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Davis, Elisabeth; Stephan, Jennifer L.; Lindsay, Jim; Park, So Jung – Regional Educational Laboratory Midwest, 2016
This study examined the early college success of students who graduated from an Indiana high school in 2010 and enrolled immediately in a public two-year or four-year college in Indiana. The study team identified data elements in Indiana's Student Information System that predicted the early college success of this cohort of students. Half of…
Descriptors: High School Students, Public Colleges, Predictor Variables, Academic Achievement
Zacharakis, Jeff; Wang, Haiyan; Patterson, Margaret Becker; Andersen, Lori – Journal of Research and Practice for Adult Literacy, Secondary, and Basic Education, 2015
This research analyzed linked high-quality state data from K-12, adult education, and postsecondary state datasets in order to better understand the association between student demographics and successful completion of a postsecondary program. Due to the relatively small sample size compared to the large number of features, we analyzed the data…
Descriptors: Adult Basic Education, High School Equivalency Programs, Elementary Secondary Education, Postsecondary Education
Stephan, Jennifer L.; Davis, Elisabeth; Lindsay, Jim; Miller, Shazia – Regional Educational Laboratory Midwest, 2015
This study examined whether data on Indiana high school students, their high schools, and the Indiana public colleges and universities in which they enroll predict their academic success during the first two years in college. The researchers obtained student-level, school-level, and university-related data from Indiana's state longitudinal data…
Descriptors: High School Students, Public Colleges, Predictor Variables, Academic Achievement
Curtin, Jenny; Hurwitch, Bill; Olson, Tom – National Center for Education Statistics, 2012
An early warning system is a data-based tool that helps predict which students are on the right path towards eventual graduation or other grade-appropriate goals. Through such systems, stakeholders at the school and district levels can view data from a wide range of perspectives and gain a deeper understanding of student data. This "Statewide…
Descriptors: Databases, Educational Indicators, Predictor Variables, At Risk Students
Parrott-Robbins, Rebecca Jon – ProQuest LLC, 2010
The purpose of this study was to investigate--by utilizing data obtained from the Kentucky Community and Technical College System (KCTCS) PeopleSoft database-- whether the American College Testing (ACT) assessment was a predictor of student success for students who had graduated from respiratory, radiography, and nursing programs at Southeast…
Descriptors: Nursing Education, Technical Institutes, Grade Point Average, Multiple Regression Analysis
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