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Showing 1 to 15 of 16 results Save | Export
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Swank, Jacqueline M.; Mullen, Patrick R. – Measurement and Evaluation in Counseling and Development, 2017
The article serves as a guide for researchers in developing evidence of validity using bivariate correlations, specifically construct validity. The authors outline the steps for calculating and interpreting bivariate correlations. Additionally, they provide an illustrative example and discuss the implications.
Descriptors: Correlation, Construct Validity, Guidelines, Data Interpretation
Creswell, John W. – Pearson Education, Inc., 2015
"Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research" offers a truly balanced, inclusive, and integrated overview of the processes involved in educational research. This text first examines the general steps in the research process and then details the procedures for conducting specific types…
Descriptors: Educational Research, Qualitative Research, Statistical Analysis, Research Methodology
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
Aspen Institute, 2013
Never before has the link between a college education and postgraduate job prospects been more important. College graduates are employed more often and, on average, earn significantly more than those without college degrees. During recent years, as students have moved into a challenging job market, a college education has remained the most…
Descriptors: Community Colleges, Labor Market, Information Utilization, Guidelines
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
Castellano, Katherine E.; Ho, Andrew D. – Council of Chief State School Officers, 2013
This "Practitioner's Guide to Growth Models," commissioned by the Technical Issues in Large-Scale Assessment (TILSA) and Accountability Systems & Reporting (ASR), collaboratives of the "Council of Chief State School Officers," describes different ways to calculate student academic growth and to make judgments about the…
Descriptors: Guides, Models, Academic Achievement, Achievement Gains
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Cunningham, Alisa – Change: The Magazine of Higher Learning, 2007
What people know about higher education may depend on which data they look at and how they examine them. Responsible analysts should present a full picture of their sources of data and the limitations of those sources, restricting their conclusions to those that the data genuinely warrant. When new research conflicts with previous results, enough…
Descriptors: Educational Assessment, Higher Education, Data Analysis, Context Effect
Washington State School Directors' Association (NJ1), 2008
This guide is designed to inform school directors about the value of a data dashboard and to provide information on how districts can create a data dashboard for school directors. A data dashboard is a tool for viewing and analyzing student achievement and performance data. Key data for monitoring student achievement and directing policy level…
Descriptors: Educational Improvement, Academic Achievement, Charts, School Effectiveness
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McNeil, Keith; Newman, Isadore – Mid-Western Educational Researcher, 1994
Meta-analysis synthesizes related research by considering three major factors: sample size, magnitude of significance, and statistical test used. These factors produce an effect size, expressed as a correlation or as a difference between means, divided by the standard deviation. Discusses ways to use effect size when results are not consistent and…
Descriptors: Data Interpretation, Effect Size, Literature Reviews, Meta Analysis
Carr, Clay; Totzke, Larry – Performance and Instruction, 1995
Discusses two tools necessary for the successful practice of human performance technology: gathering data and interpreting data. The focus is on what data to gather, how to gather it, and how to interpret the data. (Author/JKP)
Descriptors: Data Analysis, Data Collection, Data Interpretation, Human Factors Engineering
Busch, Deborah – 1999
This report examines how Juvenile Detention Alternatives Initiative (JDAI) sites used data to plan reforms and assess reform success, noting where and how they gathered data. Chapter 1, "The Need for Data," discusses: assessing data utilization, using data to enhance communication, and using this report to support reform. Chapter 2,…
Descriptors: Adolescents, Computers, Data Collection, Data Interpretation
Levesque, Karen; Bradby, Denise; Rossi, Kristi; Teitelbaum, Peter – 1998
This book discusses how to use everyday data to create strategies for educational improvement in schools. It provides users with a process for building a performance indicator system, identifying the most important aspects of a school's innovational efforts and traps to avoid that may lead to misinterpretation of data. The introduction identifies…
Descriptors: Data Analysis, Data Interpretation, Educational Assessment, Educational Improvement
Clagett, Craig A. – 1990
Guidelines are offered to institutional researchers and planning analysts for presenting research results in formats and levels of sophistication that are accessible to top management. Fundamental principles include: (1) know what is needed; (2) know when the information is needed; (3) match format to analytical sophistication and learning…
Descriptors: Communication (Thought Transfer), Data Interpretation, Higher Education, Information Dissemination
Schalock, Robert L.; Kiernan, William E.; McGaughey, Martha J. – 1992
Targeted to mental retardation/developmental disability (MR/DD) and vocational rehabilitation agencies, developmental disabilities councils, consumer and advocate groups, and protection and advocacy programs, this manual is designed to assist in the development of state-level data systems responsive to current accountability requirements. It also…
Descriptors: Adults, Data Collection, Data Interpretation, Database Design
Reder, Nancy – National Post-School Outcomes Center, 2006
The purpose of this document is to give state directors of special education, especially those who are new in their positions, a guide to understanding their role and responsibilities with respect to the collection, analysis and reporting of post-school outcomes data for Indicator 14 of the Part B State Performance Plan (SPP). To assist state…
Descriptors: Elementary Secondary Education, Educational Objectives, Outcomes of Education, Disabilities
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