Advertisement

Research in Higher Education

, Volume 58, Issue 2, pp 184–213 | Cite as

Rethinking Graduation and Time to Degree: A Fresh Perspective

  • Hongtao YueEmail author
  • Xuanning Fu
Article

Abstract

Graduation and time to degree are paramount concerns in higher education today and have caught the attention of policy makers, educators and researchers in recent years. However, our understanding is limited regarding the factors related to graduation and time to degree beyond students’ pre-college characteristics (demographics and academic preparation), especially how student decision and performance in college affect their graduation. This study employs longitudinal data and applies event history analysis to track 12,096 first-time freshmen in a large public university from 2002 to 2014. Students’ academic progress is conceptualized into eight time-dependent variables whose values change over time, including major status (major change, double majors/minors and major declaration), enrollment intensity (enrolled term units and extra enrollment), and academic performance (term GPA, cumulative units and cumulative GPA). Discrete-time hazard models were used to answer the following question: beyond pre-college characteristics, what aspects of students’ decisions on majors and enrollment and their performance affect graduation and time to degree? The findings reveal that academic performance is the most important factor, followed by students’ decisions on majors (such as having double majors/minors). Pre-college characteristics only accounted for a very small proportion of the total variance after students’ performance and decisions are controlled. The study goes further in investigating how the effects of these factors change over time by enrolled terms.

Keywords

Graduation Time to degree Enrolled terms Event history analysis Time-dependent variables Time-varying effects 

