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How Do Transfers Survive after “Transfer Shock”? A Longitudinal Study of Transfer Student Departure at a Four-Year Institution

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Abstract

Prompted by the notion of “Transfer Shock”, numerous studies examined academic performance of transfer students at senior institutions. However, few studies are found that examine how the varying nature of semester GPAs impact subsequent persistence behavior of transfer students after the initial drop in their college GPAs. Using an institutional data set, this study longitudinally investigated departure behavior of transfer students at a senior institution. Particular attention was given to how entry at different times and semester GPAs affected transfer student departure. Results indicate that during their first semester, sophomore and junior transfer students were 73% less likely to depart than freshman transfer students. After controlling for explanatory variables, higher semester GPAs were positively associated with higher persistence rates throughout the observation period.

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Notes

  1. Native students are referred to as those who initially began their postsecondary education at a four-year institution and continued their enrollment at the same institution.

  2. These tests are nonparametric rank tests to compare two or more distributions. The parameter of these tests was computed as a weighted standardized sum of the difference between the observed and expected number of departure in each of the four student types. The expected number of departure was estimated under the null hypothesis of no difference existing in the number of students who departed.

  3. Some may question how sophomore completed the program in a rather shorter period. Class classification was defined in a range of earned transferable credit hours. Thus, some of the sophomore transfer students matriculated with transfer credit hours that were a few credit hours short of being classified as a junior.

  4. This study offered to examine whether the effects of explanatory variables on persistence would vary over time. Thus, explanation on why these effects varying over time is beyond the scope of the present study.

References

  • Allison, P. D. (1984). Event history analysis: Regression for longitudinal event data. Newbury Park, CA: Sage.

    Google Scholar 

  • Avakian, A. N., MacKinney, A. C., & Allen, G. R. (1982). Race and sex differences in student retention at an urban university. College and University, 57(2), 160–165.

    Google Scholar 

  • Bean, J. P. (1980). Dropouts and turnover: The synthesis and test of a causal model of student attrition. Research in Higher Education, 12(2), 155–187.

    Article  Google Scholar 

  • Bean, J. P. (1983). The application of model of turnover in work organizations to the student attrition process. Review of Higher Education, 6(2), 129–148.

    Google Scholar 

  • Braxton, J. M., Duster, M., & Pascarella, E. T. (1988). Causal modeling and path analysis: An introduction and an illustration in student attrition research. Journal of College Student Development, 29(3), 263–272.

    Google Scholar 

  • Braxton, J. M., Milem, J. F., & Sullivan, A. S. (2000). The influence of active learning on the college student departure process: Toward a revision of Tinto’s theory. Journal of Higher Education, 71(5), 569–590.

    Article  Google Scholar 

  • Cabrera, A. F., Nora, A., & Castaneda, M. B. (1993). College persistence: Structural equations modeling test of an integrated model of student retention. Journal of Higher Education, 64(2), 123–139.

    Article  Google Scholar 

  • Caison, A. L. (2004). Determinants of systemic retention: Implications for improving retention practice in higher education. Journal of College Student Retention, 6(4), 425–441.

    Article  Google Scholar 

  • Conference Board. (2006). Are they really ready to work? Employers’ perspectives on the basic knowledge and applied skills of new entrants to the 21st century U.S. workforce, Retrieved October 10, 2006, from the Conference Board Web site: http://www.conference-board.org/pdf_free/BED-06-Workforce.pdf.

  • DesJardins, S. L. (2003). Event history methods: Conceptual issues and an application to student departure from college. In J. C. Smart (Ed.), Higher education: Handbook of theory and research (Vol. 18, pp. 421–471). New York, NY: Springer.

    Google Scholar 

  • DesJardins, S. L., Ahlburg, A. A., & McCall, B. P. (1999). An event history model of student departure. Economics of Education Review, 18(3), 375–390.

    Article  Google Scholar 

  • DesJardins, S. L., Ahlburg, D.A., & McCall, B.P. (2006). The effects of interrupted enrollment on graduation from college: Racial, income, and ability differences. Economics of Education Review, 25(6), 575–590.

    Article  Google Scholar 

  • Diaz, P. E. (1992). Effects of transfer on academic performance of community college students at the four-year institution. Community/Junior College Quarterly, 16(3), 279–291.

    Google Scholar 

  • Gao, H., Hughes, W. W., O’Rear, M. R., & Fendley, W. R. (2002, June). Developing structural equation models to determine factors contributing to student graduation and retention: Are there differences for native students and transfers? Paper Presented at the Annual Forum of the Association for Institutional Research, Toronto, ON, Canada.

