Research in Higher Education

, Volume 49, Issue 7, pp 647–664 | Cite as

Third-year College Retention and Transfer: Effects of Academic Performance, Motivation, and Social Connectedness

  • Jeff Allen
  • Steven B. Robbins
  • Alex Casillas
  • In-Sue Oh
Article

Abstract

We studied the effects of academic performance, motivation, and social connectedness on third-year retention, transfer, and dropout behavior. To accommodate the three outcome categories and nesting of data within institutions, we fit a hierarchical multinomial logistic regression path model with first-year academic performance as a mediating effect. Our sample included 6,872 students representing 23 four-year universities and colleges. This work expands the current state of persistence research by (1) considering the effects of motivation and social connectedness on college persistence beyond the first year of college, (2) testing whether the effects of motivation and social connectedness on third-year retention and transfer are direct, indirect, or both, and (3) testing whether the effects of academic performance, motivation, and social connectedness are different for retention and transfer. We found that academic performance has large effects on likelihood of retention and transfer; academic self-discipline, pre-college academic performance, and pre-college educational development have indirect effects on retention and transfer; and college commitment and social connectedness have direct effects on retention. Academic self-discipline led to greater first-year academic performance, which suppressed its effect on retention and transfer. Practical and theoretical implications of these findings and directions for future research are discussed.

