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Riley N. Loria; Edgar I. Sanchez – ACT Education Corp., 2024
Effectively predicting academic success is essential for providing students with the resources they need to succeed in their careers and for matching individuals to postsecondary institutions that suit their needs. Despite evidence for ACT scores as meaningful predictors of both first-year grade point average (FYGPA) and degree completion, little…
Descriptors: College Entrance Examinations, Predictive Validity, Time to Degree, Models
Anika Alam; A. Brooks Bowden – Society for Research on Educational Effectiveness, 2024
Background: The importance of high school completion for jobs and postsecondary opportunities is well- documented. Combined with federal laws where high school graduation rate is a core performance indicator, school systems and states face pressure to actively monitor and assess high school completion. This proposal employs machine learning…
Descriptors: Dropout Characteristics, Prediction, Artificial Intelligence, At Risk Students
Amanda M. Dettmer – Online Submission, 2023
Emotional, behavioral, and mental health challenges make it difficult for many children and adolescents to engage and succeed at school. Research indicates that at least 20% of all children and adolescents have been diagnosed with one more mental health disorders. Behavioral problems, anxiety, and depression are the most diagnosed mental health…
Descriptors: Mental Health, Mental Disorders, Clinical Diagnosis, Academic Achievement
Krause, Elizabeth D.; Vélez, Clorinda E.; Woo, Rebecca; Hoffmann, Brittany; Freres, Derek R.; Abenavoli, Rachel M.; Gillham, Jane E. – Journal of Early Adolescence, 2018
Recent research suggests that rumination may represent both a risk factor for and consequence of depression, especially among female samples. Nevertheless, few longitudinal studies have examined a reciprocal model of rumination and depression in early adolescence, just before rates of depression diverge by gender. The present study evaluated a…
Descriptors: Depression (Psychology), Longitudinal Studies, Gender Differences, Symptoms (Individual Disorders)
Reinke, Wendy M.; Herman, Keith C.; Thompson, Aaron; Copeland, Christa; McCall, Chynna S.; Holmes, Shannon; Owens, Sarah A. – Grantee Submission, 2021
Many youth experience mental health problems. Schools are an ideal setting to identify, prevent, and intervene in these problems. The purpose of this study was to investigate patterns of student social, emotional, and behavioral risk over time among a community sample of 3rd through 12th grade students and the association of these risk patterns…
Descriptors: Mental Disorders, Models, Mental Health, Prevention
Eugene, Danielle R. – Journal of Education for Students Placed at Risk, 2020
This multilevel study examined the effects of socioeconomic status (SES) and student perceptions of school climate on academic achievement at the student and school levels. Data used were from the Education Longitudinal Study of 2002. The sample included 9,518 students enrolled in 584 public high schools. The results revealed that student-level…
Descriptors: Models, Educational Environment, Socioeconomic Status, Student Attitudes
Hung, Jui-Long; Shelton, Brett E.; Yang, Juan; Du, Xu – IEEE Transactions on Learning Technologies, 2019
Performance prediction is a leading topic in learning analytics research due to its potential to impact all tiers of education. This study proposes a novel predictive modeling method to address the research gaps in existing performance prediction research. The gaps addressed include: the lack of existing research focus on performance prediction…
Descriptors: Prediction, Models, At Risk Students, Identification
Reinke, Wendy M.; Herman, Keith C.; Thompson, Aaron; Copeland, Christa; McCall, Chynna S.; Holmes, Shannon; Owens, Sarah A. – School Psychology Review, 2020
Many youth experience mental health problems. Schools are an ideal setting to identify, prevent, and intervene in these problems. The purpose of this study was to investigate patterns of student social, emotional, and behavioral risk over time among a community sample of 3rd through 12th grade students and the association of these risk patterns…
Descriptors: Mental Disorders, Models, Mental Health, Prevention
Ghasemi, Abolfazl – ProQuest LLC, 2018
The purpose of this study was to build a forecasting model for medical students at risk using the survival analysis technique. Authors of previous studies have investigated dropouts from medical programs or success of medical students on national board exams. However, little research has been done to identify students at risk, mainly the timing of…
Descriptors: Medical Students, Medical Education, At Risk Students, Gender Differences
Gray, Geraldine; McGuinness, Colm; Owende, Philip; Hofmann, Markus – Journal of Learning Analytics, 2016
This paper reports on a study to predict students at risk of failing based on data available prior to commencement of first year. The study was conducted over three years, 2010 to 2012, on a student population from a range of academic disciplines, n=1,207. Data was gathered from both student enrollment data and an online, self-reporting,…
Descriptors: Prediction, At Risk Students, Academic Failure, College Freshmen
Noffsinger, Sandra; Clements-Nolle, Kristen; Bacon, Robinette; Lee, William; Albers, Eric; Yang, Wei – Journal of Child & Adolescent Substance Abuse, 2012
While previous studies have investigated the relationship between substance use and violent behaviors among youths, the individual influence of specific drugs among males and females is poorly understood. Using the Nevada 2005 Youth Risk Behavior Surveillance (YRBS) Survey (N = 1,556), weighted logistic regression was used to assess the…
Descriptors: Narcotics, At Risk Students, Drinking, Adolescents
Yasmin, Dr. – Distance Education, 2013
This paper demonstrates the meaningful application of learning analytics for determining dropout predictors in the context of open and distance learning in a large developing country. The study was conducted at the Directorate of Distance Education at the University of North Bengal, West Bengal, India. This study employed a quantitative research…
Descriptors: Distance Education, Open Universities, Predictor Variables, Student Behavior
Tapper, Donna; Zhu, Jing; Scuello, Michael – Online Submission, 2015
(Purpose) This study contributes to the knowledge base about strategies for helping disconnected youth re-engage with schooling. The study presents findings of a rigorous impact evaluation of the Good Shepherd Services (GSS) Transfer School Model that is grounded in developmental theory positing that social and emotional factors are essential to…
Descriptors: High School Students, Social Influences, Emotional Response, Student School Relationship
Chen, Ji-Kang; Astor, Ron Avi – Health Education Research, 2011
School violence has become an international problem affecting the well-being of students. To date, few studies have examined how school variables mediate between personal and family factors and school violence in the context of elementary schools in Asian cultures. Using a nationally representative sample of 3122 elementary school students in…
Descriptors: Elementary School Students, Elementary Schools, Violence, Structural Equation Models
Wanzek, Jeanne; Vaughn, Sharon – Remedial and Special Education, 2011
Patterns of identification for special education services across three cohorts of students in kindergarten through third grade before and after implementation of a schoolwide, three-tier reading prevention model in one large school district are reported. The first cohort of students represents a historical control group that did not participate in…
Descriptors: Disabilities, Special Education, Student Placement, At Risk Students
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