Research in Higher Education

, Volume 27, Issue 1, pp 15–38 | Cite as

The estimation of a conceptual model of nontraditional undergraduate student attrition

  • Barbara S. Metzner
  • John P. Bean
Article

Abstract

The purpose of this study was to estimate a conceptual model of nontraditional student attrition. Data were gathered from 624 nontraditional (commuter, part-time) freshmen at a midwestern urban university enrolling 22,000 students. For these nontraditional students, dropout was a function of GPA and credit hours enrolled, as well as the utility of education for future employment, satisfaction with the student role, opportunity to transfer, and age affecting dropout through intent to leave. In addition, absence from class, age, high school performance, and ethnicity had indirect effects on dropout through GPA. These results suggested that nontraditional students dropped out of college for academic reasons or because they were not committed to attending the institution, but their reasons for leaving were unrelated to social factors at school. The findings helped validate the conceptual model.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aitken, N. D. (1982). College student performance, satisfaction, and retention.Journal of Higher Education 53: 32–50.Google Scholar
  2. Allen, W. R. (1981). Correlates of black student adjustment, achievement, and aspirations at a predominately white southern university. In G. Thomas (ed.),Black Students in Higher Education pp. 126–141. Westport, CT: Greenwood Press.Google Scholar
  3. Anderson, K. L. (1981). Post-high school experiences and college attrition.Sociology of Education 54: 1–15.Google Scholar
  4. Astin, A. W. (1975).Preventing Students from Dropping Out. San Francisco: Jossey-Bass.Google Scholar
  5. Baumgart, N. L., and Johnstone, J. N. (1977). Attrition at an Australian university.Journal of Higher Education 48: 553–570.Google Scholar
  6. Bean, J. P. (1985). Interaction effects based on class level in an explanatory model of college student dropout syndrome.American Educational Research Journal 22: 35–64.Google Scholar
  7. Bean, J. P., and Metzner, B. S. (1985). A conceptual model of nontraditional undergraduate student attrition.Review of Educational Research 55: 485–540.Google Scholar
  8. Behrendt, R. L. (1974). Attrition/retention patterns at HJC. Final report. Hagerstown, MD: Hagerstown Junior College. (ERIC Document Reproduction Service No. ED 088 539.)Google Scholar
  9. Bentler, P. M., and Speckart, G. (1979). Models of attitude-behavior relations.Psychological Review 86: 452–464.Google Scholar
  10. California State Coordinating Council for Higher Education (1974). Through the open door: A study of persistence and performance in California's community colleges (Report No. 3). Sacramento, CA (ERIC Document Reproduction Service No. ED 121 393.)Google Scholar
  11. Carnegie Council on Policy Studies in Higher Education (1980).Three Thousand Futures. San Francisco: Jossey-Bass.Google Scholar
  12. Carter, B. L. (1982). Exit interview summary, fall, 1981. Indianapolis, IN: Indiana University-Purdue University, Office of Student Services.Google Scholar
  13. Cope, R. G., and Hannah, W. (1975).Revolving College Doors. New York: Wiley.Google Scholar
  14. Fetters, W. B. (1977) National Longitudinal Study: Withdrawal from institutions of higher education. Washington, DC: U.S. Department of Health, Education, and Welfare, National Center for Education Statistics. (ERIC Document Reproduction Service No. ED 150 913.)Google Scholar
  15. Gorter, S. (1978). Non-returning students, spring 1978. Trenton, NJ: Mercer County Community College. (ERIC Document Reproduction Service No. ED 161 473.)Google Scholar
  16. Greer, L. R. (1980). Persistence and academic success among non-traditional age students at a junior college. Paper presented at the annual forum of the Association for Institutional Research, Atlanta, GA (ERIC Document Reproduction Service No. ED 189 942.)Google Scholar
  17. Heise, D. R. (1969). Problems in path analysis and causal inference. In E. F. Borgatta (ed.),Sociological Methodology. San Francisco: Jossey-Bass.Google Scholar
  18. Heise, D. R. (1975).Causal Analysis. New York: Wiley-Interscience.Google Scholar
  19. Johnson, R. H. (1980). The relationship of academic and social integration to student attrition—A study across institutions and institutional types.Dissertation Abstracts International 41: 1868A. (University Microfilms No. 80-25, 700.)Google Scholar
  20. Kasworm, C. E. (1980). The older student as an undergraduate.Adult Education 31: 30–47.Google Scholar
  21. Kerlinger, F. N., and Pedhazur, E. J. (1973).Multiple Regression in Behavioral Research. New York: Holt, Rinehart, and Winston.Google Scholar
  22. Kimball, R. L., and Sedlacek, W. E. (1971). Characteristics of older undergraduates at the University of Maryland. College Park: University of Maryland, Counseling Center. (ERIC Document Reproduction Service No. ED 165 523.)Google Scholar
