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Bloemer, William; Day, Scott; Swan, Karen – Online Learning, 2017
In this paper we argue that simply identifying gateway courses in which a large number of students fail or withdraw and focusing attention on them may not always be the best use of limited resources. No matter what we do, there will always be courses with high D/F/W rates simply because of the nature of their content and the preparation of the…
Descriptors: Courses, Success, Academic Persistence, School Holding Power
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Pittendrigh, Adele; Borkowski, John; Swinford, Steven; Plumb, Carolyn – Journal of General Education, 2016
This study explores the effects of an academic seminar on the persistence of first-year college students, including effects on students most at risk of dropping out. A secondary interest was demonstrating the utility of using classification and regression tree analysis to identify relevant predictors of student persistence. The results of the…
Descriptors: First Year Seminars, Academic Persistence, At Risk Students, Classification
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Stuit, David; O'Cummings, Mindee; Norbury, Heather; Heppen, Jessica; Dhillon, Sonica; Lindsay, Jim; Zhu, Bo – Regional Educational Laboratory Midwest, 2016
In partnership with the Midwest Dropout Prevention Research Alliance the study team used student-level data and a five-step process to identify the most accurate indicators of students' failure to graduate from high school on time. Student-level data came from attendance records, transcripts, and discipline records of grade 8 and 9 students in…
Descriptors: High School Students, Academic Failure, Predictor Variables, Graduation
Chappell, Shanan L.; O'Connor, Patrick; Withington, Cairen; Stegelin, Dolores A. – National Dropout Prevention Center/Network, 2015
Almost from the start of the public schools system in America, students have been leaving school without high school diplomas. However, the dropout issue did not rise to the level of significance it has today until the early 1980s, when social pressures, along with business leaders, leveraged their influence on educators to address the dropout…
Descriptors: Public Schools, Dropout Prevention, At Risk Students, Business
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Weybright, Elizabeth H.; Caldwell, Linda L.; Xie, Hui; Wegner, Lisa; Smith, Edward A. – South African Journal of Education, 2017
Education is one of the strongest predictors of health worldwide. In South Africa, school dropout is a crisis where by Grade 12, only 52% of the age appropriate population remain enrolled. Survival analysis was used to identify the risk of dropping out of secondary school for male and female adolescents and examine the influence of substance use…
Descriptors: Foreign Countries, Predictor Variables, Predictive Measurement, Secondary School Students
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Elffers, Louise – European Journal of Psychology of Education, 2013
Behavioral disengagement from school is a proximal predictor of dropout. Therefore, the enhancement of behavioral engagement is a useful point of entry for dropout prevention. In this study, we examine the behavioral engagement of at-risk and non-at-risk students in Dutch senior vocational education (SVE), a sector confronted with high dropout…
Descriptors: Learner Engagement, Student School Relationship, Dropouts, Predictor Variables
Massachusetts Department of Elementary and Secondary Education, 2013
The Massachusetts Department of Elementary and Secondary Education (Department) created the grades 1-12 Early Warning Indicator System (EWIS) in response to district interest in the Early Warning Indicator Index (EWII) that the Department previously created for rising grade 9 students. Districts shared that the EWII data were helpful, but also…
Descriptors: Dropout Prevention, Risk, Models, Identification
Massachusetts Department of Elementary and Secondary Education, 2013
The Massachusetts Department of Elementary and Secondary Education (Department) created the grades 1-12 Early Warning Indicator System (EWIS) in response to district interest in the Early Warning Indicator Index (EWII) that the Department previously created for rising grade 9 students. Districts shared that the EWII data were helpful, but also…
Descriptors: Dropout Prevention, Risk, Models, Identification
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Elffers, Louise; Oort, Frans J.; Karsten, Sjoerd – Learning and Individual Differences, 2012
This study examines the emotional engagement with school of a diverse sample of 909 students in post-secondary vocational education in the Netherlands. Using multilevel regression analysis, we assess the role of students' background characteristics and school experiences, and their interaction, in students' emotional engagement with school.…
Descriptors: Foreign Countries, Dropout Prevention, At Risk Students, Vocational Education
Wilkinson, L. David; Frazer, Linda H. – 1990
In the 1988-89 school year, the Austin (Texas) Independent School District's Office of Research and Evaluation undertook a new dropout research project. Part of this initiative, termed Project GRAD, attempted to develop a statistical equation by which one could predict which students were likely to drop out. If reliable predictive information…
Descriptors: Discriminant Analysis, Dropout Prevention, Dropout Research, Ethnic Groups
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Carney, Michelle M.; Buttell, Frederick P. – Journal of Offender Rehabilitation, 2004
Objective: The purpose of this study was to: (a) investigate differences in demographic variables and psychological variables between treatment completers and dropouts among abusive women in a treatment program for domestic violence offenders; and, (b) create a predictive model that would correctly identify women at greatest risk of dropping out…
Descriptors: Family Violence, Females, Dropout Rate, Predictor Variables