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Cited by 72Reading and Literacy DevelopmentBehavioral and Psychological StudiesEducational Assessment and Improvement

Evaluating Curriculum-Based Measurement Slope Estimates Using Data From Triannual Universal Screenings

Ardoin, Scott P., Christ, Theodore J.·2008·School Psychology Review
DOI 10.1080/02796015.2008.12087912
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Abstract

Early identification of students in need of academic assistance results in a greater likelihood of academic success and a decrease in the likelihood that students will need continual special education services (Jenkins & O'Connor, 2002; Torgesen, 2002). Prevention is often more cost efficient, more effective, and more beneficial to students than delayed remediation. This and other observations support implementation of early screening and intervention for prevention of academic problems (President's Commission on Excellence in Special Education, 2002; Reschly, Tilly, & Grimes, 1999). The corresponding screening procedures are often referred to as either universal screenings or benchmarking. Curriculum-based measurement of oral reading fluency (CBM-R) is one common procedure used for universal screening purposes (Deno, 2002). CBM-R was evaluated by the Reading First Assessment Panel, which concluded that there was sufficient evidence for its use in universal screening (Francis et al., 2002). Although districts can develop their own source of CBM-R passages, various commercial sets of CBM-R passages exist such as the Dynamic Indicators of Basic Early Literacy Skills (DIBELS; http://dibels.uoregon.edu) and AIMS-web (http://aimsweb.com). CBM-R universal screening data can be norm referenced, criterion referenced, or self-referenced. Norms can be used to evaluate the relative standing of a student's performance in comparison to peers. This is an especially useful interpretative approach, which is often used as part of universal screenings and triannual assessments, to identify students discrepant in level and rate of growth from peers. In a criterion-referenced framework, CBM-R data can be used to evaluate a student's level of achievement compared to established benchmarks of expected levels of achievement. Such comparisons are beneficial when attempting to predict performance on large-scale assessments (e.g., state tests). Finally, a student's performance on previous administrations can be used to evaluate change or growth, which is valuable for gauging the effects of instruction (i.e., response to intervention, RTI). Norm-, criterion-, and self-referenced interpretations can be used in conjunction to support early intervention and prevention of reading problems. Early intervention and prevention practices increase the probability that students at risk will meet or exceed academic expectations in the future (Fuchs, Fuchs, & Compton, 2004) and demonstrate proficiency on statewide tests (Good, Simmons, & Kame'enui, 2001; Hintze & Silberglitt, 2005; Stage, 2001). Norm-referenced interpretation enables problem solving and resource allocation at the local level. School systems functioning within either a problem-solving or RTI framework must screen students to identify those individuals most likely to benefit from early intervention. Local norms are most appropriate to identify struggling readers at the individual and group level. The evaluation of student performance relative to classroom, local, and district norms enables schools to consider local variables external to the child (e.g., quality of the curriculum and instruction). Academic problems within problem-solving and RTI models are defined by the discrepancy between what is typically achieved by a student's peer group (i.e., what is expected) and what is achieved by an individual student or group (i.e., what is observed). CBM-R is often used to define problems in this manner. Within Fuchs and Fuchs' (1998) RTI dual-discrepancy model, CBM-R is a primary dependent variable used to define problems and evaluate response to instruction. CBM-R data are often used to establish the expected level of reading achievement at specific points in the academic year. Triannual CBM-R universal screening data are also used to establish the expected rate of reading growth across the year (Deno, Fuchs, Marston, & Shin, 2001). CBM-R universal screening data are used to determine which students are discrepant in their level of reading achievement and rate of academic growth. …

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  • Deno et al. documented growth from nearly 3,000 students tested from four regions of the country, reporting 2.0 words correct per minute growth per week until students achieved 30 WRCM; thereafter, general education students improved at least 1.0 word correct per minute/week.

    “They reported 2.0 words correct per minute growth per week until students achieved 30 WRCM; thereafter, students in the general education population improved at least 1.0 word correct per minute/week.”

    From Curriculum-Based Measurement: A Brief History of Nearly Everything from the 1970s to the Present (2013) · cites this paper as [70]

  • In the past decade, seven studies have been published on slope of progress in oral reading fluency.

    “In the past decade years, seven studies have been published on slope of progress in oral reading fluency (Deno et al. [70]).”

    From Curriculum-Based Measurement: A Brief History of Nearly Everything from the 1970s to the Present (2013) · cites this paper as [70]

  • Deno et al. reported that for 2,675 students in general education and 324 in special education classes, growth was 2.0 words correct per minute per week until students achieved 30 WRCM; thereafter, general education students improved at least 1.0 word correct per minute per week.

    “For 2,675 students in general education and 324 in special education classes, they reported 2.0 words correct per minute growth per week until students achieved 30 WRCM; thereafter, students in the general education population improved at least 1.0 word correct per minute/week.”

    From Curriculum-Based Measurement: A Brief History of Nearly Everything from the 1970s to the Present (2013) · cites this paper as [70]

  • Deno et al. suggested normative growth rates; others considered slope of improvement relative to aim lines by fitting an OLS regression line to each student's scores, computed the weekly increase based on the obtained parameter, and averaged these weekly increases (across students within grade levels and within general or special education programs).

    “Deno et al. [70] suggested normative growth rates; others considered slope of improvement relative to aim lines by fitting an OLS regression line to each student's scores, computed the weekly increase based on the obtained parameter, and averaged these weekly increases (across students within grade levels and within general or special education programs).”

    From Curriculum-Based Measurement: A Brief History of Nearly Everything from the 1970s to the Present (2013) · cites this paper as [70]

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Authors
Ardoin, S. P., & Christ, T. J.
Affiliations
  • University of South Carolina (US)
  • University of Minnesota (US)
Corresponding author
Ardoin, Scott P.
ORCID
Venue
School Psychology Review
Publisher
Informa UK Limited
Published
2008-03-01
Volume
37
Issue
1
Pages
109-125
ISSN
  • 0279-6015 (ISSN-L)
  • 2372-966X
DOI
10.1080/02796015.2008.12087912
OpenAlex
W1580012532
Cited by
72
References
23
Citations by year
2025: 1 · 2024: 1 · 2021: 1 · 2019: 1 · 2018: 3 · 2017: 4 · 2016: 8 · 2015: 6 · 2014: 9 · 2013: 7 · 2012: 12
FWCI
10.53
Type
journal article
Language
en
Open access
closed
Locations
School Psychology Review (publishedVersion)
Topics
  • Social Sciences › Psychology › Developmental and Educational Psychology › Reading and Literacy Development
  • Social Sciences › Psychology › Developmental and Educational Psychology › Behavioral and Psychological Studies
  • Social Sciences › Decision Sciences › Information Systems and Management › Educational Assessment and Improvement
Keywords
curriculum-based measurement, oral reading fluency, universal screening, early identification of reading problems, Response to Intervention, early intervention, reading prevention, DIBELS, reading achievement prediction, special education eligibility

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