Academic journal article The Behavior Analyst Today

Evaluating Curriculum-Based Measurement from a Behavioral Assessment Perspective

Academic journal article The Behavior Analyst Today

Evaluating Curriculum-Based Measurement from a Behavioral Assessment Perspective

Article excerpt

Curriculum-based measurement for reading (CBM-R) procedures were developed in the late 1970's and early 1980's as a set of standardized assessment tools for gauging students' academic performance in reading. It was developed in order to provide teachers with an efficient, easily understood measurement system yielding relevant data about students' level of performance, as well as their reading growth over time (Deno, 1985). Educators and researchers have noted that an important characteristic of CBM-R is its ability to measure both inter-individual differences in groups of students as well as intra-individual change within specific students (Fuchs & Fuchs, 1998; Fuchs, Fuchs, & Speece, 2002). While CBM-R data were initially used exclusively to guide low-stakes educational decisions (Deno, 1985; Deno, 1986; Deno, Marston, & Tindal, 1985; Deno & Shinn, 1989), CBM-R data are now being used for making high-stakes decisions (i.e., special education eligibility) within Response to Intervention (RtI) models.

Several features distinguish CBM-R procedures from other standardized measures used to assess students' reading. First, the assessment materials are relatively cheap and it requires little time to administer probes to students. Second, CBM-R is meant to be a measurement of students' global reading performance, which allows for practitioners to evaluate how students' are progressing toward towards long-term goals (Deno, Fuchs, Marston, & Shin, 2001; Fuchs, Fuchs, Hamlett, Walz, & Germann, 1993). Finally, as described by Deno et al.

"CBM-R departs from conventiona l psychometric applications by integrating the concepts of standardized measurement and traditional reliability and validity with features from behavioral and observational assessment methodology: repeated performance sampling, fixed time recording, graphic display of times-series data, and qualitative descriptions of performance" (Deno et al., 2001, p. 508)

These characteristics makes CBM-R ideal for use within an RtI model, as an instrument used to both identify students at-risk for academic problems and to evaluate individual students' response to instruction.

Within the Fuchs and Fuchs (1998) dual discrepancy RtI model, CBM-R data are first used to identify students who are at-risk for academic problems based upon a comparison of their performance to that of their normative group (i.e., nomothetic context). Such decisions are relatively low-stakes decisions, given that the identification of a student at-risk simply results in the student being provided with supplemental instruction. CBM-R data modeling individual student's response to the supplemental instruction is then used as a primary source of data for making high-stakes decisions. Students' response to supplemental instruction is generally evaluated using CBM-R progress monitoring procedures, which entails the frequent administration of CBM-R probes and plotting of collected data in time-series fashion. Progress monitoring data are evaluated by comparing the plotted data to a pre-established goal line or an estimate of weekly growth calculated using ordinary least square regression techniques. Regardless of the method of comparison, these evaluations of data are within an idiographic context in which an individual's data are compared to his/her previous performance(s). Based upon the evaluation of data, one of the following high-stakes decisions is made: (a) the intervention was successful, therefore the student is not eligible for special education and the intervention should be terminated, (b) the intervention was not adequate and a more intense intervention is needed, or (c) supplemental interventions of varying levels of intensity have not been successful and the student is eligible for special education.

The importance of the psychometric adequacy of CBM-R is especially salient now that CBM-R data are being used as a primary source for making high-stakes educational decisions (Ardoin & Christ, in press; Christ & Ardoin, 2007). …

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