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Arnold, Lydia; Norton, Lin – Higher Education Academy, 2018
This resource has been written specifically for higher education practitioners who are interested in improving students' learning experiences through the process of researching their own practice. We use the term 'higher education practitioners' to describe all who work in universities and who have a stake in students' learning experiences.…
Descriptors: Higher Education, Educational Research, Action Research, Definitions
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
Kinder, Ann – NCREL's Learning Point, 2000
Discusses the importance of the process of making decisions based on data referred to as data-driven decision making, or D3M. Presents guidelines for teachers to consider when implementing a data-driven decision making process. (ASK)
Descriptors: Data Interpretation, Decision Making, Educational Change, Elementary Secondary Education
Thomas, R. Murray – 2003
This guide discusses combining qualitative and quantitative research methods in theses and dissertations. It covers a wide array of methods, the strengths and limitations of each, and how they can be effectively interwoven into various research designs. The first chapter is "The Qualitative and the Quantitative." Part 1, "A…
Descriptors: Data Analysis, Data Collection, Data Interpretation, Doctoral Dissertations
Peer reviewedWhiteley, Meredith A.; Stage, Frances K. – New Directions for Institutional Research, 1987
The widespread use of comparative data can lead to problems on a campus unless the data are systematically incorporated in the institutional planning cycle. A model has been developed to alleviate a number of problems and increase the power of comparison as a management tool. (MSE)
Descriptors: College Planning, Comparative Analysis, Data Interpretation, Higher Education
Bernhardt, Victoria L. – 1998
Data can help identify solutions to some of the biggest problems in schools. Yet few schools use data effectively. The purpose of this book is to help schools become aware of the advantages of collecting and using data (data analysis) for overall school improvement. The book begins with an overview of the current state of education and the…
Descriptors: Automation, Data Analysis, Data Collection, Data Interpretation
Recruiting New Teachers, Inc., Belmont, MA. – 1998
This handbook is designed to help beginning evaluators of teacher recruitment programs. It addresses the information and assessment needs of teacher recruitment programs. It takes a hands-on approach and includes worksheets and instructions for using them. After presenting tips for getting started, the handbook offers eight steps to successful…
Descriptors: Data Analysis, Data Collection, Data Interpretation, Elementary Secondary Education
Iowa State Occupational Information Coordinating Committee, Des Moines. – 1985
This guide is intended to assist planners in developing and using labor market and occupational information when assessing the need for and planning occupational training programs. The first chapter discusses the responsibilities of various federal, state, and local entities for developing labor market information. Special attention is given to…
Descriptors: Data Interpretation, Information Sources, Information Utilization, Labor Market
Peer reviewedBrinkman, Paul T.; Teeter, Deborah J. – New Directions for Institutional Research, 1987
Institutional comparison groups can be selected in several ways, depending on the comparison issue. The method chosen involves both technical and political considerations. (Author/MSE)
Descriptors: Comparative Analysis, Data Analysis, Data Interpretation, Higher Education
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
Peer reviewedTheall, Michael; Franklin, Jennifer – New Directions for Teaching and Learning, 1991
For student rating data to be useful in improving college teaching, consultants and faculty need to know how different evaluative purposes effect evaluation results, and they must be able to interpret and use the data at hand. A series of steps should be followed to help ensure valid data interpretation. (MSE)
Descriptors: College Instruction, Data Interpretation, Faculty Evaluation, Feedback
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
National Council on Measurement in Education, Washington, DC. – 1990
The assessment competencies set forth in this monograph are knowledge and skills critical to a teacher's role as an educator. It is suggested that the seven standards described as essential for educational assessment of students be incorporated into future teacher training and certification programs. The standards require that teachers be skilled…
Descriptors: Competence, Data Interpretation, Decision Making, Educational Testing
Learning, 1995
Skillful, scientific observation of even one student having difficulty can give teachers ideas for helping all of their students. Discusses planning observation time, tools for observation, and how to observe students and interpret observations. Provides specific suggestions for five observed behaviors and sources of more information (two…
Descriptors: Classroom Observation Techniques, Classroom Research, Data Interpretation, Elementary Education
American Association of School Administrators, Arlington, VA. – 2002
School system leaders are discovering the power of data for promoting school improvement. This guide provides practitioners, parents, and community with insights and tools for cultivating a districtwide culture of data-driven inquiry. Chapter 1 points out that data provide quantifiable proof, taking the emotion and rancor out of the…
Descriptors: Academic Achievement, Accountability, Data Analysis, Data Collection

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