References

  1. Adelman, C. (2006). The toolbox revisited: Paths to degree completion from high school through college. U.S. Department of Education, 1-202. http://www2.ed.gov/rschstat/research/pubs/toolboxrevisit/index.html. Accessed Sept 2014.
  2. Allen, J., & Robbins, S. (2010). Effects of interest–major congruence, motivation, and academic performance on timely degree attainment. Journal of Counseling Psychology, 57(1), 23.CrossRefGoogle Scholar
  3. Allen, J., Robbins, S. B., Casillas, A., & Oh, I. S. (2008). Third-year college retention and transfer: Effects of academic performance, motivation, and social connectedness. Research in Higher Education, 49(7), 647–664.CrossRefGoogle Scholar
  4. Allison, P. D. (1982). Discrete-time methods for the analysis of event histories. In S. Leinhart (Ed.), Sociological methodology (pp. 61–98). San Francisco: Jossey-Bass.Google Scholar
  5. Allison, P. D. (1984). Event history analysis: Regression for longitudinal event data. Sage University Papers: Quantitative Applications in the Social Sciences, 07-046. Newbury Park, CA: Sage.Google Scholar
  6. Allison, P. D. (2010). Survival analysis using SAS: A practical guide (2nd ed.). Cary: SAS Institute.Google Scholar
  7. Arcidiacono, P., Aucejo, E. M., & Spenner, K. (2012). What happens after enrollment? An analysis of the time path of racial differences in GPA and major choice. IZA Journal of Labor Economics, 1(1), 1–24.CrossRefGoogle Scholar
  8. Attewell, Paul, Scott Heil, and Liza Reisel. (2011). What Is Academic Momentum? And Does It Matter? Education Evaluation and Policy Analysis. American Educational Research Association, 22 Nov. 2011. Web. 22 Feb. 2016.Google Scholar
  9. Bahr, P. R. (2009). Educational attainment as process: Using hierarchical discrete-time event history analysis to model rate of progress. Research in Higher Education, 50(7), 691–714.CrossRefGoogle Scholar
  10. 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.CrossRefGoogle Scholar
  11. Beekhoven, S., De Jong, U., & Van Hout, H. (2003). Different courses, different students, same results? An examination of differences in study progress of students in different courses. Higher Education, 46(1), 37–59.CrossRefGoogle Scholar
  12. Berger, J. B. (2000). Organizational behavior at college and student outcomes: A new perspective on college impact. The Review of Higher Education, 23(2), 177–198.CrossRefGoogle Scholar
  13. Berger, J. B., & Milem, J. F. (2000). Organizational behavior in higher education and student outcomes. In J. C. Smart & W. G. Tierney (Eds.), Higher Education: Handbook of Theory and Research. New York: Agathon.Google Scholar
  14. Boughan, K. (2000). The role of academic process in student achievement: an application of structural equations modeling and cluster analysis to community college longitudinal data. Air Professional File, 74, 1–17.Google Scholar
  15. Bound, J., Lovenheim, M. F., & Turner, S. (2010a). Why have college completion rates declined? An analysis of changing student preparation and collegiate Resources. American Economic Journal: Applied Economics, American Economic Association, 2(3), 129–157.Google Scholar
  16. Bound, J., Lovenheim, M. F. & Turner, S. (2010b). Increasing Time to Baccalaureate Degree in the United StatesGoogle Scholar
  17. Braxton, J. M., & Hirschy, A. S. (2005). Theoretical developments in the study of college student departure. College Student Retention: Formula for Student Success, 3, 61–87.Google Scholar
  18. Cabrera, A. F., Burkum, K. R., & La Nasa, S. M. (2003). Pathways to a four-year degree: Determinants of degree completion among socioeconomically disadvantaged students. Paper presented at the annual meeting of the Association for the Study of Higher Education, Portland, Oregon. ERIC ED482160.Google Scholar
  19. Chen, X. (2005). First Generation Students in Postsecondary Education: A Look at Their College Transcripts. (NCES 2005-171). U.S. Department of Education, National Center for Education Statistics. Washington, DC: U.S. Government Printing Office.Google Scholar
  20. Chen, X. (2007). Part-Time Undergraduates in Postsecondary Education: 2003–04. Postsecondary Education Descriptive Analysis Report. NCES 2007–165. National Center for Education Statistics.Google Scholar
  21. Chen, R. (2008). Financial aid and student dropout in higher education: A heterogeneous research approach. In John Smart (Ed.), Higher Education: Handbook of Theory and Research (Vol. 23, pp. 209–240). New York: Springer.CrossRefGoogle Scholar
  22. Chen, R. (2012). Institutional characteristics and college student dropout risks: A multilevel event history analysis. Research in Higher Education, 53(5), 487–505.CrossRefGoogle Scholar
  23. DeAngelo, L., Franke, R., Hurtado, S., Pryor, J. H., & Tran, S. (2011). Completing college: Assessing graduation rates at four-year institutions. Los Angeles: Higher Education Research Institute at UCLA.Google Scholar
  24. DesJardins, S. L. (2003). Event history methods: Conceptual issues and an application to student departure from college. In J. Smart (Ed.), Higher education: Handbook of theory and research (Vol. XVIII, pp. 421–471). New York: Agathon Press.CrossRefGoogle Scholar
  25. DesJardins, S. L., Ahlburg, D. A., & McCall, B. P. (2002a). A temporal investigation of factors related to timely degree completion. Journal of Higher Education, 73, 555–581.CrossRefGoogle Scholar
  26. DesJardins, S. L., Ahlburg, D. A., & McCall, B. P. (2002b). Simulating the longitudinal effects of changes in financial aid on student departure from college. Journal of Human Resources, 37, 653–679.CrossRefGoogle Scholar