  • Hill, J. R. (1965). Transfer shock: The academic performance of the junior college transfer. Journal of Experimental Education, 33(3), 201–215.

    Google Scholar 

  • Ishitani, T. T. (2003). A longitudinal approach to assessing attrition behavior among first-generation students: Time-varying effects of pre-college characteristics. Research in Higher Education, 44(4), 433–449.

    Article  Google Scholar 

  • Ishitani, T. T. (2006). Studying attrition and degree completion behavior among first-generation college students in the United States. Journal of Higher Education, 77(5), 861–885.

    Article  Google Scholar 

  • Ishitani, T. T., & DesJardins, S. L. (2002). A longitudinal investigation of dropout from colleges in the United States. Journal of College Student Retention, 4(2), 173–201.

    Article  Google Scholar 

  • Johnson, I. Y. (2006). Analysis of stopout behavior at a public research university: The multi-spell discrete-time approach. Research in Higher Education, 47(8), 905–934.

    Article  Google Scholar 

  • Liu, R., & Liu, E. (2000, May). Institutional integration: An analysis of Tinto’s theory. Paper Presented at the Annual Forum of the Association for Institutional Research, Cincinnati, OH.

  • McCormick, A. C. (1997). Transfer behavior among beginning postsecondary students: 1989–94. (NCES 97–266). U.S. Department of Education, NCES. Washington, DC.

  • McLendon, M. K., Hearn, J. C., & Deaton, R. (2006). Called to account: Analyzing the origins and spread of state. Educational Evaluation and Policy Analysis, 28(1), 1–24.

    Google Scholar 

  • Menard, S. (1995). Applied logistic regression analysis. Thousand Oaks, CA: Sage.

    Google Scholar 

  • Murtaugh, P. A., Burns, L. D., & Schuster, J. (1999). Predicting the retention of university students. Research in Higher Education, 40(3), 355–371.

    Article  Google Scholar 

  • National Center for Education Statistics. (1996). Descriptive summary of 1989–90 beginning postsecondary students: Five years later (NCES 96–155). Washington, DC: U.S. Department of Education, NCES.

  • National Center for Education Statistics. (2003). The condition of education: Transfers from community colleges to 4-year institutions. (NCES 2003–067). Washington, DC: U.S. Department of Education, NCES.

  • Nora, A., Attinasi, L.C., & Matonak, A. (1990). Testing qualitative indicators of pre-college factors in Tinto’s attrition model: A community college student population. Review of Higher Education, 13(3), 337–355.

    Google Scholar 

  • Pascarella, E. T. (1997). It’s time we started paying attention to community college students. About Campus, 1(6), 14–17.

    Google Scholar 

  • Pascarella, E. T., & Chapman, D. (1983). A multi-institutional path analytical validation of Tinto’s model of college withdrawal. American Educational Research Journal, 20(1), 87–102.

    Google Scholar 

  • Pascarella, E. T., Duby, P., & Iverson, B. (1983). A test and reconceptualization of a theoretical model of college withdrawal in a commuter institution setting. Sociology of Education, 56(2), 88–100.

    Article  Google Scholar 

  • Pascarella, E. T., & Terenzini, P. (1983). Path analytic validation of Tinto’s model. Journal of Educational Psychology, 75(2), 215–226.

    Article  Google Scholar 

  • Peng, S. S., & Bailey, J. P. (1977). Differences between vertical transfer and native students in four-year institutions. Research in Higher Education, 7(2), 145–154.

    Article  Google Scholar 

  • Porter, S. R. (1999, May). Assessing transfer and native student performance at four-year institutions. Paper Presented at the 43rd Annual Forum of the Association for Institutional Research, Seattle, WA.

  • Schartman, L., & Rhee, B. (2000, May). Linking student retention model with institutional planning: The benefits and limitations of a student matrix model. Paper Presented at the Annual Forum of the Association for Institutional Research, Cincinnati, OH.

  • Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of recent research. Review of Educational Research, 45(1), 89–125.

    Google Scholar 

  • Yamaguchi, K. (1991). Event history analysis. Applied social research methods series, Vol. 28. Newbury Park, CA: Sage.

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  1. Department of Counseling, Educational Psychology and Research, The University of Memphis, Memphis, TN, 38152-3570, USA

    Terry T. Ishitani

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  1. Terry T. Ishitani
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Correspondence to Terry T. Ishitani.

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Ishitani, T.T. How Do Transfers Survive after “Transfer Shock”? A Longitudinal Study of Transfer Student Departure at a Four-Year Institution. Res High Educ 49, 403–419 (2008). https://doi.org/10.1007/s11162-008-9091-x

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