General and Specific Goal Orientations as Correlates of Adult Student Degree Completion: Lessons from the Community College of the Air Force

Abstract

This research examined degree completion through the lens of Snyder's hope theory (Snyder, 2000) in an effort to expand the research on student retention from Tinto's sociological theory to a theory that focuses on the psychological orientations that might help explain student success. The study focused on a sample of 443 master sergeants enrolled in associate of applied science degrees offered by the Community College of the Air Force, a non-traditional, non-transfer, regionally accredited community college. The results of the logistic regression analysis revealed hope, as one component of overall goal orientation, to be a statistically significant predictor of degree attainment. Specific goal orientation, defined and measured as the strength of desire for earning this particular degree, was particularly important to degree completion for this sample.

References

Adelman

(2004). Principal indicators of student academic histories in postsecondary education, 1972–2000. Washington, DC: U.S. Department of Education.

Air Force Enlisted Demographics. (2004). Randolph Air Force Base, San Antonio, TX: Analysis and Reports Branch, HQ Air Force Personnel Center.

Andrews

Nonnecke

& Preece

(2003). Electronic survey methodology: A case study in reaching hard-to-involve Internet users. International Journal of Human-Computer Interaction, 16, 185–210.

Astin

A. W.

(1993). What matters in college? Four critical years revisited. San Francisco, CA: Jossey-Bass.

Austin

J. T.

Yaffee

R. A.

& Hinkle

D. E.

(1992). Logistic regression for research in higher education. In Smart

J. C.

(Ed.), Higher education: Handbook of theory and research (Vol. VIII, pp. 379–399). New York: Agathon Press.

Baird

L. L.

(2002). College climate and the Tinto model. In Braxton

J. M.

(Ed.), Reworking the student departure puzzle (pp. 62–80). Nashville, TN: Vanderbilt University Press.

Bean

J. P.

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

Bean

J. P.

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

Bean

J. P.

(2005). Nine themes of college student retention. In Seidman

(Ed.), College student retention: Formula for student success (pp. 215–243). Westport, CT: Praeger.

10.

Bean

J. P.

& Eaton

S. B.

(2002). A psychological model of college student retention. In Braxton

J. M.

(Ed.), Reworking the student departure puzzle (pp. 48–61). Nashville, TN: Vanderbilt University Press.

11.

Braxton

J. M.

(Ed.). (2002). Reworking the student departure puzzle. Nashville, TN: Vanderbilt University Press.

12.

Braxton

J. M.

& Hirschy

A. S.

(2005). Theoretical developments in the study of college student departure. In Seidman

(Ed.), College student retention: Formula for student success (pp. 61–87). Westport, CT: Praeger.

13.

Braxton

J. M.

& Lee

S. D.

(2005). Toward reliable knowledge about college student departure. In Seidman

(Ed.), College student retention: Formula for student success (pp. 107–127). Westport, CT: Praeger.

14.

Braxton

J. M.

Sullivan

A. S.

& Johnson

R. M.

(1997). Appraising Tinto's theory of college student departure. In Smart

J. C.

(Ed.), Higher Education: A handbook of theory and research (Vol. XII, pp. 107–164). New York: Agathon Press.

15.

Cohen

A. M.

& Brawer

F. B.

(2003). The American community college (4th ed.). San Francisco, CA: Jossey-Bass.

16.

CCSSE. (2004). Community College Survey of Student Engagement (CCSSE). University of Texas at Austin.

17.

CCSSE. (2005). Community College Survey of Student Engagement (CCSSE). University of Texas at Austin.

18.

Davis

L. J.

& Offord

K. P.

(1997). Logistic regression. Journal of Personality Assessment, 68, 497–507.

19.

DeMaris

(1992). Logit modeling: Practical applications. Newbury Park, CA: Sage.

20.

DeMaris

(1995). A tutorial in logistic regression. Journal of Marriage and the Family, 57, 956–968.

21.

Feldman

M. J.

(1993). Factors associated with one-year retention in a community college. Research in Higher Education, 34, 503–512.

22.

