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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
Martin, Merissa R.; Pickett, Matt T. – Online Submission, 2013
The purpose of this action research project report was to increase student motivation and engagement. There seemed to be an increasing disconnect between student potential and performance, especially among gifted math and beginning music students. Two teacher researchers carried out this research with 25 fifth-grade students at two different sites…
Descriptors: Academically Gifted, Student Motivation, Learner Engagement, Individualized Instruction
Godzicki, Linda; Godzicki, Nicole; Krofel, Mary; Michaels, Rachel – Online Submission, 2013
This action research project report was conducted in order to increase motivation and engagement in elementary and middle school students through technology-supported learning environments. The study was conducted from August 27, 2012, through December 14, 2012 with 116 participating students in first-, fourth-, fifth- and eighth-grade classes. To…
Descriptors: Educational Environment, Homework, Educational Technology, Student Motivation
Xia, Nailing – RAND Corporation, 2010
There is considerable debate about the relative importance of family versus school factors in producing academic and nonacademic student outcomes, and whether and how their impacts vary across different student groups. In addition to critically reviewing and synthesizing earlier work, this study extends the literature by (a) using the ECLS-K, a…
Descriptors: Blacks, Whites, Asians, Latin Americans