Keywords

College persistence Retention Transfer Academic motivation Social connectedness 

References

  1. ACT, Inc. (1997a). ACT assessment technical manual. Iowa City, IA: Author.Google Scholar
  2. ACT, Inc. (1997b). Prediction research services summary tables. Iowa City, IA: Author.Google Scholar
  3. ACT, Inc. (2005). Crisis at the core. Iowa City, IA: Author.Google Scholar
  4. ACT, Inc. (2006). National collegiate retention and persistence to degree rates. Iowa City, IA: Author.Google Scholar
  5. Agresti, A. (1990). Categorical data analysis. New York: Wiley.Google Scholar
  6. Allen, J., Robbins, S., & Sawyer, R. (2008). Can measuring psychosocial factors promote college success? Manuscript submitted for publication.Google Scholar
  7. Braxton, J., Sullivan, A., & Johnson, R. (1997). Appraising Tinto’s theory of college student departure. In J. C. Smart (Ed.) Higher education: Handbook of theory and research (Vol. 12, pp. 107–158). New York: Agathon.Google Scholar
  8. Bridgeman, B., McCamley-Jenkins, L., & Ervin, N. (2000). Predictions of freshman grade point average from the revised and recentered SAT I: Reasoning test. College Board Research Report No. 2000-1. New York: College Entrance Examination Board.Google Scholar
  9. Burd, S. (2004). Colleges permit too many needy students to drop out, says report on graduation rates. Chronicle of Higher Education, 50(39), A19.Google Scholar
  10. Cabrera, A. F., Castaneda, M. B., Nora, A., & Hengstler, D. (1992). The convergence between two theories of college persistence. Journal of Higher Education, 63, 143–164.CrossRefGoogle Scholar
  11. Cabrera, A., Nora, A., & Castaneda, M. (1993). College persistence: Structural equations modeling test of an integrated model of student retention. Journal of Higher Education, 62, 123–139.CrossRefGoogle Scholar
  12. Carey, K. (2004). A matter of degrees: Improving graduation rates in four-year colleges and universities. Washington, DC: The Education Trust.Google Scholar
  13. Cole, R. P., Saltonstall, M., & Gore, P. (2008). Assessing student readiness to promote student success: A campus collaboration. In W. Troxel & M. Cutright (Eds.), Exploring the evidence: Campus-wide initiatives in the first college year. Columbia, SC: The National Resource Center for the First-Year Experience and Students in Transition, University of South Carolina.Google Scholar
  14. DesJardins, S., Ahlburg, D., & McCall, B. (2002). A temporal investigation of the factors related to timely degree completion. Journal of Higher Education, 73, 555–581.CrossRefGoogle Scholar
  15. DesJardins, S. L., Kim, D. O, & Rzonca, C. S. (2002–2003). A nested analysis of factors affecting bachelor’s degree completion. Journal College Student Retention, 4, 407–435.Google Scholar
  16. Easterling, D., Pattern, J., & Krile, D. (1995). The impact of developmental education on student progress: A three-year longitudinal analysis. Paper presented at the meeting of the Association for Institutional Research, Boston.Google Scholar
  17. Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53, 109–132.CrossRefGoogle Scholar
  18. Fidler, P. (1999). The USC Freshman Seminar today: Twenty-five years of outcomes results. Paper presented at the 12th International Conference on the First-Year Experience, Edinburgh, Scotland.Google Scholar
  19. Geweke, J. (1992). Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments (with discussion). In J. M. Bernado, et al. (Eds.), Bayesian statistics 4 (pp. 169–193). Oxford: Oxford University Press.Google Scholar
  20. Harackiewicz, J. M., Barron, K. E., Tauer, J. M., & Elliot, A. J. (2002). Predicting success in college: A longitudinal study of achievement goals and ability measures as predictors of interest and performance from freshman year through graduation. Journal of Educational Psychology, 94, 562–575.CrossRefGoogle Scholar
  21. Herzog, S. (2005). Measuring determinants of student return vs. dropout/stopout vs. transfer: A first-to-second year analysis of new freshmen. Research in Higher Education, 46, 883–928.CrossRefGoogle Scholar
  22. Johnson, V. E. (2003). Grade inflation: A crisis in college education. New York: Springer-Verlag.Google Scholar
  23. Le, H., Casillas, A., Robbins, S., & Langley, R. (2005). Motivational and skills, social, and self-management predictors of college outcomes: Constructing the student readiness inventory. Educational and Psychological Measurement, 65, 482–508.CrossRefGoogle Scholar
  24. Liu, W. M., Ali, S. R., Soleck, G., Hopps, J., Dunston, K., & Pickett, T. (2004). Using social class in counseling psychology research. Journal of Counseling Psychology, 51, 3–18.CrossRefGoogle Scholar
  25. Mackinnon, D. P., & Dwyer, J. H. (1993). Estimating mediated effects in prevention studies. Evaluation Review, 17, 144–158.CrossRefGoogle Scholar
  26. Mackinnon, D. P., Krull, J. L., & Lockwood, C. M. (2000). Equivalence of the mediation, confounding and suppression effect. Prevention Science, 1, 173–181.CrossRefGoogle Scholar
  27. McGrath, M., & Braunstein, A. (1997). The prediction of freshmen attrition: An examination of the importance of certain demographic, academic, financial, and social factors. College Student Journal, 31, 396–408.Google Scholar
  28. Mitchell, T. R., Holtom, B. C., Lee, T. W., Sablynski, C. J., & Erez, M. (2001). Why people stay: Using job embeddedness to predict voluntary turnover. Academy of Management Journal, 44, 1102–1122.CrossRefGoogle Scholar
  29. National Center for Supplemental Instruction. (1997). Supplemental Instruction (SI): Review of research concerning the effectiveness of SI from the University of Missouri-Kansas City and other institutions from across the United States. Kansas City: University of Missouri- Kansas City, Center for Academic Development.Google Scholar
  30. Nora, A., & Carbrera, A. (1993). The construct validity of institutional commitment: A confirmatory factor analysis. Research in Higher Education, 34, 243–262.CrossRefGoogle Scholar
  31. Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students: A third decade of research. San Francisco: Jossey-Bass.Google Scholar
  32. Peterson, C. H., Casillas, A., & Robbins, S. B. (2006). The student readiness inventory and the big five: Examining social desirability and college academic performance. Personality and Individual Differences, 41, 663–673.CrossRefGoogle Scholar
  33. Porter, S. R. (2002). Including transfer-out behavior in retention models: Using the NSC EnrollmentSearch data. AIR Professional File, 82(Winter), 1–16.Google Scholar
  34. Robbins, S., Allen, J., Casillas, A., Peterson, C., & Le, H. (2006). Unraveling the differential effects of motivational and skills, social, and self-management measures from traditional predictors of college outcomes. Journal of Educational Psychology, 98, 598–616.CrossRefGoogle Scholar
  35. Robbins, S., Lauver, K., Le, H., Davis, D., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological Bulletin, 130, 261–288.CrossRefGoogle Scholar
  36. Seidman, A. (1991). The evaluation of a pre/post admissions/counseling process at a suburban community college: Impact on student satisfaction with the faculty and the institution, retention, and academic performance. College and University, 66, 223–232.Google Scholar
  37. Selingo, J. (2001) Colleges and lawmakers push students to graduate in 4 years. Chronicle of Higher Education, 48(11), A22.Google Scholar
  38. Spiegelhalter, D., Thomas, A., Best, N., & Lunn, D. (2003). WinBUGS user manual version 1.4, January 2003. Cambridge, UK: MRC Biostatistics Unit, Institute of Public Health.Google Scholar
  39. Tinto, V. (1993). Leaving college: Rethinking the cause and cures of student attrition (2nd ed.). Chicago: University of Chicago.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Jeff Allen
    • 1
  • Steven B. Robbins
    • 1
  • Alex Casillas
    • 1
  • In-Sue Oh
    • 2
  1. 1.ACT, Inc.Iowa CityUSA
  2. 2.Department of Management and Organizations, Henry B. Tippie College of BusinessUniversity of IowaIowa CityUSA

Personalised recommendations