intervention: a snapshot of progress,” Journal of Learning Disabilities, vol. 42, no. 1, pp. 85–95, 2009. View at Publisher · View at Google Scholar · View at Scopus
  191. J. Wanzek and C. Cavanaugh, “Characteristics of general education reading interventions implemented in elementary schools with reading difficulties,” Remedial and Special Education, vol. 33, no. 3, pp. 192–202, 2012. View at Google Scholar
  192. D. Barnett, N. Elliott, J. Graden et al., “Technical adequacy for response to intervention practices,” Assessment for Effective Intervention, vol. 32, no. 1, pp. 20–31, 2006. View at Google Scholar
  193. S. Messick, “Validity,” in Educational Measurement, R. Linn, Ed., pp. 13–103, Macmillan Publishing Company, New York, NY, USA, 3rd edition, 1989. View at Google Scholar
  194. A. VanDerHeyden, “Technical adequacy of response to intervention decisions,” Council for Exceptional Children, vol. 77, no. 3, pp. 335–350, 2011. View at Google Scholar
  195. R. Gersten, T. Keating, and L. K. Irvin, “The burden of proof: validity as improvement of instructional practice,” Exceptional Children, vol. 61, no. 5, pp. 510–519, 1995. View at Google Scholar
  196. R. Allinder, “An examination of the relationship between teacher efficacy and curriculum-based measurement and student achievement,” Remedial and Special Education, vol. 16, pp. 247–254, 1995. View at Publisher · View at Google Scholar
  197. R. M. Allinder, “When some is not better than none: effects of differential implementation of curriculum-based measurement,” Exceptional Children, vol. 62, no. 6, pp. 525–535, 1996. View at Google Scholar · View at Scopus
  198. R. Allinder and M. BeckBest, “Differential effects of two approaches to supporting teachers' use of curriculum-based measurement,” School Psychology Review, vol. 24, pp. 287–298, 1995. View at Google Scholar
  199. R. M. Allinder, R. M. Bolling, R. G. Oats, and W. A. Gagnon, “Effects of teacher self-monitoring on implementation of curriculum-based measurement and mathematics computation achievement of students with disabilities,” Remedial and Special Education, vol. 21, no. 4, pp. 219–226, 2000. View at Google Scholar · View at Scopus
  200. P. M. Stecker, L. S. Fuchs, and D. Fuchs, “Using curriculum-based measurement to improve student achievement: review of research,” Psychology in the Schools, vol. 42, no. 8, pp. 795–819, 2005. View at Publisher · View at Google Scholar · View at Scopus
  201. M. K. Burns and B. V. Senesac, “Comparison of dual discrepancy criteria to assess response to intervention,” Journal of School Psychology, vol. 43, no. 5, pp. 393–406, 2005. View at Publisher · View at Google Scholar · View at Scopus
  202. D. Mellard, M. McKnight, and K. Woods, “Response to intervention screening and progress-monitoring practices in 41 local schools,” Learning Disabilities Research & Practice, vol. 24, no. 4, pp. 186–195, 2009. View at Google Scholar
  203. C. H. Hofstetter, “Contextual and mathematics accommodation test effects for English-language learners,” Applied Measurement in Education, vol. 16, no. 2, pp. 159–188, 2003. View at Google Scholar · View at Scopus
  204. L. Fuchs and S. Deno, “Must instructionally useful performance assessment be based in the curriculum?” Exceptional Children, vol. 61, no. 1, pp. 15–24, 1994. View at Google Scholar
  205. P. Stecker and E. Lembke, Advanced Applications of CBM in Reading (K-6): Instructional Decision-making Strategies Manual, National Center on Student Progress Monitoring, Washington, DC, USA, 2011.
  206. G. Tindal, J. Alonzo, J. F. T. Nese, and L. Saez, “Validating progress monitoring in the context of RTI,” in Pacific Coast Research Conference (PCRC), Coronado, Calif, USA, February 2012.
  207. R. Gersten and J. A. Dimino, “RTI (Response to Intervention): rethinking special education for students with reading difficulties (yet again),” Reading Research Quarterly, vol. 41, no. 1, pp. 99–108, 2006. View at Publisher · View at Google Scholar · View at Scopus
  208. J. M. Hintze and E. S. Shapiro, “Curriculum-based measurement and literature-based reading: is curriculum-based measurement meeting the needs of changing reading curricula?” Journal of School Psychology, vol. 35, no. 4, pp. 351–375, 1997. View at Google Scholar · View at Scopus
  209. J. Hintze, E. Shapiro, and J. Lutz, “The effects of curriculum on the sensitivity of curriculum-based measurement in reading,” The Journal of Special Education, vol. 28, pp. 188–202, 1994. View at Publisher · View at Google Scholar
  210. L. Fuchs, G. Tindal, and S. Deno, Effects of Varying Item Domains and Sample Duration on Technical Characteristics of Daily Measures in Reading, University of Minnesota Institute for Research on Learning Disabilities, Minneapolis, Minn, USA, 1982.
