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Yanagiura, Takeshi – Community College Research Center, Teachers College, Columbia University, 2020
Among community college leaders and others interested in reforms to improve student success, there is growing interest in adopting machine learning (ML) techniques to predict credential completion. However, ML algorithms are often complex and are not readily accessible to practitioners for whom a simpler set of near-term measures may serve as…
Descriptors: Community Colleges, Man Machine Systems, Artificial Intelligence, Prediction
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
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
Moosai, Susan; Walker, David A.; Floyd, Deborah L. – Community College Journal of Research and Practice, 2011
Prediction models using graduation rate as the performance indicator were obtained for community colleges in California, Florida, and Michigan. The results of this study indicated that institutional graduation rate could be predicted effectively from an aggregate of student and institutional characteristics. A performance measure was computed, the…
Descriptors: Community Colleges, Graduation Rate, Institutional Evaluation, Institutional Characteristics
Fagan, Joseph F.; Holland, Cynthia R. – Intelligence, 2009
A theoretically based, culture-fair test of new learning ability is predictive of academic achievement. A sample of 633 adults, 121 of minority status, drawn from urban private universities, colleges, and community colleges were given information as to the meanings of previously unknown words, sayings, similarities, and analogies. They were also…
Descriptors: Academic Achievement, Prediction, College Students, Urban Schools
Smith, Vernon C.; Lange, Adam; Huston, Daniel R. – Journal of Asynchronous Learning Networks, 2012
Community colleges continue to experience growth in online courses. This growth reflects the need to increase the numbers of students who complete certificates or degrees. Retaining online students, not to mention assuring their success, is a challenge that must be addressed through practical institutional responses. By leveraging existing student…
Descriptors: Academic Achievement, At Risk Students, Prediction, Community Colleges
Bailey, Brenda L. – New Directions for Institutional Research, 2006
Data mining of IPEDS data is used to develop models that calculate predicted graduation rates for two- and four-year institutions. (Contains 7 tables and 5 figures.)
Descriptors: Graduation Rate, Models, Data, Prediction

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