  23. Knoell, D. M. (1966). A critical review of research on the college dropout. In L. A. Pervin, L. E. Reik, and W. Dalrymple (eds.),The College Dropout and the Utilization of Talent pp. 63–81. Princeton, NJ: Princeton University Press.Google Scholar
  24. Land, K. C. (1969). Principles of path analysis. In E. F. Borgatta (ed.),Sociological Methodology. San Francisco: Jossey-Bass.Google Scholar
  25. Lenning, O. T., Beal, P. E., and Sauer, K. (1980). Retention and attrition: Evidence for action and research. Boulder, CO: National Center for Higher Education Management Systems.Google Scholar
  26. Lewin, K. (1935).A Dynamic Theory of Personality: Selected Papers. New York: McGraw-Hill.Google Scholar
  27. Lewis-Beck, M. S. and Mohr, L. B. (1976). Evaluating affects of independent variables.Political Methodology 3: 27–49.Google Scholar
  28. Locke, E. A. (1976). The nature and causes of job satisfaction. In M. D. Dunnett (ed.),Handbook of Industrial and Organizational Psychology. Chicago: Rand McNally.Google Scholar
  29. Metzner, B. S. (1984). An application and evaluation of a model of student attrition using freshmen at a public urban commuter university.Dissertation Abstracts International 44: 2378A. (University Microfilms No. 83-28,8080.)Google Scholar
  30. Munro, B. H. (1981). Dropouts from higher education: Path analysis of a national sample.American Educational Research Journal 18: 133–141.Google Scholar
  31. National Institute of Education (1984). Involvement in learning: Realizing the potential of American higher education. Report of the Study Group on the Conditions of Excellence in American Higher Education. Washington, DC: U.S. Government Printing Office.Google Scholar
  32. Nunnally, J. C. (1967).Psychometric Theory. New York: McGraw-Hill.Google Scholar
  33. Pantages, T. J., and Creedon, C. F. (1978). Studies of college attrition: 1950–1975.Review of Educational Research 48: 49–101.Google Scholar
  34. Pascarella, E. T. (1980). Student-faculty informal contact and college outcomes.Review of Educational Research 50: 545–595.Google Scholar
  35. Pascarella, E. T., and Chapman, D. W. (1983). A multi-institutional, path analytic validation of Tinto's model of college withdrawal.American Educational Research Journal 20: 87–102.Google Scholar
  36. Pascarella, E. T., Duby, P. B., and Iverson, B. K. (1983). A test and reconceptualization of a theoretical model of college withdrawal in a commuter institution setting.Sociology of Education 56: 88–100.Google Scholar
  37. Preston, W. G. (1976). Adults as regular community college students: Comparative analysis of some of their characteristics and perceptions and those of college-age students. Pleasant Hill, CA: Diablo Valley College. (ERIC Document Reproduction Service No. ED 121 368.)Google Scholar
  38. Rice, R. L. (1983). USC Lancaster: A retention study for a two-year commuter campus. Lancaster: University of South Carolina. (ERIC Document Reproduction Service No. ED 231 440.)Google Scholar
  39. Roelfs, P. J. (1975). Teaching and counseling older college students.Findings, Vol. 2. Princeton, NJ: Educational Testing Service.Google Scholar
  40. Sexton, V.S. (1965). Factors contributing to attrition in college populations: Twenty-five years of research.Journal of General Psychology 72: 301–326.Google Scholar
  41. Spady, W. G. (1970). Dropouts from higher education: An interdisciplinary review and synthesis.Interchange 1: 64–85.Google Scholar
  42. Staman, E. M. (1980). Predicting student attrition at an urban college.Dissertation Abstracts International 40: 4440A. (University Microfilms No. 80-02,565.)Google Scholar
  43. Stewart, S. S., and Rue, P. (1983). Commuter students: Definition and distribution. In S. S. Stewart (ed.),Commuter students: Enhancing their Educational Experiences pp. 3–8. San Francisco: Jossey-Bass.Google Scholar
  44. Summerskill, J. (1962). Dropouts from college. In N. Sanford (ed.),The American College pp. 627–657. New York: Wiley.Google Scholar
  45. Terenzini, P. T., Pascarella, E. T., Theophilides, C., and Lorang, W. G. (1985). A replication of a path analytic validation of Tinto's theory of college student attrition.Review of Higher Education 8: 319–340.Google Scholar
  46. Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of recent research.Review of Educational Research 45: 89–125.Google Scholar
  47. Tinto, V. (1982). Limits of theory and practice in student attrition.Journal of Higher Education 53: 687–700.Google Scholar
  48. U.S. Department of Education, National Center for Education Statistics (1982). The condition of education. Washington, DC.Google Scholar
  49. Zaccaria, L., and Creaser, J. (1971). Factors related to persistence in an urban commuter university.Journal of College Student Personnel 12: 286–291.Google Scholar

Copyright information

© Agathon Press, Inc. 1987

Authors and Affiliations

  • Barbara S. Metzner
    • 1
  • John P. Bean
    • 2
  1. 1.University DivisionIndiana University-Purdue UniversityIndianapolis
  2. 2.Department of Educational Leadership and Policy StudiesIndiana UniversityBloomington

Personalised recommendations