Field

(2003). Discovering statistics using SPSS for Windows: Advanced techniques for the beginner. Thousand Oaks, CA: Sage.

23.

Gall

M. D.

Gall

J. P.

& Borg

W. R.

(2003). Educational research: An introduction (7th ed.). Boston, MA: Allyn and Bacon.

24.

Garson

G. D. C.

(2005). Logistic regression. In PA 765 Statnotes: An on-line textbook (pp. 1–23). Retrieved April 27, 2005 from http://www2.chass.ncsu.edu/garson/pa765/logistic.html.

25.

George

& Mallery

(2003). SPSS for Windows: A simple guide and reference. Boston, MA: Pearson Education, Inc.

26.

Glass

G. V.

& Hopkins

K. D.

(1996). Statistical methods in education and psychology (3rd ed.). Boston, MA: Allyn and Bacon.

27.

Grimm

L. G.

& Yarnold

P. R.

(Eds.). (1995). Reading and understanding multivariate statistics. Washington, DC: American Psychological Association.

28.

Hagedorn

L. S.

(2005). How to define retention: A new look at an old problem. In Seidman

(Ed.), College student retention: Formula for student success (pp. 89–105). Westport, CT: Praeger.

29.

Hagedorn

L. S.

(2006). Traveling successfully on the community college pathway: The research and findings of the Transfer and Retention of Urban Community College Students project. Los Angeles, CA: University of Southern California Rossier School of Education.

30.

Halpin

R. L.

(1990). An application of the Tinto model to the analysis of freshman persistence in a community college [Electronic version]. Community College Review, 17(4), 22–33.

31.

Horn

& Nevill

(2006). Profile of undergraduates in U.S. postsecondary education institutions: 2003–2004: With a special analysis of community college students (NCES 2006–184). U.S. Department of Education. Washington, DC: National Center for Education Statistics (NCES).

32.

Hosmer

D. W.

& Lemeshow

(2000). Applied logistic regression (2nd ed.). New York: John Wiley & Sons.

33.

Kaufman

R. L.

(1996). Comparing effects in dichotomous logistic regression: A variety of standardized coefficients. Social Science Quarterly, 77, 90–109.

34.

Kraska

M. F.

Larkins

J. R.

Jr. (1999). Factors affecting master sergeants' completion of Community College of the Air Force AAS degree requirements. Journal of Industrial Teacher Education, 36(3), 5–23.

35.

Kuh

G. D.

Kinzie

Schuh

J. H.

Whitt

E. J.

, & Associates. (2005). Student success in college: Creating conditions that matter. San Francisco, CA: Jossey-Bass.

36.

Lopez

S. J.

Ciarlelli

Coffman

Stone

& Wyatt

(2000). Diagnosing for strengths: On measuring hope building blocks. In Snyder

C. R.

(Ed.), Handbook of hope: Theory, measure, and applications (pp. 57–85). San Diego, CA: Academic Press.

37.

Martinez

Jr. Nielsen

A. L.

& Lee

M. T.

(2003). Reconsidering the Marielto legacy: Race/ethnicity, nativity, and homicide motives. Social Science Quarterly, 84, 397–411.

38.

Menard

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

39.

Mutter

(1992). Tinto's theory of departure and community college student persistence. Journal of College Student Development, 33, 310–317.

40.

Newton

R. R.

& Rudestam

K. E.

(1999). Your statistical consultant: Answers to your data analysis questions. Thousand Oaks, CA: Sage.

41.

Nippert

(2001). Influences on the educational degree attainment of two-year college students. Journal of College Student Retention: Research, Theory & Practice, 2, 29–40.

42.

Pascarella

E. T.

& Chapman

D. W.

(1983). A multi-institutional, path analytic validation of Tinto's model of college withdrawal. American Educational Research Journal, 20, 87–102.

43.

Pascarella

E. T.

Duby

P. B.

& 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.

44.

Pascarella

E. T.

& Terenzini

P. T.

(2005). How college affects students: A third decade of research (Vol. 2). San Francisco, CA: Jossey-Bass.

45.

