Examining the Impact of Proposition 48 on Graduation Rates in Division 1A Football and Program Recruiting Behavior

Abstract

The intersection of athletics and academics is legitimized through eligibility rules, which provide standards that bind commercial athletics to the educational purposes of higher education. To compete in intercollegiate athletics, freshman student athletes must meet the initial academic eligibility criteria set by the National Collegiate Athletic Association (NCAA) membership. Proposition 48 crystallized many of the calls for reform regarding inadequate academic standards in the public and postsecondary institutions that occurred during the early 1980s. In this article, the authors propose and test a time series structural equation model to investigate Proposition 48's impact on raising Division IA freshman student athletes' graduation rates in football and its impact in changing football programs' recruiting practices regarding freshman and junior college student athletes.

Keywords

Proposition 48 policy change

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References

Brewer, D. , Gates, S. M. , & Goldman, C. A. (2002).In pursuit of prestige: Strategy and competition in U.S. higher education. New Brunswick, NJ: Transaction Books.

Campbell, D. T. , & Stanley, J. C. (1963). Experimental and quasi-experimental designs for research. Chicago: Rand McNally.

Cook, T. D. (2002). Randomized experiments in education: Why are they so rare? Educational Evaluation and Policy Analysis, 24(3), 175-200.

Cook, T. D. , & Campbell, D. T. (1979). Quasi-experimentation: Design and analysis issues for field settings. Boston: Houghton Mifflin.

Coplin, W. D. , & O'Leary, M. K. (1981). Basic policy studies skills. Croton-on-Hudson, NY: Policy Studies.

Covell, D. , & Barr, C. A. (2001). Ties that bind: Presidential involvement with the development of NCAA Division I initial eligibility legislation. Journal of Higher Education, 72(4), 415-452.

Cureton et al. v. NCAA, 37 F. Supp. 2D 687; 1999 U.S. Dist. LEXIS 2359 (1991).

Helman, J. W. (1989). A history of American intercollegiate athletic eligibility: Educational compromises to competitive interests. Unpublished doctoral dissertation, Pennsylvania State University.

Lawson, H. A. , & Ingram, A. G. (1980). Conflicting ideologies concerning the university and intercollegiate athletics: Harper and Hutchins at Chicago, 1892-1940. Journal of Sports History, 7(3), 37-67.

10.

Lilley, T. J. (1987, September 28). Effects of bylaw 5-1-(j) won't be known for years. NCAA News, 1-2.

11.

Marcoulides, G. A. , & Hershberger, S. L. (1997). Multivariate statistical methods. Mahwah, NJ: Lawrence Erlbaum.

12.

Muthén, B. O. (2002). Beyond SEM: General latent variable modeling. Behaviormetrika,29, 81-117.

13.

Muthén, B. O., & Asparouhov, T. (2003). Advances in latent variable modeling, Part 1: Integrating multilevel and structural equation modeling using Mplus. Unpublished manuscript.

14.

Muthén, L. , & Muthén, B. O. (1998-2004). Mplus user's guide. Los Angeles: Author.

15.

National Collegiate Athletic Association (1999). 1999 NCAA graduation-rates summary. Retrieved November 22, 2005, from http://www.ncaa.org/grad_rates/1999/index.html

16.

National Collegiate Athletic Association , (2004). 1981-82-2003-04 sports sponsorship and participation report. Retrieved November 22, 2005, from http://www.ncaa.org/library/research/participation_rates/1982-2004/1982_2004_participation_rates.pdf

17.

Ostrom, E. (1999). Institutional rational choice: An assessment of the institutional analysis and development framework. In P. A. Sabatier (Ed.),Theories of the policy process(pp. 35-71). Boulder, CO: Westview.

18.

Raykov, T. , & Marcoulides, G. A. (2000). A first course in structural equation modeling. Mahwah, NJ: Lawrence Erlbaum.

19.

Suggs, W. (1999, April 9). Fight over NCAA standards reflects long-standing dilemma. Chronicle of Higher Education, A35-A36.

20.

Tyack, D. B. (1991). Public school reform: Policy talk and institutional practice. American Journal of Education, 99(1), 1-19.

21.

Willett, J. , & Sayer, A. (1996). Cross-domain analysis of change over time: Combining growth modeling and covariance structure analysis. In G. A. Marcoulides & R. Schumacker (Eds.),Advanced structural equation modeling: Issues and techniques (pp. 125-158). Mahwah, NJ: Lawrence Erlbaum.