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Peer reviewedAiken, Lewis R. – Educational and Psychological Measurement, 1994
Three dozen observations and recommendations concerning the activities of research consultants in the behavioral sciences are listed and discussed. These guidelines, some stated as aphorisms, are discussed in the categories of planning; implementation; analysis; interpretation; and reporting. (Author/SLD)
Descriptors: Behavioral Sciences, Data Analysis, Data Interpretation, Guides
Peer reviewedBracey, Gerald W. – Educational Leadership, 1993
Disagrees with Harold Stevenson's article in same "Educational Leadership" issue; Stevenson compares incomparable groups of students and misinterprets data. Although U.S. students rate ability higher than Chinese students, they also appreciate value of effort. Chicago kids are poorer and come from larger families than their Chinese…
Descriptors: Academic Achievement, Comparative Education, Cultural Differences, Data Interpretation
Peer reviewedPeverly, Stephen T. – Review of Educational Research, 1991
The claim that knowledge alone accounts for variance of memory and development (MAD) is critiqued. Topics include the movement toward a knowledge-based view of MAD and problems with this approach; data suggesting that domain-independent strategies influence MAD; and evidence for a domain-independent tool of developmental import. (SLD)
Descriptors: Cognitive Processes, Data Interpretation, Development, Knowledge Level
Peer reviewedSnyder, Patricia; Lawson, Stephen – Journal of Experimental Education, 1993
Why methodologists encourage the use of magnitude-of-effect (ME) indices as research interpretation aids is discussed, and different types of ME estimates are reviewed. Correction formulas developed to alternate statistical bias in ME estimates are also discussed, and their effects are illustrated. (SLD)
Descriptors: Data Interpretation, Effect Size, Estimation (Mathematics), Research Methodology
Peer reviewedPrince, Jeffrey P. – Career Development Quarterly, 1998
A career counselor describes how he prepares for and carries out an interpretation of a female client's responses to the Strong Interest Inventory. Demonstrates the variety of information contained in a Strong profile and the flexibility with which a counselor might adapt an interpretation to the needs and goals of a client. (MKA)
Descriptors: Career Counseling, Case Studies, Data Interpretation, Females
Peer reviewedHartung, Paul J. – Career Development Quarterly, 1998
Interprets the results of utilizing the Salience Inventory (SI) and the Values Scale (VS) with a 29-year-old female high school teacher. Describes the four steps of the Career Development Assessment and Counseling model: preview, depth-view, data assessment, and counseling. (MKA)
Descriptors: Career Counseling, Case Studies, Data Interpretation, Females
Interpreting Experimental Data: The Views of Upper Secondary School and University Science Students.
Peer reviewedRyder, Jim; Leach, John – International Journal of Science Education, 2000
Examines student views about the interpretation of experimental data within a specified science context. A written survey was completed by 731 students drawn from upper secondary schools and universities in five European countries. Data support previous studies that found that science students tend not to recognize the role of theoretical models…
Descriptors: Data Interpretation, Foreign Countries, Higher Education, Models
Peer reviewedAinley, Janet; Nardi, Elena; Pratt, Dave – International Journal of Computers for Mathematical Learning, 2000
Describes research using a pedagogic strategy developed during an exploratory work called Active Graphing in which access to spreadsheets allows graphs to be used as analytic tools within practical experiments. Identifies aspects of student interaction with the experiment itself, the data collected and the graphs, and traces the emergence of…
Descriptors: Computer Uses in Education, Data Interpretation, Elementary Education, Graphs
Peer reviewedKalinowski, Joseph; Rastatter, Michael P.; Stuart, Andrew; Ingham, Roger J.; Ingham, Janis C.; Cordes, Anne K.; Moglia, Richard – Journal of Speech, Language, and Hearing Research, 1998
The authors (Ingham et al.) of the original report respond to criticisms by Kalinowski et al. that they misinterpreted their data in a study of the effects of frequency-altered feedback on stuttering in four single-subject design investigations. They also address larger issues concerning altered auditory feedback procedures. (DB)
Descriptors: Auditory Perception, Data Analysis, Data Interpretation, Feedback
Peer reviewedKavale, Kenneth A. – Exceptionality, 2001
Discussion of the methods of meta-analysis first identifies problems associated with research integration, the limitations of traditional review techniques, and the advantages of quantitative methods. Meta-analytic procedures are described with respect to how they parallel classical scientific method, including problem formulation, sampling,…
Descriptors: Data Interpretation, Disabilities, Elementary Secondary Education, Meta Analysis
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
Roth, Wolff-Michael – International Journal of Computers for Mathematical Learning, 2003
Past research has shown that many scientists, when asked to interpret unfamiliar graphs that have nevertheless been culled from introductory undergraduate courses in their own field, experience problems and cannot give the standard answer accepted in the field. Yet, these same scientists turn out to be highly competent when it comes to graphs from…
Descriptors: Scientists, Laboratories, Graphs, Data Interpretation
Heritage, Margaret; Chen, Evan – Phi Delta Kappan, 2005
Without using data to inform their actions at every step of the way, teachers and administrators will probably not reach their goals for school improvement. In this article, the authors describe a CRESST initiative that helps educators develop the skills to collect, analyze, and be guided by data. Five steps to effective date use are described in…
Descriptors: Academic Achievement, Educational Improvement, Data Collection, Data Analysis
Mendick, Heather – International Journal of Inclusive Education, 2005
This paper focuses on the ways in which many researchers working in the area of gender and mathematics make sense of their data. In particular, it is argued that their use of the oppositional framing, separation versus connection (and others, such as cognition versus affect and objective versus subjective), operates to fix difference, and so to…
Descriptors: Mathematics Instruction, Mathematics Curriculum, Gender Differences, Educational Research
Johnson, L.; Levine, A.; Scott, C.; Smith, R.; Stone, S. – New Media Consortium, 2009
The New Media Consortium's Horizon Project is an ongoing research project that seeks to identify and describe emerging technologies likely to have a large impact in education and other industries around the world over a five-year time period. The chief products of the project are the "Horizon Reports", an annual series of publications…
Descriptors: Small Businesses, Trend Analysis, Technological Advancement, Internet

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