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Laanan, Frankie Santos; Sanchez, Jorge R. – New Directions for Community Colleges, 1996
Examines the discussion surrounding the establishment of a reliable transfer rate measure by outlining the major arguments advanced by scholars and researchers in the field. Discusses traditional models of calculating transfer rates, their strengths and weaknesses, and introduces nontraditional transfer rate models. (24 citations) (AJL)
Descriptors: College Transfer Students, Community Colleges, Data Interpretation, Evaluation Methods
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Spicer, Scot L.; Armstrong, William B. – New Directions for Community Colleges, 1996
Discusses the difficulty in obtaining transfer rates due to the disagreement over definitions of "transfer." Compares different options to show how manipulating the pool of eligible transfer students influences transfer rates. Describes transfer-ready models for calculating transfer eligibility rate, as well as the Student Right-to-Know formula.…
Descriptors: College Transfer Students, Community Colleges, Data Interpretation, Evaluation Methods
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Slavin, Robert E. – Educational Leadership, 2003
Expresses the importance of scientifically based research in education reform and explains how to judge the validity of educational research. Describes control groups, randomized and matched experiments, statistical educational significance, sample size, and the difference between scientifically based and rigorously evaluated research. (Contains…
Descriptors: Control Groups, Data Interpretation, Educational Research, Elementary Secondary Education
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Underwood, Jean; Underwood, Geoffrey – British Journal of Educational Psychology, 1987
Discussion of the use of computer-based information retrieval systems in schools focuses on three paper and pencil experiments conducted in the United Kingdom that were designed to investigate how 9- to 11-year-olds organized and retrieved information from four organizational structures: lists, hierarchies, networks, and tables. (18 references)…
Descriptors: Analysis of Variance, Cognitive Processes, Computer Assisted Instruction, Correlation
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Norwood, Janet L. – Journal of Economic Education, 1994
Asserts that policymakers and the general public should be well informed about economic and social issues. Contends that a statistical system in a democracy has a heavy responsibility to ensure that the data represent fact, not opinion. Discusses changes made in the Consumer Price Index to prevent it from becoming politicized. (CFR)
Descriptors: Citizen Participation, Cost Indexes, Data Interpretation, Databases
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Phillips, Mark P. – Science Activities, 1992
Describes the construction of durable, inexpensive and large sand-hourglasses for use in controlled experiments that allow students to observe, infer, measure, record data, and predict. This hands-on activity is designed to take place over a three-day interval. Includes materials needed, techniques, procedures, follow-up activities, and resource…
Descriptors: Concept Formation, Data Collection, Data Interpretation, Discovery Learning
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Davis, Richard A.; Sandall, Orville C. – Chemical Engineering Education, 1991
Described is a membrane experiment that provides students with experience in fundamental engineering skills such as mass balances, modeling, and using the computer as a research tool. Included are the experimental design, theory, method of solution, sample calculations, and conclusions. (KR)
Descriptors: Chemical Engineering, Chemistry, College Science, Computer Uses in Education
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Mitchell, Douglas E.; And Others – Peabody Journal of Education, 1989
Article reanalyzes and expands upon data from Tennessee's Project STAR which examined the effects of class size reduction on student achievement in the primary grades. It describes six competing theories of class size impact on achievement and test performance, settling on the student group/modeling interpretation of study data. (SM)
Descriptors: Academic Achievement, Achievement Gains, Class Size, Data Interpretation
Ross, Kenneth N. – Prospects, 1992
Contends that the high quality of the probability sampling used by the International Association for the Evaluation of Educational Achievement (IEA) is due, in large part, to procedures developed by IEA's first statistical consultant, Gilbert Peaker. Concludes that the Peaker process is a first-class sample design. (CFR)
Descriptors: Academic Achievement, Comparative Education, Cross Cultural Studies, Data Interpretation
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Swanson, H. Lee – Remedial and Special Education (RASE), 1993
This article presents guidelines for "beginning" career researchers on developing a research program, focusing on topic choice, research methodology quality, coauthoring, funding, and selection of journal for publication. Career models in special education research are described, the importance of careful interpretation of research data is…
Descriptors: Career Development, Data Interpretation, Disabilities, Educational Research
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Spitz, Herman H.; And Others – Intelligence, 1993
H.H. Spitz argues that interesting results from the preschool intervention of the Abecedarian Project continue to be disregarded. C.T. Ramey reiterates his earlier objections to Spitz's conclusions, and H.H. Spitz rejoins with specific objections to Ramey. (SLD)
Descriptors: Ability, Age Differences, Control Groups, Criticism
Burley, Hansel – American School Board Journal, 2001
Disappointing high-stakes test results matter far less than the type of future citizens that schools produce. Citizenship values (teamwork, leadership, and neighborliness) are not assessed well by multiple-choice exams. Poor performers should not be segregated, data should be reinterpreted, and remediation should stress tutoring interventions, not…
Descriptors: Accountability, Citizenship Education, Data Interpretation, Elementary Secondary Education
Bracey, Gerald W. – Phi Delta Kappan, 2000
Mountains of data over 10 years show that the educational sky is not falling. This article deplores critics' disregard of the Sandia Report, American policymakers' test-craziness and education/economic productivity obsessions, the overrated "Texas Miracle," National Education Goals, and weighty student backpacks. (MLH)
Descriptors: Comparative Education, Data Interpretation, Education Work Relationship, Educational History
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Long, Jeffrey D. – Psychological Methods, 2005
Often quantitative data in the social sciences have only ordinal justification. Problems of interpretation can arise when least squares multiple regression (LSMR) is used with ordinal data. Two ordinal alternatives are discussed, dominance-based ordinal multiple regression (DOMR) and proportional odds multiple regression. The Q[superscript 2]…
Descriptors: Simulation, Social Science Research, Error of Measurement, Least Squares Statistics
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Theobald, Rebecca – International Research in Geographical and Environmental Education, 2005
The influence of location as exemplified by neighbourhood factors and school characteristics on primary education is examined in the context of the school choice movement of the last two decades. The analysis incorporates statistical information about schools and population data from Census 2000 describing neighbourhoods and schools in one…
Descriptors: Primary Education, School Choice, Statistical Data, Socioeconomic Influences
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