NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
Assessments and Surveys
Massachusetts Comprehensive…2
What Works Clearinghouse Rating
Showing 1 to 15 of 27 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Marshall, David T. – Preventing School Failure, 2022
Using administrative data from an urban school district, two series of predictive models were tested for their ability to project a student's high school graduation status. The models included student grades, attendance, behavior, demographic predictors, and school-level variables. Eighth and ninth-grade variables were tested for two graduation…
Descriptors: High School Students, Grades (Scholastic), Grade 8, Grade 9
Peer reviewed Peer reviewed
Direct linkDirect link
Hachey, Alyse C.; Conway, Katherine M.; Wladis, Claire; Karim, Shirsti – Journal of Computing in Higher Education, 2022
Even prior to the COVID-19 pandemic, online learning had become a fundamental part of post-secondary education. At the same time, empirical evidence from the last decade documents higher dropout online in comparison to face-to-face courses for some students. Thus, while online learning may provide students access to post-secondary education,…
Descriptors: Undergraduate Students, Student Characteristics, Demography, Online Courses
McCormic, Kathryn – ProQuest LLC, 2023
The purpose of this study was to examine the factors associated with academic achievement in at-risk high school students attending one of four charter schools in south Florida geared toward dropout prevention. Several factors were identified through a thorough review of the literature to identify the common demographic variables associated with…
Descriptors: At Risk Students, High School Students, Academic Achievement, Charter Schools
Peer reviewed Peer reviewed
Direct linkDirect link
Thao-Trang Huynh-Cam; Long-Sheng Chen; Tzu-Chuen Lu – Journal of Applied Research in Higher Education, 2025
Purpose: This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability. Design/methodology/approach: The real-world…
Descriptors: Foreign Countries, Undergraduate Students, At Risk Students, Dropout Characteristics
Peer reviewed Peer reviewed
Direct linkDirect link
Cannistrà, Marta; Masci, Chiara; Ieva, Francesca; Agasisti, Tommaso; Paganoni, Anna Maria – Studies in Higher Education, 2022
This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading…
Descriptors: Dropouts, Potential Dropouts, Dropout Prevention, Dropout Characteristics
Dina Perfetti-Deany – ProQuest LLC, 2021
Over the last 100 years, the overwhelming majority of Americans have attended this nation's public schools. There are clearly documented deleterious effects for students who do not successfully graduate from high school. Further, scholars and practitioners have recognized the adverse impacts on communities and the economy. Unfortunately, Colorado…
Descriptors: Graduation Rate, Public Schools, Middle School Students, At Risk Students
Slaughter, Austin; Neild, Ruth Curran; Crofton, Molly – Philadelphia Education Research Consortium, 2018
Ninth grade is a critical juncture for students--and can be a jarring transition. Even students a strong track record in the middle grades can experience academic difficulty, and those who enter high school with poor course grades, weak attendance, or behavior problems are especially at risk. An early misstep can have lasting implications:…
Descriptors: High School Students, Grade 9, At Risk Students, Potential Dropouts
Peer reviewed Peer reviewed
Direct linkDirect link
McKee, M. Todd; Caldarella, Paul – Education, 2016
Dropping out of high school has negative results and implications for individuals and society. The likelihood of dropping out is attributed to both social and academic risk factors. Poor high school attendance, low course completion, and low grade-point-average (GPA) have been identified as three leading indicators that students are at risk for…
Descriptors: Middle School Students, High School Students, Academic Achievement, Predictor Variables
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Carroll, Shannon Rae – ProQuest LLC, 2010
The high school dropout rate in a southern U.S. state is 22.1% and students who fall behind in reading and math in middle school are more likely to fail 9th grade. This specific failure is one of the strongest predictors that a student will ultimately drop out of school. The research questions of this study addressed the relationship between math…
Descriptors: Mathematics Achievement, Statistical Analysis, Grade 7, Mathematics Anxiety
Vogt, Dave – 1977
The objective of this study was to devise a methodology for predicting the return or nonreturn of a student for the spring semester, upon his completion of the fall term. Nineteen variables from existing student files were examined by several multivariate analyses to determine their ability to help in such a prediction. The random sample was of…
Descriptors: College Students, Dropout Characteristics, Dropout Prevention, Higher Education
MacMillan, Donald L. – 1991
This booklet addresses the difficulties of comparing and drawing meaning from dropout data prepared by different agencies, and examines the characteristics of students--and of schools--that place students at risk for leaving school prematurely. The booklet describes prevention programs and presents evidence on their effectiveness. It reviews…
Descriptors: Data Interpretation, Disabilities, Dropout Prevention, Dropout Rate
Previous Page | Next Page »
Pages: 1  |  2