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Ormiston, Heather E.; Renshaw, Tyler L. – School Mental Health, 2023
Universal screening for social, emotional, and behavioral risk is an important method for identifying students in need of additional or targeted support (Eklund and Dowdy in School Mental Health 6:40-49, 2014). Research is needed to explore how potential bias may be implicated in universal screening. We investigated student demographics as…
Descriptors: Student Characteristics, Predictor Variables, At Risk Students, Student Placement
Andrea M. Connolly – ProQuest LLC, 2022
Given the rapid growth of K-12 online learning, research is needed in the effective identification of at-risk students so that administrators and teachers can develop appropriate supports and interventions. The purpose of this research was to determine if student success in an online course could be predicted for English Learners (EL) using…
Descriptors: Prediction, Academic Achievement, Virtual Schools, Elementary Secondary Education
Kelly Anne Young – Open Learning, 2024
This paper sought to examine psychological grit, defined as passion and perseverance for long-term goals, and its efficacy in determining postgraduate retention among historically disadvantaged students enrolled at the University of South Africa (UNISA). The Grit-S scale was used to gauge the level of grit among the participants (n = 594) followed…
Descriptors: Foreign Countries, Academic Persistence, Resilience (Psychology), Student Characteristics
Madhumita Banerjee; Han Zhang – Journal of Educators Online, 2024
This study uses a logistic regression model to analyze survey data (n = 341) and predict factors influencing online course success for underserved and academically at-risk undergraduate students at a small, broad access, four-year, public Midwestern university. Three blocks of predictor variables, demographic (first generation, low income,…
Descriptors: Student Characteristics, Online Courses, Academic Achievement, Minority Group Students
Erin M. Picou; Hilary Davis; Leigh Anne Tang; Lisa Bastarache; Anne Marie Tharpe – Journal of Speech, Language, and Hearing Research, 2025
Purpose: School-age children with unilateral hearing loss are at an increased risk of exhibiting academic difficulties. Yet, approximately half of children with unilateral hearing loss will not require additional support. There is a dearth of information to assist in determining which of these children will express academic deficits and which will…
Descriptors: Hard of Hearing, At Risk Students, Low Achievement, Students with Disabilities
Faust, Luke E.; Rosendale, Joseph A. – Review of Education, 2023
This mixed methods study examined the impact of grit and self-efficacy and the factors of these constructs on the performance of at-risk, developmental placement students, surveying 184 first-year students before the midterm point of their first semester. Following the quantitative portion, six upperclassmen, who had started their careers in the…
Descriptors: Persistence, Resilience (Psychology), Self Efficacy, At Risk Students
Nalbone, David P.; Ashoori, Minoo; Fasanya, Bankole K.; Pelter, Michael W.; Rengstorf, Adam – International Journal for the Scholarship of Teaching and Learning, 2023
Much discussion in higher education has focused upon predicting student learning, and how to identify students who may be at particular risk of failure. Little research has actually tackled that challenge, and research on the scholarship of teaching and learning (SoTL) in this areas is scarce; this study does so by measuring students across three…
Descriptors: College Students, Predictor Variables, Academic Achievement, Identification
Pei, Bo; Xing, Wanli – Journal of Educational Computing Research, 2022
This paper introduces a novel approach to identify at-risk students with a focus on output interpretability through analyzing learning activities at a finer granularity on a weekly basis. Specifically, this approach converts the predicted output from the former weeks into meaningful probabilities to infer the predictions in the current week for…
Descriptors: At Risk Students, Learning Analytics, Information Retrieval, Models
Willis, William K.; Williamson, Vickie M.; Chuu, Eric; Dabney, Alan R. – Journal of Science Education and Technology, 2022
In an effort to investigate the factors that lead to success in general chemistry, the Math-Up Skills Test (MUST) and common questions were used along with a student characteristic questionnaire. The MUST is a 20-item instrument to measure mathematics fluency, which is done without a calculator with a 15-min time limit. It has been shown as a…
Descriptors: Chemistry, Mathematics Skills, Student Characteristics, Predictor Variables
Haskett, Mary E.; Kotter-Grühn, Dana; Majumder, Suman – Journal of College Student Development, 2020
There has been more attention to insecurity among college students for basic needs (e.g., Miles, McBeath, Brockett, & Sorenson, 2017; Morris, Smith, Davis, & Null, 2016); however, published research on student food insecurity and housing insecurity remains sparse. It is critical to understand the prevalence of these challenges because they…
Descriptors: College Students, Hunger, Food, Housing
Daniel Z. Merian – ProQuest LLC, 2021
In the 21st century, more students enroll in higher education and take federal loans to defer the cost of attendance resulting in average levels of borrowing steadily increasing. In the same timeframe, there is an increase in the number of students entering repayment for their federal loans and an increase in the proportion of individuals…
Descriptors: Predictor Variables, Student Financial Aid, Loan Default, Commuter Colleges
Marisa de la Torre; Elaine Allensworth; Kaitlyn Franklin – Society for Research on Educational Effectiveness, 2024
Background/Context: English learners (ELs) have the potential to bring much-needed multilingual skills to the workforce, and most ELs aspire to graduate high school and earn a post-secondary credential (Gwynne, Pareja, Ehrlich, & Allensworth, 2012; Shi & Watkinson, 2019). But active ELs graduate high school at far lower rates than their…
Descriptors: English Language Learners, High School Students, At Risk Students, Student Characteristics
Varga, Erika B.; Sátán, Ádám – Hungarian Educational Research Journal, 2021
The purpose of this paper is to investigate the pre-enrollment attributes of first-year students at Computer Science BSc programs of the University of Miskolc, Hungary in order to find those that mostly contribute to failure on the Programming Basics first-semester course and, consequently to dropout. Our aim is to detect at-risk students early,…
Descriptors: Identification, At Risk Students, Computer Science Education, Undergraduate Students
Nathan A. Hawk; Kui Xie; Azita Manouchehri – Journal of Urban Mathematics Education, 2025
In online virtual-based learning, combining more adaptive personal student characteristics with risk factors, the purpose of this study was to examine the relationship between student at-risk factors and mathematics achievement. Further, the study examined how personal student characteristics, which are sometimes amenable to change and…
Descriptors: Student Characteristics, Mathematics Achievement, Nontraditional Students, High School Students
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