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Sorensen, Lucy C. – Educational Administration Quarterly, 2019
Purpose: In an era of unprecedented student measurement and emphasis on data-driven educational decision making, the full potential for using data to target resources to students has yet to be realized. This study explores the utility of machine-learning techniques with large-scale administrative data to identify student dropout risk. Research…
Descriptors: At Risk Students, Dropouts, Data Collection, Data Analysis
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Dogru, Mustafa; Sarac, Esra – Educational Research and Reviews, 2013
The purpose of this study is to reveal the metaphors of primary school students (n = 362) relating to the concept of global warming. Data collected by completing the expression of "global warming is like..., because..." of the students were analysed by use of qualitative and quantitative data analysis techniques. According to findings of…
Descriptors: Elementary School Students, Environmental Education, Data Collection, Figurative Language
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Beighle, Aaron; Alderman, Brandon; Morgan, Charles F.; Le Masurier, Guy – Research Quarterly for Exercise and Sport, 2008
Seasonality appears to have an impact on children's physical activity levels, but equivocal findings demand more study in this area. With the increased use of pedometers in both research and practice, collecting descriptive data in various seasons to examine the impact of seasonality on pedometer-measured physical activity among children is…
Descriptors: Physical Activities, Females, Physical Activity Level, Elementary School Students
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Carmo, Mafalda, Ed. – Online Submission, 2017
This book contains a compilation of papers presented at the International Conference on Education and New Developments (END 2017), organized by the World Institute for Advanced Research and Science (W.I.A.R.S.). Education, in our contemporary world, is a right since we are born. Every experience has a formative effect on the constitution of the…
Descriptors: Educational Quality, Models, Vocational Education, Outcomes of Education