Words read correctly per minute (WCPM) is the reporting score metric in oral reading fluency (ORF) assessments, which is popularly utilized as part of curriculum-based measurements to screen at-risk readers and to monitor progress of students who receive interventions. Just like other types of assessments with multiple forms, equating would be necessary when WCPM scores are obtained from multiple ORF passages to be compared both between and within students. This article proposes a model-based approach for equating WCPM scores. A simulation study was conducted to evaluate the performance of the model-based equating approach along with some observed-score equating methods with external anchor test design.

Curriculum-based measurement (CBM) is an approach to measuring student academic growth and evaluating the effectiveness of instruction (Deno, Exceptional Children, 52, 219-232, 1985) that was developed, in part, based on characteristics of applied behavior analysis. Learning to administer and use CBM data is commonly part of teacher preparation programs, but less common in behavior analysis graduate programs (Schreck et al. Behavioral Interventions, 31, 355-376, 2016; Schreck & Mazur, Behavioral Interventions, 23, 201-212, 2008). This article describes a sequence of steps that educational teams can follow to use CBM within the multi-tiered system of support (MTSS) framework. These steps include (1) selecting a CBM publisher and gathering materials; (2) practicing administering and scoring CBM; (3) administering, scoring, and comparing student scores to grade-level benchmarks; (4) using CBM data to write ambitious and realistic IEP goals; and (5) using data-based individualization. Each step is described and includes a description of a case study that is based on our experiences working with pre-service teacher candidates, and special education and behavior analysis graduate students in K-12 and after-school instructional programs.

Data-based decision-making (DBDM) using curriculum-based measurement (CBM) data has demonstrated effectiveness in improving academic achievement for students with or at risk for learning disability. Despite substantial evidence supporting DBDM, its use is not common practice for many educators, even those who regularly collect CBM data. One explanation for its lack of widespread use is that educators may not receive adequate training in the DBDM aspects of CBM. Espin et al. examined the extent to which DBDM is represented in CBM professional development (PD) materials and found that the topic was significantly underrepresented (12% to 14% of CBM PD material content) compared with other CBM topics. The purpose of this study was to conduct a conceptual replication of the Espin et al. systematic review through an analysis of CBM content in practitioner journal articles. The present review includes 29 practitioner articles coded to the four CBM categories used in the Espin et al. study: (a) general CBM information, (b) conducting CBM, (c) data-based decision-making, and (d) other. Results revealed a pattern similar to the one found by Espin et al. with approximately 18% of the content of practitioner articles on CBM devoted to the topic of decision-making. These findings strengthen the recommendation from Espin et al. for increased attention to DBDM in CBM training materials.

The purpose of this literature review on curriculum-based measurement in mathematics (CBM-M) was to update and extend the Foegen et al. (2007) progress monitoring in mathematics review. We included 99 studies focused on at least one of the three stages of CBM research (i.e., one point in time [screening], repeatedly over time [progress monitoring], and instructional utility) in mathematics for students in preschool through Grade 12. The results of this review indicated that researchers have increased the amount of research conducted at the early mathematics and secondary levels; however, many studies focused on the stages of CBM research are still conducted at the elementary level. The results also demonstrated that most studies (k = 85; 85.9%) were focused on Stage 1, with fewer studies reporting results related to Stage 2 (k = 40; 40.4%) and Stage 3 (k = 5; 5.1%). The results of this literature review also underscore that although considerable growth has been achieved in the past 15 years in CBM-M development and reporting, next steps in research include a focus on investigating the uses of CBM-M for progress monitoring and instructional decision making.

Although researchers have investigated technical adequacy and usability of written-expression curriculum-based measures (WE-CBM), the economic implications of different scoring approaches have largely been ignored. The absence of such knowledge can undermine the effective allocation of resources and lead to the adoption of suboptimal measures for the identification of students at risk for poor writing outcomes. Therefore, we used the Ingredients Method to compare implementation costs and cost-effectiveness of hand-calculated and automated scoring approaches. Data analyses were conducted on secondary data from a study that evaluated predictive validity and diagnostic accuracy of quantitative approaches for scoring WE-CBM samples. Findings showed that automated approaches offered more economic solutions than hand-calculated methods; for automated scores, the effects were stronger when the free writeAlizer R package was employed, whereas for hand-calculated scores, simpler WE-CBM metrics were less costly than more complex metrics. Sensitivity analyses confirmed the relative advantage of automated scores when the number of classrooms, students, and assessment occasions per school year increased; again, writeAlizer was less sensitive to the changes in the ingredients than the other approaches. Finally, the visualization of the cost-effectiveness ratio illustrated that writeAlizer offered the optimal balance between implementation costs and diagnostic accuracy, followed by complex hand-calculated metrics and a proprietary automated program. Implications for the use of hand-calculated and automated scores for the universal screening of written expression with elementary students are discussed.

