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Aom Perkash; Qaisar Shaheen; Robina Saleem; Furqan Rustam; Monica Gracia Villar; Eduardo Silva Alvarado; Isabel de la Torre Diez; Imran Ashraf – Education and Information Technologies, 2024
Developing tools to support students, educators, intuitions, and government in the educational environment has become an important task to improve the quality of education and learning outcomes. Information and communication technology (ICT) is adopted by educational institutions; one such instance is video interaction in flipped teaching.…
Descriptors: Academic Achievement, Colleges, Artificial Intelligence, Predictor Variables
Sahar Voghoei – ProQuest LLC, 2021
The importance of retention rate for higher education institutions has encouraged data analysts to present various methods to predict at-risk students. Their objective is to provide timely information that may enable educators to channel the most effective remedial treatments towards precisely targeted students in an efficient manner. The present…
Descriptors: Data Science, Academic Achievement, School Holding Power, Predictor Variables
Hoffman, Nancy; O'Connor, Anna; Mawhinney, Joanna – Jobs for the Future, 2022
The purpose of this brief is to provide school-level examples of how early college practitioners are collecting and using data to improve their practices. Examples three and four are school-level data from two early college partnerships: the MetroWest CPC (Framingham, Milford, Waltham), and Lawrence. The brief begins, however, with the national…
Descriptors: College School Cooperation, Partnerships in Education, High Schools, Universities
Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – Annenberg Institute for School Reform at Brown University, 2021
Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…
Descriptors: At Risk Students, Higher Education, Predictive Measurement, Models
How Calculus Eligibility and At-Risk Status Relate to Graduation Rate in Engineering Degree Programs
Bowen, Bradley D.; Wilkins, Jesse L. M.; Ernst, Jeremy V. – Journal of STEM Education: Innovations and Research, 2019
The problematic persistence rates that many colleges and schools of engineering encounter has resulted in ongoing conversations about academic readiness, retention, and degree completion within engineering programs. Although a large research base exists about student preparedness in engineering, many studies report a wide variety of factors that…
Descriptors: At Risk Students, Engineering Education, Graduation Rate, College Students
Aulck, Lovenoor; Nambi, Dev; Velagapudi, Nishant; Blumenstock, Joshua; West, Jevin – International Educational Data Mining Society, 2019
Each year, roughly 30% of first-year students at US baccalaureate institutions do not return for their second year and billions of dollars are spent educating these students. Yet, little quantitative research has analyzed the causes and possible remedies for student attrition. What's more, most of the previous attempts to model attrition at…
Descriptors: Student Records, Registrars (School), Predictor Variables, Undergraduate Students
Papay, Clare; Grigal, Meg; Hart, Debra; Kwan, Ngai; Smith, Frank A. – Intellectual and Developmental Disabilities, 2018
Higher education programs for students with intellectual and developmental disabilities (IDD) offer opportunities to engage in college experiences including access to typical college courses. The purpose of the present study was to examine data from federally funded programs in order to describe and identify predictors of inclusive course…
Descriptors: Enrollment, College Freshmen, Intellectual Disability, Inclusion
Gill, Tim – Cambridge University Press & Assessment, 2022
The Extended Project Qualification (EPQ) is available for students in Key Stage 5 (KS5), to be taken alongside other qualifications, such as A levels. It differs from most other academic qualifications at KS5 because it is not examined, but instead involves students undertaking an in-depth project in an area of their choosing. Students are…
Descriptors: Foreign Countries, Secondary School Students, Exit Examinations, Independent Study
Barra, Cristian; Zotti, Roberto – Tertiary Education and Management, 2017
The main purpose of the paper is to estimate the efficiency of a big public university in Italy using individual student-level data, modeling exogenous variables in human capital formation through a heteroscedastic stochastic frontier approach. Specifically, a production function for tertiary education has been estimated with emphasis on…
Descriptors: Efficiency, School Statistics, Student Records, Information Utilization
Cohen, Richard; Kelly, Angela M. – Review of Higher Education, 2019
This study explored science, mathematics, and general academic factors that predicted outcomes for community college students (N = 3052) in a regional institution. A binary logistic regression was performed to determine significant independent variables contributing to successful outcomes (graduation or transfer) vs. non-completion. Transcript…
Descriptors: Community Colleges, Mathematics Instruction, Remedial Instruction, Prediction
Murtagh, S.; Ridley, A.; Frings, D.; Kerr-Pertic, S. – Journal of Further and Higher Education, 2017
The first year of study in higher education is a time of major transition for students. While the importance of induction has been widely demonstrated, there is evidence to suggest that not all students benefit equally from participation in induction. This study examined attendance rates at induction, the relationship between induction attendance…
Descriptors: Undergraduate Students, College Freshmen, School Orientation, Attendance Patterns
Johnson, Iryna – College Student Journal, 2017
Based on data from a single institution, this study estimates the effect of having a female instructor, the effects of measures of self-efficacy, and the interaction effects of measures of self-efficacy and having a female instructor on female and male student grade performance. Self-efficacy for academic achievement, self-regulated learning,…
Descriptors: Self Efficacy, Role Models, Females, Academic Achievement
Mengo, Cecilia; Black, Beverly M. – Journal of College Student Retention: Research, Theory & Practice, 2016
Violence against university students has significant impact on their mental health. The impact of violence on students' academic performance has received little attention. The primary purpose of this study is to examine the impact of sexual and physical/verbal violence on the academic performance of college students. Data from 74 case files of…
Descriptors: Violence, Victims, Grade Point Average, Dropouts
Wiggins, Afi Y. – Online Submission, 2015
This supplemental report provides technical documentation for the main report (published separately). A significantly higher percentage of AISD graduates enrolled in postsecondary institutions in 2014 (66%) than enrolled in 2013 (63%). Eighty-one percent of Class of 2013 graduates enrolled and persisted in a postsecondary institution 2 consecutive…
Descriptors: College Enrollment, High School Graduates, School Districts, Academic Persistence
Lee, Katelyn; Therriault, Susan – College and Career Readiness and Success Center, 2016
This brief examines strategies for leveraging State longitudinal data systems (SLDS) to promote college and career readiness (CCR) goals. The examples provided are based on current state efforts to use their state longitudinal data systems to achieve their CCR vision and goals. The following information outlines the basic purpose and elements of…
Descriptors: Longitudinal Studies, Career Readiness, College Readiness, Elementary Secondary Education