An existing data set for a sample of 3rd grade students was used to determine the
relationship between performance during a reading intervention and short-term
achievement test outcomes, and long-term risk status. Students participated in a reading
intervention, one-on-one practice with a trained adult, during which weekly curriculum
based measurement-reading data and dosage of intervention service time were collected.
The sample was comprised of reading curriculum based measurement progress
monitoring data for 99 students from 8 different schools. The recommendation was for
students to receive 60 minutes per week of fluency sessions, the average student received
a dosage of 51 minutes per week. Student scores on district and state reading tests from
the spring of third grade, and student participation in pre-referral or special education
programming 1 and 2 years post participation were also examined. Reading test data
were provided by the schools including student performance on the spring 3rd grade No
Child Left Behind state reading test, and for 6 of the schools, a district reading test by the
Northwest Evaluation Association called the Measures of Academic Progress. Schools
also provided existing information about free/reduced lunch eligibility and risk-status, for
each of the students.
The following research questions guided the study: (a) how does performance
during a third-grade reading intervention predict future performance on district and state
reading tests; and (b) how does performance during a third-grade reading intervention
predict future risk-status in 4th and 5th grades? Multiple linear regression models were used to determine the amount of variance
accounted for in state and district reading test performance, using the predictor variables
related to participation in the 3rd grade reading fluency intervention. Twenty-three percent
of the variance in state test scores, and 44% of the variance in district test scores could be
explained using multiple linear regression models with the predictor variables: lunch
status, slope, baseline and end levels, and dosage. There were different significant
coefficients in each model, and 2 of the schools did not administer the MAP.
Risk-status 1 and 2 years following participation in the 3rd grade reading
intervention also was determined, using the predictors: performance during the
intervention, dosage, and lunch status. Logistic regression models used to predict
placement in special education in 4th or 5th grades were not significant. The logistic
regression model used to predict student participation in pre-referral programming in 4th
grade was not significant, but the model was significant in 5th grade. Variables were
backwards eliminated to further determine which variable(s) in the model was/were
significant in predicting pre-referral participation in 5th grade, and baseline level at the onset of the 3rd grade reading intervention was the significant predictor. An estimated
probability plot illustrated that students with a higher baseline level were less likely to
participate in pre-referral programming in 5th grade, versus students with lower baseline
The findings from the first part of this study further support the existing research
that reading curriculum based measurement does predict performance on other reading
tests (Baker, et al., 2008; Chard, Vaughn & Tyler, 2002; Lennon & Slesinski, 1999) and state reading tests (Stage & Jacobsen, 2001; Good, Simmons & Kame’enui, 2001;
Crawford, Tindal, Stieber, 2001; McGlinchey & Hixson, 2004; Keller-Margios, Shaprio
& Hintz, 2008). The current study is unique in its application of progress monitoring
data for students that participated in a reading intervention, versus seasonal benchmark
scores. The second part of the study examined risk-status in 4th and 5th grades for the
students who participated in the reading intervention service in 3rd grade. Results
supported the findings of other studies, that some intervention participants struggle to
maintain gains in subsequent years, (Byrne & Fielding-Barnsley, 1993; Bus & Van
Ijzendoorn, 1999; O’Connor, Notari-Syverson, & Vadasy, 1996, 1998) and that
curriculum-based measurement baseline level, can be a strong predictor of growth
(Silberglitt and Hintz, 2007). The current study was unique in that much of prior
research has examined results for students that participate in interventions higher in
dosage, diverse in skill areas and prior to 3rd grade. The findings from this study suggest
that progress-monitoring data at the on-set, and during an intervention, do relate to
performance on other reading assessments, and may predict future risk-status.
University of Minnesota Ph.D. dissertation. July 2012. Major:Educational Psychology. Advisor: Matthew K. Burns. 1 computer file (PDF); ix, 117 pages.
Using student performance during a reading intervention to predict student outcomes and performance on accountability measures of reading..
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