  211. Department of Education, Assisting Students Struggling With Reading: Response to Intervention and Multi-Tier Intervention in the Primary Grades, Institute of Education Sciences, Washington, DC, USA, 2009.
  212. Department of Education, Improving Reading Comprehension in Kindergarten Through 3rd Grade, Institute of Education Sciences, Washington, DC, USA, 2010.
  213. Department of Education, WWC Evidence Review Protocol for K-12 Students with Learning Disabilities, Institute of Education Sciences, Washington, DC, USA.
  214. E. R. O'Connor and P. Vadasy, The Handbook of Reading Interventions, Guilford Press, New York, NY, USA, 2011.
  215. R. M. Schwartz, M. C. Schmitt, and M. K. Lose, “Effects of teacher-student ratio in response to intervention approaches,” The Elementary School Journal, vol. 112, no. 4, pp. 547–567, 2012. View at Google Scholar
  216. L. Saez, “Instructional responsiveness: what are teachers doing?” in Proceedings of the Pacific Coast Research Conference, Coronado, Calif, USA, Februrary 2012.
  217. B. Elbaum, S. Vaughn, M. T. Hughes, and S. W. Moody, “How effective are one-to-one tutoring programs in reading for elementary students at risk for reading failure? A meta-analysis of the intervention research,” Journal of Educational Psychology, vol. 92, no. 4, pp. 605–619, 2000. View at Google Scholar · View at Scopus
  218. R. E. O'Connor, “Phoneme awareness and the alphabetic principle,” in The Handbook of Reading Interventions, R. E. O'Connor and P. Vadasy, Eds., Guilford Press, New York, NY, USA, 2011. View at Google Scholar
  219. R. Spicuzza, J. Ysseldyke, A. Lemkuil, S. Kosciolek, C. Boys, and E. Teelucksingh, “Effects of curriculum-based monitoring on classroom instruction and math achievement,” Journal of School Psychology, vol. 39, no. 6, pp. 521–542, 2001. View at Publisher · View at Google Scholar · View at Scopus
  220. S. Deno, “Individual differences and individual difference: the essential difference of special education,” The Journal of Special Education, vol. 24, pp. 160–173, 1990. View at Publisher · View at Google Scholar
  221. D. L. Gast, Single-Subject Research Methodology in Behavioral Science, Routledge, New York, NY, USA, 2010.
  222. R. H. Horner, E. G. Carr, J. Halle, G. Mcgee, S. Odom, and M. Wolery, “The use of single-subject research to identify evidence-based practice in special education,” Exceptional Children, vol. 71, no. 2, pp. 165–179, 2005. View at Google Scholar · View at Scopus
  223. L. Fuchs, “Assessing intervention responsiveness: conceptual and technical issues,” Learning Disabilities Research & Practice, vol. 18, no. 3, pp. 172–186, 2003. View at Google Scholar
  224. M. K. Burns, S. E. Scholin, S. Kosciolek, and J. Livingston, “Reliability of decision-making frameworks for response to intervention for reading,” Journal of Psychoeducational Assessment, vol. 28, no. 2, pp. 102–114, 2010. View at Publisher · View at Google Scholar · View at Scopus
  225. S. P. Ardoin, “The response in response to intervention: evaluating the utility of assessing maintenance of intervention effects,” Psychology in the Schools, vol. 43, no. 6, pp. 713–725, 2006. View at Publisher · View at Google Scholar · View at Scopus
  226. A. M. VanDerHeyden, J. C. Witt, and D. W. Barnett, “The emergence and possible futures of response to intervention,” Journal of Psychoeducational Assessment, vol. 23, no. 4, pp. 339–361, 2005. View at Publisher · View at Google Scholar · View at Scopus
  227. J. B. Willet, “Measuring change more effectively by modeling individual change over time,” in The International Encyclopedia of Education, T. Husen and T. N. Postlethwaite, Eds., Pergamon Press, Elmsford, NY, USA, 2nd edition, 1994. View at Google Scholar