Research in Higher Education

, Volume 54, Issue 8, pp 851–873 | Cite as

Women in STEM Majors and Professional Outcome Expectations: The Role of Living-Learning Programs and Other College Environments

  • Katalin Szelényi
  • Nida Denson
  • Karen Kurotsuchi Inkelas
Article

Abstract

Using data from the 2004–2007 National Study of Living Learning Programs, the only national dataset offering longitudinal information on outcomes associated with living-learning (L/L) program participation, this study investigated the role of L/L programs and other college environments in the professional outcome expectations of women in science, technology, engineering, and mathematics (STEM) majors. Specifically, we examined an overall measure of professional outcome expectations, along with participants’ anticipation of the chances that they will “get a good job in their field,” “achieve success in their career,” and “combine a professional career with having a balanced personal life.” Findings indicated that attending a coeducational STEM L/L program and discussing academic and career issues with peers were positively related with three of the outcome measures. Additional findings spoke to the importance of self-efficacy and interactions with diverse peers in the development of professional outcome expectations among women in STEM. Implications are presented for higher education institutions’ efforts to support coeducational and women-only STEM-related L/L programs, peer and faculty interactions, and diverse peer interactions.

Keywords

Women in STEM Career development Living learning programs Quantitative 

References

  1. Allen, C. (1999). WISER women: Fostering undergraduate success in science and engineering with a residential academic program. Journal of Women and Minorities in Science and Engineering, 5, 265–277.Google Scholar
  2. Appel, A. (2012). A passion for science without barriers. Nature, 481, 13.CrossRefGoogle Scholar
  3. Astin, A. W. (1993). What matters in college? Four critical years revisited. San Francisco, CA: Jossey-Bass.Google Scholar
  4. Astin, A. W., & Astin, H. S. (1992). Undergraduate science education: The impact of different college environments on the educational pipeline in the sciences. Los Angeles: Higher Education Research Institute, UCLA.Google Scholar
  5. Astin, A. W., & Denson, N. (2009). Multi-campus studies of college impact: Which statistical method is appropriate? Research in Higher Education, 50, 354–367.CrossRefGoogle Scholar
  6. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  7. Beede, D., Julian, T., Langdon, D., McKittrick, G., Khan, B., & Doms, M. (2011). Women in STEM: A gender gap to innovation. Retrieved April 17, 2013 from http://www.esa.doc.gov/sites/default/files/reports/documents/womeninstemagaptoinnovation8311.pdf.
  8. Betz, N. (2006). Basic issues and concepts in the career development and counseling of women. In W. B. Walsh & M. Heppner (Eds.), Handbook of career counseling for women. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  9. Betz, N. E., & Hackett, G. (2006). Career self-efficacy theory: Back to the future. Journal of Career Assessment, 14(3), 3–12.CrossRefGoogle Scholar
  10. Brower, A. M., & Inkelas, K. K. (2010). Living-learning: One high-impact educational practice we now know a lot about. Liberal Education, 96(2), 36–43.Google Scholar
  11. Buck, G. A., Plano Clark, V. L., Leslie-Pelecky, D., Lu, Y., & Cerda-Lizarraga, P. (2008). Examining the cognitive processes used by adolescent girls and women scientists in identifying science role models: A feminist approach. Science Education, 92(4), 688–707.CrossRefGoogle Scholar
  12. Buday, S. K., Stake, J. E., & Peterson, Z. D. (2012). Gender and the choice of a science career: The impact of social support and possible selves. Sex Roles, 66, 197–209.CrossRefGoogle Scholar
  13. Cech, E., Rubineau, B., Silbey, S., & Seron, C. (2011). Professional role confidence and gendered persistence in engineering. American Sociological Review, 76(5), 641–666.CrossRefGoogle Scholar
  14. Chang, M. J., Astin, A. W., & Kim, D. (2004). Cross-racial interaction among undergraduates: Some causes and consequences. Research in Higher Education, 45(5), 529–553.CrossRefGoogle Scholar
