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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
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Bingham, Melissa A.; Solverson, Natalie Walleser – Journal of Student Affairs Research and Practice, 2016
First- to second-year retention rates are one metric reported by colleges and universities to convey institutional success to a variety of external constituents. But how much of a retention rate is institutional inputs, and how much can be understood by examining student inputs? The authors utilize multi-year, multi-institutional data to examine…
Descriptors: Public Colleges, Universities, College Students, School Holding Power
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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
Brown, Narren J. – ProQuest LLC, 2013
Combining institutional data and measures with predictive analyses is a viable means by which to determine where and how to allocate all too limited institutional resources and programming. There are not many among us who would argue against the richness of data and depth of understanding of a phenomenon that are gained through focus groups and…
Descriptors: Prediction, Resource Allocation, Educational Change, Research Methodology
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Hillman, Nicholas W. – Educational Policy, 2015
This study examines the institutional factors associated with student loan default. When a college has more than 30% of its students default on their loans, then the institution faces federal sanctions that could make them ineligible from participating in the federal student loan program. Using Integrated Postsecondary Education Data System…
Descriptors: Cohort Analysis, Probability, Prediction, Federal Regulation