Assessing and Validating Effects of a Data‐Based Decision‐Making Intervention on Student Growth for Mathematics and Spelling

Abstract

Data‐based decision making (DBDM) is presumed to improve student performance in elementary schools in all subjects. The majority of studies in which DBDM effects have been evaluated have focused on mathematics. A hierarchical multiple single‐subject design was used to measure effects of a 2‐year training, in which entire school teams learned how to implement and sustain DBDM, in 39 elementary schools. In a multilevel modeling approach, student achievement in mathematics and spelling was analyzed to broaden our understanding of the effects of DBDM interventions. Student achievement data covering the period from August 2010 to July 2014 were retrieved from schools’ student monitoring systems. Student performance on standardized tests was scored on a vertical ability scale per subject for Grades 1 to 6. To investigate intervention effects, linear mixed effect analysis was conducted. Findings revealed a positive intervention effect for both mathematics and spelling. Furthermore, low‐SES students and low‐SES schools benefitted most from the intervention for mathematics.

Introduction to the Special Issue on Classroom Assessment

“…The next two papers (Briggs, Chattergoon, & Burkhardt, ; Hopster‐den Otter, Wools, Eggen, & Veldkamp, ) both contribute valuable general perspectives on the methodology of classroom assessment, addressing issues regarding (a) student learning objectives, and (b) a general framework for validity. The next set of four papers (Chen, Senk, Thompson, & Voogt, ; Keuning, van Geel, Visscher, & Fox, ; Leighton, ; Liu et al., ), makes valuable contributions to specific areas of the broad domain of classroom assessment in the areas of reading comprehension, formative assessment feedback, data‐based decision making, and geometry learning, respectively. The final paper (Duckor & Holmberg, ) looks beyond the student, to investigate teacher learning progressions.…”

Effects of Data-Based Decision-Making on Low-Performing Readers in General Education Classrooms: Cumulative Evidence From Six Intervention Studies

“…Highlighting the potential of this framework, Keuning et al (2019) found that primary school teachers who were trained in DBDM effected higher mathematics and spelling skills for their students than teachers who were not trained in DBDM. Similarly, Carlson et al (2011) found that extensive teacher training on the interpretation and use of data led to higher student achievement in mathematics and showed a positive effect trend on reading.…”

“…Providing teachers with such supports has been shown across several studies to yield positive effects on student learning (e.g., Förster et al, 2018;Förster & Souvignier, 2015;L. S. Fuchs et al, 1990;Keuning et al, 2019;Staman et al, 2017).…”

Exploratory Data Analysis in Schools: A Logic Model to Guide Implementation

“…In schools where DDDM systems are in place, they are generally led by district-level administrators and tied to specific goals, outcomes, or the formal accountability structures stemming from high-stakes testing (Carrier & Whaland, 2017;Noyce, Perda, & Traver, 2000). Left untended, DDDM procedures have little impact on student outcomes, but some research has shown that, with training, impacts on student achievement can be seen (Carrier & Whaland, 2017;Crone, Carlson, Haack, Kennedy, Baker, & Fine, 2016;Keuning, van Geel, Visscher, & Fox, 2016). In a best-practice scenario, DDDM models can be effectively deployed when leadership makes it a priority and develops an open and collaborative school culture (Lange, Range, & Welsh, 2012).…”