The purpose of this article is to demonstrate ways to model nonlinear growth using three testing occasions. We demonstrate our growth models in the context of curriculum-based measurement using the fall, winter, and spring passage reading fluency benchmark assessments. We present a brief technical overview that includes the limitations of a growth model with three time points, and how nonlinear growth can be modeled and the associated limitations. We present results for a piecewise growth mixture modeling approach to model nonlinear growth for 1 to 3 classes, as well as to further explain individual differences and to capture heterogeneity of growth patterns. We discuss our interpretation of these results, as well as the implications of different methods for modeling nonlinear growth with three occasions.
We report the results of an alternate form reliability and criterion validity study of kindergarten and grade 1 (N = 84-‐-‐-‐199) reading measures from the easyCBM© assessment system and Stanford Early School Achievement Test/Stanford Achievement Test, 10 edition (SESAT/SAT-‐-‐-‐10) across 5 time points. The alternate form reliabilities ranged from .31-‐-‐-‐.94 for the kindergarten measures and from .27-‐-‐-‐.96 for the grade 1 measures. Multiple regression analyses were used to examine the overall variance explained by the combined measures when predicting end-‐-‐-‐of-‐-‐-‐year reading achievement. In kindergarten, the easyCBM© measures accounted for 35-‐-‐-‐58% of the variance in SAT-‐-‐-‐10 performance. In grade 1 easyCBM© measures accounted for 14-‐-‐-‐32% of the variance in SAT-‐-‐-‐10 performance and 49-‐-‐-‐56% of the variance in performance on the easyCBM© word reading fluency measure administered at time 5.
The purpose of this article is to demonstrate ways to model nonlinear growth using three testing occasions. We demonstrate our growth models in the context of curriculum-based measurement using the fall, winter, and spring passage reading fluency benchmark assessments. We present a brief technical overview that includes the limitations of a growth model with three time points, and how nonlinear growth can be modeled and the associated limitations. We present results for a piecewise growth mixture modeling approach to model nonlinear growth for 1 to 3 classes, as well as to further explain individual differences and to capture heterogeneity of growth patterns. We discuss our interpretation of these results, as well as the implications of different methods for modeling nonlinear growth with three occasions.
This technical report is one in a series of five describing the reliability (test/retest and alternate form) and G-‐-‐-‐-‐-‐-‐-‐-‐-‐Theory / D-‐-‐-‐-‐-‐-‐-‐-‐-‐Study research on the easyCBM reading measures, grades 1-‐-‐-‐-‐-‐-‐-‐-‐-‐5. Data were gathered in the spring of 2011 from a convenience sample of students nested within classrooms at a medium-‐-‐-‐-‐-‐-‐-‐-‐-‐sized school district in the Pacific Northwest. Due to the length of the results, we present results of each grade level’s analysis in its own technical report, sharing a common abstract, introduction, and methods section, while differing in the results and conclusions.
This study examined the type of growth model that best fit within-year growth in oral reading fluency and between-student differences in growth. Participants were 2,465 students in grades 3–5. Hierarchical linear modeling (HLM) analyses modeled curriculum-based measurement (CBM) oral reading fluency benchmark measures in fall, winter, and spring with grade level and student characteristics (including special education and Limited English Proficiency status) as covariates. Results indicated that a discontinuous growth model fit the data better than a linear growth model, with greater growth in the fall than in the spring. Oral reading fluency growth rates also differed by grade and student characteristics. Implications for school practice and research are discussed.
Students with disabilities participate in two major measurement systems. The Individuals with Disabilities Education Act emphasizes working within a Response to Intervention (RTI) framework to identify and monitor the progress of low-performing students. Persistent low-performing students also may be eligible for some form of an alternate assessment for accountability purposes. Working within these two systems, educators need technically sound measures to inform decision making. This study presents scaling results from a Curriculum Based Measurement tool designed within an RTI framework and specifically for persistently low-performing students. We use the phrase “persistently low-performing students” to refer to a specific group of students who have been identified with a nonsevere learning disability and who perform well below grade-level expectations. Key findings indicate that items appear to function well in the lower tail of the distribution of students' estimated ability level. Further, the distribution of items is positively skewed, resulting in many accessible items that are most informative for low-performing students. Results provide initial validity evidence for the measurements as one source of data for progress monitoring within an RTI framework and the identification of persistent low-performing students who may be eligible for a large-scale assessment option other than the general grade-level assessment.
Julie Alonzo合作论文数University of Oregon18
Gerald Tindal合作论文数University of Oregon18
bitnara jasmine park合作论文数11Nese Joseph F T合作论文数Behavioral Research and Teaching, 175 Lokey Education, 5262 University of Oregon, Eugene, OR 97403-5262, United States.11Daniel Anderson合作论文数10elisa jamgochian合作论文数6Leilani Saez合作论文数6
P Shawn Irvin合作论文数University of Oregon5Akihito Kamata合作论文数Florida State University4Chalie Patarapichayatham合作论文数2jessica l saven合作论文数1Dan Farley合作论文数1
Gina Biancarosa合作论文数University of Oregon1
