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Sage, Andrew J.; Cervato, Cinzia; Genschel, Ulrike; Ogilvie, Craig A. – Journal of College Student Retention: Research, Theory & Practice, 2021
Students are most likely to leave science, technology, engineering, and mathematics (STEM) majors during their first year of college. We developed an analytic approach using random forests to identify at-risk students. This method is deployable midway through the first semester and accounts for academic preparation, early engagement in university…
Descriptors: Majors (Students), Identification, Student Satisfaction, At Risk Students
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Radunzel, Justine – Journal of College Student Retention: Research, Theory & Practice, 2021
First-generation (FG) students are generally less likely than their continuing-generation (CG) peers to persist and complete a degree. Using student data available at initial enrollment, this multi-institutional study examines retention and transfer at the second year in relation to academic readiness, financial resources, college intentions,…
Descriptors: School Holding Power, Academic Persistence, Student Attrition, Dropout Rate
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Barbera, Salvatore A.; Berkshire, Steven David; Boronat, Consuelo B.; Kennedy, Michael H. – Journal of College Student Retention: Research, Theory & Practice, 2020
A plethora of research spanning several decades has attempted to understand predictors of retention and graduation in undergraduate bachelor's degree programs. The topic is no less important today, as larger and larger swaths of the American population attend college each year. Studies have demonstrated that key demographic variables, indicators…
Descriptors: Undergraduate Students, Academic Persistence, Bachelors Degrees, Readiness
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Chen, Yu; Upah, Sylvester – Journal of College Student Retention: Research, Theory & Practice, 2020
Science, Technology, Engineering, and Mathematics student success is an important topic in higher education research. Recently, the use of data analytics in higher education administration has gain popularity. However, very few studies have examined how data analytics may influence Science, Technology, Engineering, and Mathematics student success.…
Descriptors: STEM Education, Academic Advising, Data Analysis, Majors (Students)
Sanchez, Jafeth E.; Lowman, Jennifer L.; Hill, Kathleen A. – Journal of College Student Retention: Research, Theory & Practice, 2018
Given the major investment in the Gaining Early Awareness and Readiness for Undergraduate Programs (GEAR UP) grant, rising postsecondary access, trends in poor persistence and retention rates, and the ongoing accountability measures in higher education, it is critical to examine factors related to postsecondary performance and persistence of GEAR…
Descriptors: Academic Achievement, Academic Persistence, School Holding Power, Undergraduate Study
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Grier-Reed, Tabitha; Chahla, Rose – Journal of College Student Retention: Research, Theory & Practice, 2015
Career planning courses are one of the most effective ways to improve career development, and the benefits to career decision-making are well documented. The research base regarding whether career courses contribute to academic outcomes is less well-developed. Although recent findings suggest that career courses may improve retention in the first-…
Descriptors: Academic Persistence, Career Development, Career Education, Constructivism (Learning)
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Perrine, Rose M.; Spain, Judith W. – Journal of College Student Retention: Research, Theory & Practice, 2009
The present research was a two-year longitudinal study on the effects of a six-day, optional, pre-semester, freshman orientation program on academic credits earned, GPA and college retention. Regression analyses were used to remove the variance associated with other possible predictors of academic success (gender, age, race, developmental need,…
Descriptors: Student Adjustment, College Freshmen, Grade Point Average, School Holding Power