The purpose of this narrative synthesis of the curriculum-based measure (CBM) instructional utility literature is to deepen insight into the supports required to enrich teachers\' instructional decision-making within curriculum-based measure-data-based individualization (CBM-DBI) in ways that enhance the learning outcomes of students with intensive intervention needs, including students with learning disabilities. We begin by summarizing a recent meta-analysis of CBM-DBI studies focused on academic outcomes. We then reconsider studies from that meta-analysis to further explore the supports required to enrich teachers\' instructional decision-making within CBM-DBI and improve student learning. We next draw conclusions and propose a renewed program of instructional utility CBM-DBI research for capitalizing on technology\'s potential to enhance productive instructional decision-making for students who require intensive intervention, fulfill DBI\'s potential, and bring CBM-DBI to scale.

The purpose of this review was to synthesize research on the effect of professional development (PD) targeting data-based decision-making processes on teachers\' knowledge, skills, and self-efficacy related to curriculum-based measurement (CBM) and data-based decision-making (DBDM). To be eligible for this review, studies had to (a) be published in English, (b) include in-service or pre-service K-12 teachers as participants, (c) use an empirical group design, and (d) include sufficient data to calculate an effect size for teacher outcome variables. The mean effect of DBDM PD on teacher outcomes was g = 0.57 (p < .001). This effect was not moderated by study quality. These results must be viewed through the lens of significant heterogeneity in effects across included studies, which could not be explained by follow-up sensitivity analyses. In addition, the experimental studies included in this review occurred under ideal, researcher-supported conditions, which impacts the generalizability of the effects of DBDM PD in practice. Implications for research and practice are discussed.

In reading, several curriculum-based measures (CBM) are used for universal screening in Grades K-2. This study summarized the criterion-related validity of early reading CBM tools used in the context of universal screening. After the application of the inclusion and exclusion criteria, 54 studies (53 documents across 34 articles, 16 dissertations, and 3 technical reports) were identified through a systematic review of the literature through December 2018. Forty-eight studies (47 documents across 31 articles, 15 dissertations, and 2 technical reports) were included in the meta-analysis, representing 47,168 students in the US who were enrolled in Grades K, 1, or 2 when they completed the screening measure. A random effects meta-analysis with robust variance estimation was conducted separately for concurrent and predictive correlations to estimate the average effect size between each early reading CBM and the reading outcome measures. Aggregated concurrent Pearson correlation coefficients (r) ranged from 0.343 (phoneme segmenting CBM predicting more complex reading skills) to 0.750 (nonsense words CBM predicting oral reading skills). Aggregated correlations were similar in magnitude for predictive validity. For some measures, correlations were moderated by administration lag. Findings have implications for research and practice regarding the use of universal reading screeners in the early elementary grades.

Early identification of learning difficulties is a critical component of the Response to Intervention (RtI) model. In kindergarten, the screening of foundational reading skills can provide a data-based guideline for identifying students requiring a more intensive response-based intervention before starting elementary school. This study examines the classification accuracy and best predictors of a set of Spanish curriculum-based measures administered during kindergarten. The study\'s sample included 189 students tested in the fall, winter, and spring. Receiver operating characteristic (ROC) analysis was conducted. The composite score of the curriculum-based measurement (CBM) revealed area under the ROC curve (AUC) values of 0.83, 0.97, and 0.94 in the fall, winter, and spring, respectively. Phonemic awareness and letter-sound knowledge were the only isolated measures that demonstrated excellent AUC values throughout kindergarten. Logistic regression models showed that, when entered simultaneously, all measures were significant predictors of reading risk at some moment of the school year.

Although reading is an essential skill for college success, little is known about how college students with and without disabilities read within their actual college curriculum. In the present article, we report on two studies addressing this issue. Within study 1, we developed and validated curriculum-based oral reading fluency measures using a sample of college students without disabilities (N = 125). In study 2, we administered the curriculum-based measures to four groups (each with n = 25): college students without disabilities, college students with dyslexia, college students with ADHD, and a clinical control group. Study 1 results indicated that the curriculum-based measures demonstrated good reliability and criterion validity. Results from study 2 indicated that college students with dyslexia were substantially slower readers than all groups without dyslexia (ds > 1.8). The curriculum-based measures demonstrated high accuracy in classifying participants with dyslexia and with impaired oral reading fluency (area under the curve > .94). Implications for incorporating curriculum-based measures in postsecondary settings are discussed.