A longitudinal randomized design was used with a sample of 57 third-grade students to evaluate and compare the effectiveness of three variations of cover, copy, and compare (CCC; traditional CCC, CCC-answer only, and CCC-paired responding) on multiplication fluency in third-grade students. Traditional CCC requires students to write the problem and answer as a response, CCC-answer only requires students only to write the answer, and CCC-paired responding requires students to write the answer only, then verbally state the problem and answer twice. The interventions occurred for 4 min per day, 5 days per week, across 11 calendar weeks (minus 1 week during a school break).
View Article and Find Full Text PDFCurriculum-based measurement (CBM) has conventionally included accuracy criteria with recommended fluency thresholds for instructional decision-making. Some scholars have argued for the use of accuracy to directly determine instructional need (e.g.
View Article and Find Full Text PDFMath curriculum-based measurement (CBM) is an essential tool for multi-tiered systems of support decision making, but the reliability of math CBMs has received little research, particularly using more rigorous methods such as generalizability (G) theory. Math CBM is historically organized into two domains: mastery measures and general outcome measures. This paper details 17 concurrent G and dependability studies in a partially crossed design investigating the reliability of mastery measure CBMs for students ( = 263) in Grades K, 1, 3, 5, and 7.
View Article and Find Full Text PDFUnderstanding typical rates of growth under intervention is necessary to establish what environmental expectations one should have and serves as a benchmark when investigating novel interventions. These trends are not well understood in the math domain. The current study addressed this gap by aggregating available data on digits correct per minute (DCPM) growth in single-skill curriculum-based measurements as students undergo intervention.
View Article and Find Full Text PDFThe empirical literature on academic intervention has increasingly promoted comparative research, moving the field forward in addressing the question, "What works best?" Poncy et al. (2015), Skinner (2008, 2010), and Skinner, Fletcher, and Henington (1996) have suggested that researchers enhance traditional evaluations of learning (behavior change) by using learning rates (behavior change over instructional time [IT]). The precise documentation or control of IT allows researchers to address confounds commonly found in comparative intervention research, most notably variability in intervention duration.
View Article and Find Full Text PDFBayesian techniques have become increasingly present in the social sciences, fueled by advances in computer speed and the development of user-friendly software. In this paper, we forward the use of Bayesian Asymmetric Regression (BAR) to monitor intervention responsiveness when using Curriculum-Based Measurement (CBM) to assess oral reading fluency (ORF). An overview of Bayesian methods and their application to the problem-solving model is first presented, which is further illustrated by a case example.
View Article and Find Full Text PDFTo best remediate academic deficiencies, educators need to not only identify empirically validated interventions but also be able to apply instructional modifications that result in more efficient student learning. The current study compared the effect of massed and distributed practice with an explicit timing intervention to evaluate the extent to which these modifications lead to increased math fact fluency on basic addition problems. Forty-eight third-grade students were placed into one of three groups with each of the groups completing four 1-min math explicit timing procedures each day across 19 days.
View Article and Find Full Text PDFA wide variety of effect sizes (ESs) has been used in the single-case design literature. Several researchers have "stress tested" these ESs by subjecting them to various degrees of problem data (e.g.
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