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Berkner, Lutz – New Directions for Institutional Research, 2000
Provides information regarding the National Educational Longitudinal Study database that was used for many of the studies in this volume. Provides relevant background and instructions so that others may use this resource from the National Center for Education Statistics. (Author/EV)
Descriptors: Data Interpretation, Databases, Educational Research, Information Utilization
Wylie, Peter B. – Currents, 2001
Presents 10 questions that development officers should be able to answer from their database and the powerful implications this data mining has for both annual and major giving programs. Discusses development officers' increasing need for in-house expertise in data analysis. (EV)
Descriptors: Data Interpretation, Databases, Donors, Fund Raising
Lachat, Mary Ann – 2001
High schools are increasingly expected to use data for improvement and to provide evidence that programs and instructional practices are preparing all students to develop essential knowledge and skills. This publication describes how schools can develop the capacity to analyze and use data as a core component of improving secondary schools using…
Descriptors: Academic Achievement, Data Analysis, Data Collection, Data Interpretation
Bank, Adrianne; Williams, Richard C. – 1985
This document is divided into two parts: the first presents a taxonomy of questions designed for a hypothetical computer database; the second describes the rationale for a question oriented approach to data. This taxonomy is described as a list of questions an educator might use to find out more about the achievement, attendance, and…
Descriptors: Academic Achievement, Attendance Records, Classification, Computer Oriented Programs
Sirotnik, Kenneth A.; And Others – 1985
This paper presents a study of the contrast of social and clinical perspectives on the selection and use of information by school staff, including: (1) an outline of the context and activities of the study; (2) a definition and discussion of the basic distinction between social and clinical perspectives; (3) an examination of case material…
Descriptors: Academic Achievement, Computer Oriented Programs, Data Interpretation, Databases
Eckels, Elaine; Vorek, Robert – 1988
The Migrant Student Record Transfer System (MSRTS) is a nationwide computer-based communications network originally designed to transfer the health and educational records of migrant workers' children. This report assesses MSRTS data from September 1984 through June 1986 to determine the potential utility of such data for national studies of the…
Descriptors: Achievement Rating, Achievement Tests, Data Interpretation, Databases
Gutmann, Babette; And Others – 1988
This report examines federal, state, and local databases containing information on migrant workers and their children, identifies their common characteristics, and assesses their potential utility to inform educational policy analysis. General criteria used to evaluate each database's strengths and weaknesses include standardization, reliability,…
Descriptors: Data Interpretation, Databases, Elementary Secondary Education, Evaluation
Stevens, David W.; And Others – 1992
This report presents findings of a demonstration project that tested the concepts and applications of linking student records using social security numbers with state unemployment insurance (UI) wage and other data sources. It also contains information of value to policymakers, state and local administrators, practitioners, and consumers of…
Descriptors: Data Analysis, Data Collection, Data Interpretation, Data Processing
Ohio State Univ., Columbus. Center for Human Resource Research. – 1993
This practical manual is designed as a guide for those working with one or more of the National Longitudinal Surveys (NLS) data sets. Section 1 is a discussion of the sample design, sampling methodology, and field procedures used during the surveys of each NLS cohort. Weighting, sample representativeness, and attrition are discussed, and a series…
Descriptors: Adult Education, Career Planning, Data Collection, Data Interpretation