Abstract
ABSTRACTWithin multitiered systems of support, assessment practices that limit the amount of time students miss instruction should be prioritized. At the same time, decisions about student response to intervention need to be based upon technically adequate data. We evaluated the impact of data collection frequency and trend estimation method on the magnitude of average rates of growth as well as the stability of individual estimates of growth from a computer-adaptive test. Students in Grades 2 through 5 (n > 2,000) were progress monitored once a month across the 2015–2016 school year with Star Reading or Star Math assessments. Results suggest that using ordinary least squares regression to estimate growth from triannual screening periods is generally sufficient to make program evaluation decisions about response to instruction across a school year. To make decisions about individual student progress, data should be collected at a minimum bimonthly but preferably once a month.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
