Browsing by Subject "Data-based decision making"
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Item Analysis of the relationship between data use and organizational learning from teacher perspectives(2011-05) Ka, Shin-Hyun; Reyes, Pedro, 1954-; Wayman, Jeffrey C.; Heilig, Julian V.; Woolley, Jacqueline D.; Clark, Charles T.This study was conducted to explorer the relationships between teachers’ perceptions of educational data use, their school’s capacity as a learning organization, and the performance of students at their school. This study employed a quantitative research design featuring a Web-based online survey and collected data from a stratified random sample of 112 middle schools and junior high schools nested in nine school districts in Texas. I used the Dimensions of the Learning Organization Questionnaire (Watkins & Marsick, 1993, 1996) to measure the schools’ capacity as a learning organizations and the Survey of Educator Data Use (Wayman, Cho, & Shaw, 2009b) to measure teachers’ educational data use. I also used the student performance data provided by Texas Education Agency. For the data analysis, I employed the statistical techniques of multivariate analysis of covariance (MANCOVA), confirmatory factor analysis (CFA), and structural equation modeling (SEM). I found that educational data use and support did relate to the schools’ organizational learning capacity, and that this dynamic acts as an important factor in enhancing campus performance. This finding gives a clear indication that data use and support has an indirect effect on campus performance, and that this effect is mediated by organizational learning. This research is significant in that it reveals that organizational learning worked as a crucial mediating variable in enhancing student achievement through effective use of data. This finding can give meaningful direction to the pursuit of school improvement through data use in school sites, a practice that began as simple top-down policy implementation.Item Educational data use and computer data systems : policies, plans, and the enactment of practice(2011-05) Cho, Vincent, Ph. D.; Wayman, Jeffrey C.; Bailey, Diane E.; Gooden, Mark A.; Reyes, Pedro; Young, Michelle D.; McDaniel, Reuben R.Federal policies such as No Child Left Behind (NCLB) and Race to the Top (RTT) stand as examples of how teachers face increasing expectations that their activities be “data-based” or “data-driven.” Meeting these expectations requires assembling and analyzing a wide variety of data about students (e.g., demographics, discipline, locally designed tests, state test results, or longitudinal information). Computer data systems are commonly assumed to facilitate the work of educational data use. Indeed, the availability and computing power of these systems have continued to expand, further increasing the promises that these technologies hold for enhancing teaching and learning. Meaningful and widespread changes to teachers’ practices, however, have typically not occurred on a large-scale or systemic basis. Therefore, in this comparative case study of three school districts I examine the nature of districts’ efforts to improve teachers’ data use via computer data systems. I do so by examining the worldviews of various job roles in each district about data use and computer data systems. An erroneous assumption commonly made by districts was that these technologies are imbued with self-evident and predetermined effects on teacher work. Accordingly, the findings from this study speak to issues of sensemaking in districts. In them, I describe not only how teachers’ perspectives shaped their practices, but also how the alignment of perspectives among district roles influenced the implementation and success of district initiatives around computer data systems. As such, this study has implications for how districts plan, implement, and learn from initiatives around data use.Item Using student data to improve response to a multisyllabic word reading intervention : the effects of varying levels of data use(2020-06-17) Filderman, Marissa Jenette; Toste, Jessica; Clemens, Nathan; Doabler, Christian; Roberts, GregoryOne recommended way to intensify intervention, particularly for struggling readers with the most severe difficulties, is intervention intensification using student data—a process referred to as data-based individualization (DBI; Deno & Mirkin, 1977; National Center on Intensive Intervention [NCII], 2013). To date, there is a dearth of research on word reading interventions that target 4ᵗʰ and 5ᵗʰ grade students (Wanzek, Wexler, Vaughn, & Ciullo, 2010), as well as reading interventions that utilize DBI to intensify such interventions (Filderman, Toste, Didion, Peng, & Clemens, 2018). As such, this randomized controlled trial explored the use of DBI for 4ᵗʰ and 5ᵗʰ grade struggling readers within the context of a research-based multisyllabic word reading intervention (Toste, Capin, Vaughn, Roberts, & Kearns, 2017; Toste, Capin, Williams, Cho, & Vaughn, 2019). In addition to adding to the literature on this understudied population, I also evaluated whether the use of data to customize instruction at the beginning of intervention is enough to improve results of struggling readers, or whether additional adjustment using progress monitoring with explicit decision-making rules improves results above and beyond initial customization of intervention protocol. Accordingly, I compared two treatment conditions to a business-as-usual condition. One treatment condition received initial customization of intervention, with adjustments made to the amount of time students spent in each of the instructional components based on their initial decoding abilities. The second treatment condition received the same customization, but at the mid-point of the study, ongoing curriculum-based measurement and specific subskill mastery measurement was used to evaluate student response, with instruction individualized for students who demonstrated inadequate response. Results indicated that students in both treatment conditions outperformed the comparison condition on multisyllabic word reading, and that students in the DBI condition also outperformed comparison students on decoding. Both treatment conditions performed worse than the comparison on a test of sentence-level comprehension efficiency. I conclude with a discussion of the potential reasons for these findings, as well as implications and future directions for research and practice.