Abstract
This chapter describes a study that evaluated the academic pathway of transfer students from two community colleges to a 4-year university. The project focused on a series of academic milestones that students must achieve prior to earning a 4-year credential. Those milestones include the first-term GPA, re-enrollment, and program completion. The purpose of this project was to develop an integrated database that contains key data on student demographics, course-taking behaviors, and performance from both the community college and the 4-year institution and to analyze the data using data mining and traditional statistical techniques to predict student success. A series of logistic regression equations identified significant predictors of first-term GPA, re-enrollment, and graduation. For example, overall rate of successful course completion, rate of successful math completion, rate of successful English completion, completion of developmental math were found to be significant predictors of a successful first-term GPA.
Original language | English (US) |
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Title of host publication | Big Data and Learning Analytics in Higher Education |
Subtitle of host publication | Current Theory and Practice |
Publisher | Springer International Publishing |
Pages | 221-236 |
Number of pages | 16 |
ISBN (Electronic) | 9783319065205 |
ISBN (Print) | 9783319065199 |
DOIs | |
State | Published - Jan 1 2016 |
All Science Journal Classification (ASJC) codes
- General Social Sciences