  27. DesJardins, S. L., Kim, D.O., & Rzonca, C. S. (2002–2003). A nested analysis of factors affecting bachelor’s degree completion. Journal of College Student Retention: Research, Theory and Practice, 4(4), 407–435.Google Scholar
  28. DesJardins, S. L., McCall, B. P., Ahlburg, D. A., & Moye, M. J. (2002c). Adding a timing light to the “Tool Box”. Research in Higher Education, 43(1), 83–114.CrossRefGoogle Scholar
  29. Feldman, K. A., Smart, J. C., & Ethington, C. A. (1999). Major field and person-environment fit: Using Holland’s theory to study change and stability of college students. Journal of Higher Education, 70, 642–669.CrossRefGoogle Scholar
  30. Foraker, M. J. (2012). Does Changing Majors Really Affect the Time to Graduate? The Impact of Changing Majors on Student Retention, Graduation, and Time to Graduate.Google Scholar
  31. Friedman, B. A., & Mandel, R. G. (2011). Motivation predictors of college student academic performance and retention. Journal of College Student Retention: Research, Theory and Practice, 13(1), 1–15.CrossRefGoogle Scholar
  32. Garibaldi, P., Giavazzi, F., Ichino, A., & Rettore, E. (2012). College cost and time to complete a degree: Evidence from tuition discontinuities. Review of Economics and Statistics, 94(3), 699–711.CrossRefGoogle Scholar
  33. Gross, J. P. K., Vasti, T., & Desiree, Z. (2012). Financial aid and attainment among students in a state with changing demographics. Research in Higher Education, 06 Nov. 2012. Web. 22 Feb. 2016.Google Scholar
  34. Hagedorn, L. S., Maxwell, W. E., Cypers, S., Moon, H. S., & Lester, J. (2007). Course shopping in urban community colleges: An analysis of student drop and add activities. Journal of Higher Education, 78(4), 464–485.CrossRefGoogle Scholar
  35. Hall, M. (1999). Why students take more than four years to graduate. In Association for Institutional Research Forum, New Orleans, LAGoogle Scholar
  36. Harvey, J., & Wenzel, A. (Eds.). (2001). Close romantic relationships: Maintenance and Enhancement. New Jersey: Lawrence Erlbaum Associates Inc.Google Scholar
  37. Hoffer, T. B., & Welch, V. (2006). Time to degree of US research doctorate recipients. National Science Foundation. Accessed at Sept 2014, http://www.nsf.gov/statistics/infbrief/nsf06312/nsf06312.pdf
  38. Holland, J. L. (1997). Making vocational choices: A theory of vocational personalities and work environments. Psychological Assessment Resources.Google Scholar
  39. International Center for Supplemental Instruction. (2014). National Supplemental Instruction Report Fall 2002-Spring 2013. International Center for Supplemental Instruction, University of Missouri—Kansas City http://www.umkc.edu/asm/si/si-docs/National%20Data%20updated%20slides_09-13-2013.pdf. Accessed at September 2014.
  40. 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.CrossRefGoogle Scholar
  41. John, E. P. S., Hu, S., Simmons, A., Carter, D. F., & Weber, J. (2004). What difference does a major make? The influence of college major field on persistence by African American and White students. Research in Higher Education, 45(3), 209–232.CrossRefGoogle Scholar
  42. 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.CrossRefGoogle Scholar
  43. Jones, S., Sugar, T., Baumgardner, M., Raymond, D., Moore, W., Davidson, R., & Denham, K. (2012). Remediation: Higher education’s bridge to nowhere. Washington: Complete College America.Google Scholar
  44. Kalamatianou, A. G., & McClean, S. (2003). The perpetual student: Modeling duration of undergraduate studies based on lifetime-type educational data. Lifetime Data Analysis, 9(4), 311–330.CrossRefGoogle Scholar
  45. Knight, W. E. (2002). Toward a comprehensive model of influences upon time to bachelor’s degree attainment. AIR Professional File, 85, 1–15.Google Scholar
  46. Knight, W. E. (2004). Time to bachelor’s degree attainment: An application of descriptive bivariate, and multiple regression techniques. IR Applications: Using Advanced Tools, Techniques, and Methodologies, 2, 1–15.Google Scholar
  47. Knight, W. E., & Arnold, W. (2000). Towards a comprehensive predictive model of time to bachelor’s degree attainment. In annual forum of the Association for Institutional Research, Cincinnati, OHGoogle Scholar
  48. Lam, L. T. (1999). Assessing financial aid impacts on time-to-degree for nontransfer undergraduate students at a large urban public university. Paper presented at 39th Annual Forum of the Association for Intuitional Research, Seattle, WA.Google Scholar
  49. Lee, G. (2010). Determinants of baccalaureate degree completion and time-to-degree for high school graduates in 1992 (Doctoral dissertation, University of Minnesota).Google Scholar
  50. Leppel, K. (2001). The impact of major on college persistence among freshmen. Higher Education, 41(3), 327–342.CrossRefGoogle Scholar
  51. Lockeman, K. S., & Pelco, L. E. (2013). The relationship between service-learning and degree completion. Michigan Journal of Community Service Learning, 20(1), 18–30.Google Scholar
  52. Megerian, C., & Gordon L. (2013). Brown wants to tie some funding of universities to new proposals. Los Angeles Times. http://articles.latimes.com/2013/apr/22/local/la-me-brown-higher-ed-20130423. Accessed Sept 2014.
  53. National Center for Education Statistics. (2012). 2004/09 beginning postsecondary students longitudinal study (BPS: 04/09) restricted use data and codebook. Washington, DC: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education.Google Scholar
