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Data Analytics and STEM Student Success: The Impact of Predictive Analytics-Informed Academic Advising among Undeclared First-Year Engineering Students
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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)
Background or Experience? Using Logistic Regression to Predict College Retention
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Synco, Tracee M. – ProQuest LLC, 2012
Tinto, Astin and countless others have researched the retention and attrition of students from college for more than thirty years. However, the six year graduation rate for all first-time full-time freshmen for the 2002 cohort was 57%. This study sought to determine the retention variables that predicted continued enrollment of entering freshmen…
Descriptors: College Entrance Examinations, School Holding Power, Grade Point Average, Supplementary Education
Predicting Community College Student Persistence.
Davidson, Sidney H., Jr. – 1974
The principal objective of this five-year longitudinal study was to determine the efficacy of employing the Omnibus Personality Inventory (OPI) and the American College Testing (ACT) program scores in designing a predictive model for identifying entering community college freshmen students' propensity to fall into one of three categories:…
Descriptors: Academic Achievement, Academic Persistence, Community Colleges, Doctoral Dissertations