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What Works Clearinghouse Rating
Data Quality Campaign, 2021
Data reflects a series of decisions made by people--and those decisions affect the story that data tells, what it captures, and how it can and should be used to inform decision-making. Because of this, mistrust in data is often the result of incomplete information and a lack of context. This resource breaks down what it means to build trust in…
Descriptors: Data Use, Data Collection, Data Analysis, Bias
Tsai, Tiffany; Tosh, Katie – RAND Corporation, 2020
Teachers' use of student data to inform instruction is commonly accepted as sound educational practice, and this data use is only likely to grow as more data, as well as more-complex data, become increasingly available to educators. However, numerous studies reveal inconsistent data use among teachers and an overall lack of the preparation and…
Descriptors: Data Analysis, Data Use, Database Management Systems, Personnel Data
Marion, S. F.; Gonzales, D.; Wiener, R.; Peltzman, A. – National Center for the Improvement of Educational Assessment, 2020
State policymakers are confronting well-documented intersecting crises -- medical, economic, and racial -- with especially dire implications for educational equity. State education leaders face a moral urgency to both understand and respond to the challenges students are experiencing and to do so in ways that address burgeoning equity gaps.…
Descriptors: State Policy, Educational Opportunities, Program Evaluation, Summative Evaluation
Hanita, Makoto; Bailey, Jessica; Khanani, Noman; Zhang, Xinxin – Regional Educational Laboratory Northeast & Islands, 2021
This applied research methods report is a guide for state and local education agency policymakers and their analysts who are interested in studying teacher mobility and retention. This report is the second in a two-part set and builds on the foundational information in report 1. This report presents guidance on how to interpret differences in…
Descriptors: Faculty Mobility, Teacher Persistence, Educational Research, Research Methodology
Gouëdard, Pierre – OECD Publishing, 2021
Across OECD countries, the increasing demand for evidence-based policy making has further led governments to design policies jointly with clear measurable objectives, and to define relevant indicators to monitor their achievement. This paper discusses the importance of such indicators in supporting the implementation of education policies.…
Descriptors: Educational Indicators, Program Implementation, Educational Policy, Policy Formation
von Zastrow, Claus; Roberts, Maxine T.; Squires, John – Education Commission of the States, 2021
State education data systems help policymakers use data to evaluate the impact of their efforts to improve education. By disaggregating the data -- that is, breaking it out by different student subgroups -- policymakers can ensure that their efforts address the needs of students who have been traditionally underserved in educational settings. Yet…
Descriptors: Data Analysis, Student Characteristics, Data Collection, Barriers
American Institutes for Research, 2014
This tool and its supporting resources are intended to help education leaders understand and assess equitable access data to support a root-cause analysis and, ultimately, draft a State Plan to Ensure Equitable Access to Excellent Educators. The activities in this tool introduce metrics, address staff capacity for analyzing equitable access data,…
Descriptors: Data, Access to Information, State Policy, Guidelines
Baldwin, Chris; Borcoman, Gabriela; Chappell-Long, Cheryl; Coperthwaite, Corby A.; Glenn, Darrell; Hutchinson, Tony; Hughes, John; Jenkins, Rick; Jovanovich, Donna; Keller, Jonathan; Klimczak, Benjamin; Schneider, Bill; Stewart, Carmen; Stuart, Debra; Yeager, Michael – Jobs for the Future, 2012
Enrollment is rising across the nation's community colleges, but completion rates remain untenably low. Reformers are focusing on the importance of using comprehensive, high-quality data on student progress and completion to bring about change. A core tenet of Achieving the Dream: Community Colleges Count has been to embed a culture of…
Descriptors: Community Colleges, Enrollment, Educational Attainment, Educational Policy
National Forum on Education Statistics, 2012
Education data are growing in quantity, quality, and value. When appropriately used to guide action, data can be a powerful tool for improving school operations, teaching, and learning. Education stakeholders who possess the knowledge, skills, and abilities to appropriately access, analyze, and interpret data will be able to use data to take…
Descriptors: Educational Indicators, Data Interpretation, Information Utilization, Data Analysis
Dorn, Sherman, Ed. – Education Policy Analysis Archives, 2006
This editorial reviews recent studies of accountability policies using National Assessment of Educational Progress (NAEP) data and compares the use of aggregate NAEP data to the availability of individual-level data from NAEP. While the individual-level NAEP data sets are restricted-access and do not give accurate point-estimates of achievement,…
Descriptors: National Competency Tests, Academic Achievement, Accountability, Data
Michelau, Demaree – Western Interstate Commission for Higher Education, 2006
This issue of Policy Insights draws on findings from WICHE's report Accelerated Learning Options: Moving the Needle on Access and Success, to lay out some of the important policy issues that decision makers might consider when adopting new state policy related to accelerated learning or modifying policies already in existence. The publication…
Descriptors: Psychoeducational Methods, Data Interpretation, Acceleration (Education), Student Attitudes

Henige, David – Journal of Academic Librarianship, 1987
This discussion focuses on the problems involved in the interpretation and verification of the data gathered and presented by the North American Collections Inventory Project. It suggests that the National Shelflist Count is a better resource for collection management and shared library resources decisions. (CLB)
Descriptors: Citation Analysis, Data Interpretation, Evaluation Criteria, Evaluation Problems
Taylor, Bruce – School Business Affairs, 1994
Five comparative data traps repeatedly come up during school negotiation sessions: (1) average salary comparisons; (2) vague salary comparisons; (3) low master's guide; (4) considering salary only; and (5) comparing benefits. Provides examples and outlines a defense against these data traps. (MLF)
Descriptors: Collective Bargaining, Data Interpretation, Elementary Secondary Education, Fringe Benefits
Armstrong, Jane; Anthes, Katy – American School Board Journal, 2001
The Education Commission of the States conducted interviews in six school districts in five different states (California, Colorado, Iowa, Maryland, and Texas) to understand how districts can use data most effectively. These districts had used data to dramatically improve student achievement. Districts that make wise use of data have strong…
Descriptors: Academic Achievement, Data Analysis, Data Interpretation, Databases

Cherfas, Jeremy – Science, 1990
Argues about the conclusion that bigger science departments are more productive than smaller ones. Indicates the conclusion cannot be supported by the data. (YP)
Descriptors: College Faculty, College Science, Data Interpretation, Faculty