Heads Or Tails (Success Or Failure)? Using Logit Modeling To Predict Student Retention And Progression
Using a sample of 2,137 university students and applying the logit model, we find that the probability for students to return in fall 2008 is higher with a higher cumulative GPA, a higher grade for SE 101, and a returning status in the previous semester. Several other explanatory variables are test...
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| Veröffentlicht in: | Contemporary issues in education research (Littleton, Colo.) Colo.), 2010-05, Vol.3 (5), p.35 |
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| creator | Budden, Michael C. Hsing, Yu Budden, Connie B. Hall, Michelle |
| description | Using a sample of 2,137 university students and applying the logit model, we find that the probability for students to return in fall 2008 is higher with a higher cumulative GPA, a higher grade for SE 101, and a returning status in the previous semester. Several other explanatory variables are tested and have insignificant coefficients. A few variables such as the Board of Regent’s core requirements (CORE) and high school graduating GPA (HSGPA) have the expected signs and z-statistics closer to one, suggesting that the correlation coefficient may rise if the sample size were larger. The findings suggest that the cumulative GPA is a dominant factor and that the large number of failures in SE 101 may need to be examined in order to fulfill its described purpose: “a course designed to ensure first-year student success.” |
| doi_str_mv | 10.19030/cier.v3i5.204 |
| format | Article |
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| subjects | Academic achievement Academic Persistence Accountability College Freshmen College Students Correlation Correlation analysis Curriculum development Dependent variables Economic development Elementary school students Grade Point Average Grades (Scholastic) Graduation rate High School Graduates Higher education Learning Louisiana Outcomes of Education Predictions Probability Progress Regression (Statistics) School Holding Power Student retention Student writing Studies Success Tuition University students Variables |
| title | Heads Or Tails (Success Or Failure)? Using Logit Modeling To Predict Student Retention And Progression |
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