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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
Bulgakov-Cooke, Dina; Singh, Malkeet – Wake County Public School System, 2018
The Multi-Tiered System of Support (MTSS) framework, which uses a systems approach to promote school improvement and support all students in improving academics and behavior using data-based problem-solving, is a key part of the Wake County Public Schools System (WCPSS) Strategic Plan. As of 2017-18, MTSS schools were at the initial stages of MTSS…
Descriptors: Program Effectiveness, Reading Achievement, Academic Achievement, Student Behavior