Peng

C. Y. J.

Lee

K. L.

& Ingersoll

G. M.

(2002). An introduction to logistic regression analysis and reporting. The Journal of Educational Research, 96, 3–13.

46.

Peng

C. Y. J.

& So

T. S. H.

(2002). Logistic regression analysis and reporting: A primer. Understanding Statistics, 1(1), 31–70.

47.

Porter

S. R.

& Whitcomb

M. E.

(2003). The impact of lottery incentives on student survey response rates. Research in Higher Education, 44, 389–407.

48.

Reise

S. P.

(1999). Using multilevel logistic regression to evaluate person-fit in IRT models. Multivariate Behavioral Research, 35, 543–568.

49.

Seidman

(Ed.). (2005a). College student retention: Formula for student success. Westport, CT: Praeger.

50.

Seidman

(2005b). Where we go from here: A retention formula for student success. In Seidman

(Ed.), College student retention: Formula for student success (pp. 89–105). Westport, CT: Praeger.

51.

Snyder

C. R.

(1994). The psychology of hope: You can get there from here. New York: Free Press.

52.

Snyder

C. R.

(1995). Conceptualizing, measuring, and nurturing hope. Journal of Counseling and Development, 73, 355–360.

53.

Snyder

C. R.

(Ed.). (2000). Handbook of hope: Theory, measures, and applications. San Diego, CA: Academic Press.

54.

Snyder

C. R.

(2002). Hope theory: Rainbows in the mind. Psychological Inquiry, 13, 249–275.

55.

Snyder

C. R.

(2003). Hope. Speech delivered at the Gallup Positive Psychology Center at the Second International Positive Psychology Summit in Washington, DC.

56.

Snyder

C. R.

(2005). Teaching: The lessons of hope. Journal of Social and Clinical Psychology, 24, 72–84.

57.

Snyder

C. R.

Harris

Anderson

J. R.

Holleran

S. A.

Irving

L. M.

Sigmon

S. T.

(1991). The will and the ways: Development and validation of an individual-differences measure of hope. Journal of Personality and Social Psychology, 60, 570–585.

58.

Snyder

C. R.

Shorey

H. S.

Cheavens

Pulvers

K. M.

Adams

V. H.

III & Wiklund

(2002). Hope and academic success in college. Journal of Educational Psychology, 94, 820–826.

59.

Spady

W. G.

(1970). Dropouts from higher education: An interdisciplinary review and synthesis. Interchange, 1(1), 64–85.

60.

Spady

W. G.

(1971). Dropouts from higher education: Toward an empirical model. Interchange, 2(3), 38–62.

61.

St. John

E. P.

Simmons

A. B.

& Musoba

G. D.

(2001). Aptitude vs. merit: What matters in persistence. The Review of Higher Education, 24, 131–152.

62.

Steele

C. M.

(1999). A threat in the air: How stereotypes shape intellectual identity. In Lowe

E. Y.

(Ed.), Promise and dilemma: Perspectives on racial diversity and higher education (pp. 116–118). Princeton, NJ: Princeton University Press.

63.

Tabachnick

B. G.

& Fidell

L. S.

(2001). Using multivariate statistics (4th ed.). Boston, MA: Allyn and Bacon.

64.

Tinto

(1993). Leaving college: Rethinking the causes and cures of student attrition. (2nd ed.). Chicago, IL: University of Chicago Press.

65.

Voorhees

R. A.

(1987). Toward building models of community college persistence: A logit analysis. Research in Higher Education, 26, 115–129.

66.

Walsh

(1987). Teaching understanding and interpretation of logit regression. Teaching Sociology, 15, 178–183.

67.

Wild

& Ebbers

(2002). Rethinking student retention in community colleges. Community College Journal of Research and Practice, 26, 503–519.

68.

Wright

(1995). Logistic regression. In Grimm

L. G.

& Yarnold

P. R.

(Eds.), Reading and understanding multivariate statistics (pp. 217–244). Washington, DC: American Psychological Association.

69.

Xitao

& Wang

(1999). Comparing linear discriminant function with logistic regression for the two-group classification problem. Journal of Experimental Education, 67, 265–286.