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Jeremiah T. Stark – ProQuest LLC, 2024
This study highlights the role and importance of advanced, machine learning-driven predictive models in enhancing the accuracy and timeliness of identifying students at-risk of negative academic outcomes in data-driven Early Warning Systems (EWS). K-12 school districts have, at best, 13 years to prepare students for adulthood and success. They…
Descriptors: High School Students, Graduation Rate, Predictor Variables, Predictive Validity
Yanagiura, Takeshi – Community College Review, 2023
Objective: This study examines how accurately a small set of short-term academic indicators can approximate long-term outcomes of community college students so that decision-makers can take informed actions based on those indicators to evaluate the current progress of large-scale reform efforts on long-term outcomes, which in practice will not be…
Descriptors: Community Colleges, Community College Students, Educational Indicators, Outcomes of Education
Qin, Lu; Phillips, Glenn Allen – International Journal of Higher Education, 2019
The 3-year graduation rate is a rarely measured metric in higher education compared to its 4- or 6- year graduation rate counterparts. For the first time in college (FTIC) students to graduate in three years, they must come with certain skills, abilities, plans, supports, or motivations. This project considers two distinct but interrelated ways of…
Descriptors: Graduation Rate, Time to Degree, College Credits, Grade Point Average
Hutt, Stephen; Gardner, Margo; Duckworth, Angela L.; D'Mello, Sidney K. – International Educational Data Mining Society, 2019
We explore generalizability and fairness across sociodemographic groups for predicting on-time college graduation using a national dataset of 41,359 college applications. Our features include sociodemographics, institutional graduation rates, academic achievement, standardized test scores, engagement in extracurricular activities, and work…
Descriptors: Generalization, Predictive Measurement, College Applicants, Time to Degree
Grogan, Rita D. – ProQuest LLC, 2017
Purpose: The purpose of this case study was to determine the impact of utilizing predictive modeling to improve successful course completion rates for at-risk students at California community colleges. A secondary purpose of the study was to identify factors of predictive modeling that have the most importance for improving successful course…
Descriptors: Community Colleges, Case Studies, Models, Academic Persistence
Horn, Aaron S.; Lee, Giljae – Research in Higher Education, 2016
A relatively simple way of measuring institutional effectiveness in relation to degree completion is to estimate the difference between an actual and predicted graduation rate, but the reliability and validity of this method have not been thoroughly examined. Longitudinal data were obtained from IPEDS for both public and private not-for-profit…
Descriptors: Regression (Statistics), Test Reliability, Test Validity, Graduation Rate
Huang, Liuli; Roche, Lahna R.; Kennedy, Eugene; Brocato, Melissa B. – International Journal of Higher Education, 2017
Many researchers have explored the relationships between the likelihood of graduating from college and demographic and pre-college factors such as gender, race/ethnicity, high school grade point average (GPA), and standardized test scores. However, additional factors such as a student's college major, home address, or use of learning support in…
Descriptors: Graduation Rate, Predictor Variables, Predictive Measurement, Predictive Validity
National Centre for Vocational Education Research (NCVER), 2016
This work asks one simple question: "how reliable is the method used by the National Centre for Vocational Education Research (NCVER) to estimate projected rates of VET program completion?" In other words, how well do early projections align with actual completion rates some years later? Completion rates are simple to calculate with a…
Descriptors: Vocational Education, Graduation Rate, Predictive Measurement, Predictive Validity
Mertes, Scott J.; Hoover, Richard E. – Community College Journal of Research and Practice, 2014
Retention is a complex issue of great importance to community colleges. Several retention models have been developed to help explain this phenomenon. However, these models typically have used four-year college and university environments to build their foundations. Several researchers have attempted to identify predictor variables using…
Descriptors: Community Colleges, Predictor Variables, College Freshmen, Academic Persistence
Eickhoff, Mary Ann – ProQuest LLC, 2016
There is currently a nursing shortage in the United States. By 2022, the Bureau of Labor Statistics (BLS) expects, the number of job openings for Practical Nurses (PN) will be 168,500, an increase of 25% over 2012 (BLS, 2014). Nursing education does not currently meet present, much less future needs. Nursing programs have limited space; according…
Descriptors: Nursing Students, Predictor Variables, Success, Licensing Examinations (Professions)
Predicting Higher Education Outcomes and Implications for a Postsecondary Institution Ratings System
Walker, Eddie G., II – Journal of Higher Education Policy and Management, 2016
The accountability of colleges and universities is a high priority for those making policy decisions. The purpose of this study was to determine institutional characteristics predicting retention rates, graduation rates and transfer-out rates using publicly available data from the US Department of Education. Using regression analysis, it was…
Descriptors: Higher Education, Predictive Measurement, Predictive Validity, Prediction
Wladis, Claire; Conway, Katherine M.; Hachey, Alyse C. – Online Learning, 2016
This study explored the interaction between student characteristics and the online environment in predicting course performance and subsequent college persistence among students in a large urban U.S. university system. Multilevel modeling, propensity score matching, and the KHB decomposition method were used. The most consistent pattern observed…
Descriptors: Online Courses, Electronic Learning, Learning Readiness, Student Characteristics
Herrera, Cheryl; Blair, Jennifer – Research in Higher Education Journal, 2015
As the U.S. population ages and policy changes emerge, such as the Patient Protection and Affordable Care Act of 2010, the U.S. will experience a significant shortage of Registered Nurses (RNs). Many colleges and universities are attempting to increase the size of nursing cohorts to respond to this imminent shortage. Notwithstanding a 2.6%…
Descriptors: Prediction, Success, Nursing Education, Nursing Students
Lin, Jien-Jou – ProQuest LLC, 2013
Every year a group of graduates from high schools enter the engineering programs across this country with remarkable academic record. However, as reported in numerous studies, the number of students switching out of engineering majors continues to be an important issue. Previous studies have suggested various factors as predictors for student…
Descriptors: Success, Prediction, Predictive Measurement, Predictive Validity
Kotamraju, Pradeep; Blackman, Orville – Community College Journal of Research and Practice, 2011
The paper uses the Integrated Postsecondary Education Data system (IPEDS) data to simulate the 2020 American Graduation Initiative (AGI) goal introduced by President Obama in the summer of 2009. We estimate community college graduation rates and completion numbers under different scenarios that include the following sets of variables: (a) internal…
Descriptors: Community Colleges, Graduation Rate, Educational Attainment, Predictor Variables
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