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Building Community and Capacity for Data-Intensive Evidence-Based Decision Making in Schools and Districts

NSF DGE 1560720, 2016-2019

Evidence-based decision making in schools and districts is a growing area of research and practice, in which teachers and administrators come together around their students' data to build capacity and inform instructional decision making. The goal of this project is to build a researcher-practitioner community around data-intensive evidence-based decision making through bringing together large and diverse school district datasets and then applying recent innovations from the data sciences to pilot and test data analytics with teachers and administrators. This will provide a test-bed and exemplars which will be used to spur capacity building between and among researchers and current school leaders around the data currently in use in their schools.

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BIGDATA: Using Big Data to Investigate Longitudinal Education Outcomes through Visual Analytics

NSF IIS 1546653, 2015-2017

National Science Foundation: IIS #1546653 - Data science techniques have revolutionized many academic fields and led to terrific gains in the commercial sector. They have to date been underutilized in solving critical problems in the US educational system, particularly in understanding Science, Technology, Engineering and Mathematics (STEM) learning and learning environments, broadening participation in STEM, and increasing retention for students traditionally underserved in STEM. The goals of the Directorate for Education and Human Resources (EHR), through the EHR Core Research program, for the Critical Techniques and Technologies for Advancing Foundations and Applications of Big Data Science & Engineering (BIGDATA) program are to advance fundamental research aimed at understanding and solving these critical problems, and to catalyze the use of data science in Education Research. This Early Concept Grant for Exploratory Research (EAGER) will employ data from national representative datasets including approximately 35,000 students to investigate course taking patterns in high school and how these relate to critical outcomes such as college attendance, high school and college success, and career choices. Few investigators have attempted to answer this question with this scale of data. Therefore, this proposal will contribute significantly to the field's understanding of factors that affect success in high school and college. Building on these new insights will enable the potential to create interventions at the high school and college level based on data about what works to improve graduation and workforce outcomes.

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