Author ORCID Identifier
The fluency construct: Curriculum-based measurement concepts and applications
Curriculum-based measurement (CBM) has enjoyed a long history of success and study as a practice for data-based decision-making (Deno, 2003). Originally developed and studied at the University of Minnesota in the mid-1970s (see Shinn, 2012 or Tindal, 2013 for a detailed history), Stan Deno and his colleagues developed CBM measures and the problem-solving process as part of one of the Institutes for Research on Learning Disabilities (IRLDs), centers funded by the Office of Special Education Programs that addressed significant issues for students with learning dis- abilities. With Deno’s interests in applied behavior analysis, it seemed logical to apply methodologies such as collecting baseline data, setting goals for students, and collecting and graphing ongoing data and then using them to make educational decisions, as a student’s data is compared to a goal. As part of work in the IRLD, that is exactly what Deno and colleagues did, developing a system of technically adequate (i.e., reliable and valid) assessments that could be administered quickly and efficiently up to three times per week. These data would be graphed on an ongoing basis and compared with a goal set for a student. If data fell below the student’s goal for a specified number of points, a curricular change or instructional tweak would be instituted. All of these components were couched in a problem-solving process so that teachers and teams could utilize on a frequent basis to help make better decisions about student learning. As you will note already, the CBM process or model is not just the measures themselves, but the use of those measures in a more comprehensive, problem-solving process. In this chapter the use of CBM, and specifically CBMs as measures of fluency, is discussed in depth. The theoretical support for measures of fluency is discussed along with more detailed research that supports the use of CBM, basic components of the process, and using CBM data to make screening decisions across a variety of academic subjects.
Lembke, E. S., Carlisle, A., & Poch, A. (2016). Using Curriculum–based measurement fluency data for initial screening decisions. In K. D. Cummings and Y. Petscher (Eds.). The fluency construct: Curriculum-based measurement concepts and applications (pp. 91–122). New York, NY: Springer. https://doi.org/10.1007/978-1-4939-2803-3_4