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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
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
McAllister, Deborah A., Ed.; Cutcher, Cortney L., Ed. – Online Submission, 2011
As a part of the teacher licensure program at the graduate level at The University of Tennessee at Chattanooga (UTC), the M.Ed. Licensure candidate is required to complete an action research project during a 3-semester-hour course that coincides with the 9-semester-hour student teaching experience. This course, Education 5900 Culminating…
Descriptors: Action Research, Research Projects, Student Attitudes, Economics Education

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