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Showing 1 to 15 of 24 results Save | Export
Jessica Arnold; Julie Webb – WestEd, 2024
While there are many different types of education data, policymakers and education leaders often place heavy emphasis on data from large-scale quantitative measures, such as annual state assessments. But data from these sources alone do not provide a complete picture of learning and are often not well suited to informing improvements at the local…
Descriptors: Data Use, Measurement, Educational Improvement, Outcomes of Education
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Laura Smithers – Change: The Magazine of Higher Learning, 2024
Speculative reform jumps the gun on notions of data-driven reform, requiring administrators to anticipate and act to ensure problems (and the data that would show them) do not materialize. Speculative reforms are incapable of delivering the outcomes they promise, as they are fueled by a fear of the future that their reforms do not extinguish. In…
Descriptors: Educational Policy, Higher Education, Educational Change, Outcomes of Education
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Anderson, Billie; Marx, Dea; Cox, Kelline S.; McNeley, Kim; Filion, Diane L. – Assessment Update, 2023
The University of Missouri Kansas City (UMKC) is an urban research university with a special emphasis on fostering diversity. In 2021, the Center for Advancing Faculty Excellence created a Faculty Fellows program to develop comprehensive resources and support in four areas: teaching and learning, service and engagement, research and creativity,…
Descriptors: Data Use, Outcomes of Education, Program Effectiveness, Faculty Development
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Alturki, Sarah; Hulpu?, Ioana; Stuckenschmidt, Heiner – Technology, Knowledge and Learning, 2022
The tremendous growth of educational institutions' electronic data provides the opportunity to extract information that can be used to predict students' overall success, predict students' dropout rate, evaluate the performance of teachers and instructors, improve the learning material according to students' needs, and much more. This paper aims to…
Descriptors: Grade Prediction, Academic Achievement, Data Use, Dropout Rate
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Nahar, Gul; Urick, Angela; Wescoup, Stephanie M.; Jang, Chang Sung; Cascio, Casey J.; Unsicker-Durham, Shelly K. – AASA Journal of Scholarship & Practice, 2022
Many school educators struggle to reconcile the onslaught of mandatory and competing, top-down policies. Educators must merge policies into a singular plan that reflects the local stakeholders' goals and values. Given the federal and state accountability movement, schools are forced to build capacity around the use of on-site data and research…
Descriptors: Educational Improvement, Educational Planning, Evidence Based Practice, Educational Policy
Miguel A. Cardona – Office of Elementary and Secondary Education, US Department of Education, 2022
Data from high-quality State assessments can inform instruction and help school leaders drive resources to the schools and students that need them the most. This dear colleague letter from the U.S. Secretary of Education reminds all who report and interpret student outcomes this year that assessment data has always been meant to be used…
Descriptors: Evaluation Methods, Evaluation Utilization, Decision Making, Resource Allocation
Morris, Kelsey; Feinberg, Adam – Center on Positive Behavioral Interventions and Supports, 2022
Prioritizing social, emotional, and behavioral supports is essential for student success. By establishing systems to support students' social (how they interact), emotional (how they feel), and behavioral (how they act) needs and growth, educators and leaders can ensure that all students have full access to instruction and the essential skills for…
Descriptors: Fidelity, Data Collection, Positive Behavior Supports, Multi Tiered Systems of Support
Isaac, James; Pretlow, Josh; Cheng, Diane; Roberson, Amanda Janice – Institute for Higher Education Policy, 2022
We cannot continue to ask students -- and their families -- to make one of the largest and most important investments of their lives without clearer information about what their time and money will yield. Fortunately, support is broad across the country and across the political spectrum for a federal student-level data network (SLDN), which would…
Descriptors: College Students, Information Networks, Federal Programs, Higher Education
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Foster, Elizabeth – Learning Professional, 2021
Acting to dismantle structural racial inequities begins with identifying and clearly naming the challenges being faced. Data play a powerful role in this process. Several recent publications synthesize data sources, research findings, and expert recommendations to inform and guide equity improvement efforts. A five-part "Statement of the…
Descriptors: Data Use, Equal Education, Racial Discrimination, Data Analysis
National Comprehensive Center, 2024
The School Spending & Outcomes Snapshot allows users to view and print data visualizations to explore spending and outcomes data in order to foster thoughtful conversations to improve equity and outcomes in their schools communities.
Descriptors: Educational Improvement, Data Use, Decision Making, Visual Aids
Hoffman, Nancy; O'Connor, Anna; Mawhinney, Joanna – Jobs for the Future, 2022
The purpose of this brief is to provide school-level examples of how early college practitioners are collecting and using data to improve their practices. Examples three and four are school-level data from two early college partnerships: the MetroWest CPC (Framingham, Milford, Waltham), and Lawrence. The brief begins, however, with the national…
Descriptors: College School Cooperation, Partnerships in Education, High Schools, Universities
Postsecondary Value Commission, 2021
The "action agenda" is a key deliverable for the Postsecondary Value Commission that outlines policies and practices that institutional leaders, federal policymakers, and state policymakers should implement to address systemic barriers that prevent Black, Latinx, Indigenous, and AAPI students, students from low-income backgrounds, and…
Descriptors: Outcomes of Education, Access to Education, Student Costs, Graduation
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Rafalow, Matthew H.; Puckett, Cassidy – Educational Researcher, 2022
Existing scholarship suggests that schools do the work of social stratification by functioning as "sorting machines," or institutions that determine which populations of students are provided educational resources needed to help them get ahead. We build on this theory of social reproduction by extending it to better understand how…
Descriptors: Technology Uses in Education, Social Stratification, Resource Allocation, Data Use
Isaac, James; Velez, Erin; Roberson, Amanda Janice – Institute for Higher Education Policy, 2023
Students, families, colleges, and lawmakers need clearer information on postsecondary outcomes to make informed decisions. By leveraging data available at institutions and federal agencies, a nationwide student-level data network (SLDN) would close information gaps that persist in our higher education landscape to answer critical questions about…
Descriptors: College Students, Data, Information Networks, Program Design
National Forum on Education Statistics, 2023
This guide is designed for use by school, district, and state education agency staff to improve the effectiveness of efforts to collect and use discipline data, including reporting accurate and timely data to the federal government. It explains the importance of collecting discipline data, identifies key considerations for agencies implementing…
Descriptors: Discipline, Data Collection, Data Analysis, School Districts
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