  54. National Conference of State legislatures. (2014). Performance-based funding for higher education. National Conference of State legislatures (NCSL). http://www.ncsl.org/research/education/performance-funding.aspx. Accessed at September 2014.
  55. NCES. (2013). Digest of Education Statistics, 2013. National Center for Education Statistics (NCES). Table 305.40.Google Scholar
  56. Nora, A., Barlow, L., & Crisp, G. (2005). Student persistence and degree attainment beyond the first year in college. College student retention: Formula for success, pp. 129–153Google Scholar
  57. Pike, G. R. (2013). Time-varying effects of student background characteristics, high school experiences, college expectations, and initial enrollment characteristics on degree attainment. Paper presented at the annual meeting of the Association for Institutional Research, Long BeachGoogle Scholar
  58. Pitter, G.W., LeMon, R.E., Lanham, C.H. (1996). Hours to graduation: A national survey of credit hours required for baccalaureate degrees. Paper presented to the annual forum of the Association for Institutional Research, Albuquerque, NM.Google Scholar
  59. Roksa, J., Jenkins, D., Jaggars, S. S., Zeidenberg, M., & Cho, S. (2009). Strategies for promoting gatekeeper success among students needing remediation: Research report for the Virginia community college system. New York: Columbia University, Teachers College, Community College Research Center.Google Scholar
  60. Rusbult, C. E., Martz, J. M., & Agnew, C. R. (1998). The investment model Scale: Measuring commitment level, satisfaction level, quality of alternatives, and investment size. Personal Relationships, 5(4), 357–391.CrossRefGoogle Scholar
  61. Russell, A. W., Dolnicar, S., & Ayoub, M. (2008). Double degrees: Double the trouble or twice the return? Higher Education, 55(5), 575–591.CrossRefGoogle Scholar
  62. Scott-Clayton, J., Crosta, P., & Belfield, C. (2014). Improving the targeting of treatment: Evidence from college remediation. Educational Evaluation and Policy Analysis, 36(3), 371–393.CrossRefGoogle Scholar
  63. Singer, J. D., & Willett, J. B. (1991). Modeling the days of our lives: Using survival analysis when designing and analyzing longitudinal studies of duration and the timing of events. Psychological Bulletin, 110(2), 268–290.CrossRefGoogle Scholar
  64. Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and occurrence. New York: Oxford University Press.CrossRefGoogle Scholar
  65. Sklar, J. (2014). The impact of change of major on time to Bachelor’s degree completion with special emphasis on STEM disciplines: A multilevel discrete-time hazard modeling Xapproach final report. http://admin.airweb.org/GrantsAndScholarships/Documents/Grants2013/SklarFinalReport.pdf. Accessed at May 2015.
  66. Snyder, T. D., de Brey, C., & Dillow, S. A. (2014). Digest of education statistics 2014. National Center for Education Statistics.Google Scholar
  67. Steele, F. (2005). Event history analysis. NCRM/004. National Centre for Research Methods (Unpublished).Google Scholar
  68. Swail, W. S. (2003). Retaining minority students in higher education: A framework for success. ASHE-ERIC higher education report. Jossey-Bass higher and adult education series. San Francisco: Jossey-Bass.Google Scholar
  69. Thayer, & Paul B. (2000). Retention of students from first generation and low income backgrounds (ERICED446633). Opportunity Outlook (May), (pp.2–8).Google Scholar
  70. Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of recent research. Review of Educational Research, 45(1), 89–125.CrossRefGoogle Scholar
  71. Tinto, V., & Pusser, B. (2006). Moving from theory to action: Building a model of institutional action for student success. National Postsecondary Education Cooperative. http://web.ewu.edu/groups/academicaffairs/IR/NPEC_5_Tinto_Pusser_Report.pdf. Accessed 22 Feb 2016.
  72. Titus, M. A. (2006). No college student left behind: The influence of financial aspects of a state’s higher education policy on college completion. The Review of Higher Education, 29(3), 293–317.CrossRefGoogle Scholar
  73. Trapmann, S., Hell, B., Hirn, J. O. W., & Schuler, H. (2007). Meta-analysis of the relationship between the Big Five and academic success at university. Zeitschrift für Psychologie/Journal of Psychology, 215(2), 132–151.CrossRefGoogle Scholar
  74. Umbricht, M. R. (2012). First in, last out: Time-to-degree of first-generation students. Thesis. University of Illinois at Urbana-Champaign, 2012.Google Scholar
  75. Van Der Hulst, M., & Jansen, E. (2002). Effects of curriculum organization on study progress in engineering studies. Higher Education, 43(4), 489–506.CrossRefGoogle Scholar
  76. Vargas, J. H. (2004). College knowledge: Addressing information barriers to college. Boston, MA: College Access Services: The Education Research Institute (TERI). www.teri.org
  77. Volkwein, J. F., & Lorang, W. G. (1996). Characteristics of extenders: Full-time students who take light credit loads and graduate in more than four years. Research in Higher Education, 37(1), 43–67.CrossRefGoogle Scholar
  78. Woo, J., Green, C., & Matthews, M. (2012). Web tables: profile of 2007-08 first-time bachelor's degree recipients in 2009. National Center for Education Statistics.Google Scholar
  79. Zhu, L. (2004). Exploring the determinants of time-to-degree in public 4-year colleges. Online Submission. ERIC.Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Office of Institutional EffectivenessCalifornia State University, FresnoFresnoUSA
  2. 2.California State University, FresnoFresnoUSA

Personalised recommendations