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Samantha Fu; Charles Davis; Jesse Rothstein; Aparna Ramesh; Evan White – Grantee Submission, 2022
Linking data together can be a powerful way for governments and researchers alike to tackle vexing public policy research problems. However, for researchers, finding ways to link data directly between two departments can often be more challenging than even obtaining the data in the first place. Even when a researcher develops the necessary…
Descriptors: Data Use, Research Methodology, Researchers, Privacy
Daugherty, Lindsay – Grantee Submission, 2020
"Stackable credential programs" are designed to make it easier for students to earn multiple postsecondary certificates or degrees in a field as they advance in their careers. To examine the stacking of credentials in Ohio and inform ongoing efforts to scale stackable credential programs, the Ohio Department of Higher Education and the…
Descriptors: Data Use, Educational Improvement, Postsecondary Education, Credentials
Kara J. Beckman; Angeline Gacad; Barbara McMorris – Grantee Submission, 2023
Schools are increasingly turning towards restorative practices as a pathway to building schools with stronger relationships, justice, and equity. While effectiveness studies are increasing, too little attention is focused on evaluating implementation. This resources is for audiences who evaluate implementation of whole school restorative practices…
Descriptors: Program Implementation, Program Evaluation, Discipline, Justice
De Los Reyes, Andres; Cook, Clayton R.; Gresham, Frank M.; Makol, Bridget A.; Wang, Mo – Grantee Submission, 2019
Psychosocial functioning plays a key role in students' wellbeing and performance inside and outside of school. As such, techniques designed to measure and improve psychosocial functioning factor prominently in school-based service delivery and research. Given that the different contexts (e.g., school, home, community) in which students exist vary…
Descriptors: Psychological Patterns, Well Being, Information Sources, Student Adjustment
Wang, Yutao; Heffernan, Neil T.; Heffernan, Cristina – Grantee Submission, 2015
The well-studied Baker et al., affect detectors on boredom, frustration, confusion and engagement concentration with ASSISTments dataset were used to predict state tests scores, college enrollment, and even whether a student majored in a STEM field. In this paper, we present three attempts to improve upon current affect detectors. The first…
Descriptors: Majors (Students), Affective Behavior, Psychological Patterns, Predictor Variables