Academic journal article School Psychology Review

A Longitudinal Examination of the Diagnostic Accuracy and Predictive Validity of R-CBM and High-Stakes Testing

Academic journal article School Psychology Review

A Longitudinal Examination of the Diagnostic Accuracy and Predictive Validity of R-CBM and High-Stakes Testing

Article excerpt

Abstract. The purpose of this study was to compare different statistical and methodological approaches to standard setting and determining cut scores using R-CBM and performance on high-stakes tests. One thousand seven hundred and sixty-six-students were followed longitudinally from first through third grades using R-CBM benchmark assessment. In addition, students were administered the Minnesota Comprehensive Assessment (MCA) at the end of third grade. Predictive validity and diagnostic accuracy analyses using discriminative analysis, logistic regression, and receiver operator characteristic (ROC) curves were conducted. Results suggested that R-CBM is strongly associated with MCA performance at each grade level and is both accurate and efficient in predicting those students who are likely to pass the reading portion of the MCA beginning in first grade. Applied and theoretical implications are discussed along with future research.

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Curriculum-based measurement (CBM) is a standardized set of measurement techniques used to index student academic performance in the basic skill areas of reading, mathematics, spelling, and written expression (Deno, 1985; Deno, Mirkin, & Chiang, 1982; Fuchs & Deno, 1991; Shinn, 1989b). As a variant of curriculum-based assessment (CBA), CBM uses the general education curriculum as the basis for test development and is designed primarily as a measurement and evaluation system that school psychologists and teachers can routinely use to monitor individual student progress and instructional effectiveness.

CBM differs from other forms of CBA in a number of important ways (Fuchs & Deno, 1991). First, the focus of CBM is on broad long-term goal objectives, rather than short-term objectives. With CBM, practitioners specify what they want students to achieve by year's end or longer. These long-term objectives structure the assessment process throughout the progress monitoring period, as the same performance objective is continually assessed. Focusing on the broad goals of the curriculum rather than a series of short-term objectives allows CBM to attend to the assessment of more general integrated outcomes as they occur in context. The result of such measurement focuses the attention of the assessment on the broader desired outcome of instruction. This is in contrast to mastery or criterion-referenced approaches whereby the assessment material changes with each new short-term objective requiring the curriculum to be decomposed and compartmentalized for assessment. Second, because it focuses on broad aspects of the curriculum, CBM allows for the assessment of retention and generalization of learning. Using a domain sampling approach to test development, CBM draws on a broad domain of skills representing the current instructional focus, as well as those representing past and future instructional targets. As a result, CBM produces performance indicators that assess current learning in addition to the retention and generalization of previously mastered material. A third distinguishing feature of CBM is that it specifies the measurement and evaluation procedures to be used, including methods for generating test stimuli, administering and scoring tests, and summarizing and making inferences from the data collected. This again is in contrast to other forms of CBA where the administration and scoring, as well as test development procedures, are not standardized and are left up to the will of the examiner. Using standardized administration and scoring procedures allows for comparison of scores across students, as well as the comparison of scores within-student across time.

A substantial research literature has developed to demonstrate that CBM can be used effectively to gather student performance data to support a wide range of educational decisions (Deno, 2003). For example, CBM has been shown effective in improving instructional programs and enhancing teacher instructional planning through the use of goal setting, progress monitoring, and evaluating the effects of changes in a formative evaluation model (Fuchs, Deno, & Mirkin, 1984; Fuchs, Fuchs, & Hamlett, 1993; Fuchs, Fuchs, Hamlett, & Stecker, 1991); developing local normative performance standards (Marston & Magnusson, 1988; Shinn, 2002); screening to identify students academically at risk (Deno, Reschly-Anderson, Lembke, Zorka, & Callender, 2002; Marston & Magnusson, 1988); evaluating classroom prereferral interventions (Shinn, 1995; Tilly & Grimes, 1998); offering alternative special education identification procedures (Fuchs & Fuchs, 1998; Marston & Magnusson, 1988; Marston, Mirkin, & Deno, 1984; Shinn, 1989a); and recommending and evaluating inclusion (Fuchs, Roberts, Fuchs, & Bowers, 1996; Powell-Smith & Stewart, 1998). …

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