  15. Chang, M. J., Denson, N., Saenz, V., & Misa, K. (2006). The educational benefits of cross-racial interaction among undergraduates. Journal of Higher Education, 77(3), 430–455.CrossRefGoogle Scholar
  16. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  17. Colbeck, C. L., Cabrera, A. F., & Terenzini, P. T. (2001). Learning professional confidence: Linking teaching practices, students’ self-perceptions, and gender. The Review of Higher Education, 24(2), 173–191.CrossRefGoogle Scholar
  18. Denson, N., & Chang, M. J. (2009). Racial diversity matters: The impact of diversity-related student engagement and institutional context. American Educational Research Journal, 46, 322–353.CrossRefGoogle Scholar
  19. Diegelman, N. M., & Mezydlo Subich, L. (2001). Academic and vocational interests as a function of outcome expectancies in social cognitive career theory. Journal of Vocational Behavior, 59, 394–405.CrossRefGoogle Scholar
  20. Diekman, A. B., Brown, E. R., Johnston, A. M., & Clark, E. K. (2010). Seeking congruity between roles and goals: A new look at why women opt out of science, technology, engineering, and mathematics careers. Psychological Science, 21(8), 1051–1057.CrossRefGoogle Scholar
  21. Ethington, C. A., Thomas, S. L., & Pike, G. R. (2002). Back to the basics: Regression as it should be. In J. C. Smart & W. G. Tierney (Eds.), Higher education: Handbook of theory and research (Vol. 17). New York: Agathon.Google Scholar
  22. Farmer, H. S., Wardrop, J. L., Anderson, M. Z., & Risinger, R. (1995). Women’s career choices: Focus on math, science, and technology careers. Journal of Counseling Psychology, 42(2), 155–170.CrossRefGoogle Scholar
  23. Farmer, H. S., Wardrop, J. L., & Rotella, S. C. (1999). Antecedent factors differentiating women and men in science/nonscience careers. Psychology of Women Quarterly, 23, 763–780.CrossRefGoogle Scholar
  24. Fox, M. F., Sonnert, G., & Nikiforova, I. (2009). Successful programs for undergraduate women in science and engineering: Adapting versus adopting the institutional environment. Research in Higher Education, 50, 333–353.CrossRefGoogle Scholar
  25. Goulden, M., Frasch, K., & Mason, M. A. (2009). Staying competitive: Patching Americas leaky pipeline in the sciences. Berkeley, CA and Washington, DC: The University of California, Berkeley and The Center for American Progress.Google Scholar
  26. Hathaway, R. S., Sharp, S., & Davis, C.-S. (2001). Programmatic efforts affect retention of women in science and engineering. Journal of Women and Minorities in Science and Engineering, 7, 107–124.Google Scholar
  27. Inkelas, K. K. (2011). Living-learning programs for women in STEM. In J. Gaston-Gayles (Ed.), Attracting and retaining women in STEM: New directions for institutional research. Tallahassee, FL: Association for Institutional Research.Google Scholar
  28. Inkelas, K. K., & Associates. (2008). The National Study of Living-Learning Programs: 2007 Report of findings. Retrieved June 15, 2012 from http://drum.lib.umd.edu/bitstream/1903/8392/1/2007%20NSLLP%20Final%20Report.pdf.
  29. Inkelas, K. K., Daver, Z., Vogt, K., & Brown Leonard, J. (2007). Living-learning programs and first-generation college students’ academic and social transition to college. Research in Higher Education, 48(4), 403–434.CrossRefGoogle Scholar
  30. Inkelas, K. K., & Weisman, J. L. (2003). Different by design: An examination of outcomes associated with three types of living-learning programs. Journal of College Student Development, 44, 335–368. CrossRefGoogle Scholar
  31. Johnson, D., Soldner, M., & Inkelas, K. K. (2006, June). Facilitating success for women in STEM through living-learning programs. White Paper prepared for the National Conference of the Women in Engineering Programs and Advocates Network, Pittsburgh, PA. Google Scholar
  32. Kahveci, A., Southerland, S. A., & Gilmer, P. J. (2008). From marginality to legitimate peripherality: Understanding the essential functions of a women’s program. Science Education, 92(1), 33–64.CrossRefGoogle Scholar
  33. Lent, R. W., Brown, S. D., & Hackett, G. (1994). Toward a unifying social cognitive theory of career and academic interest, choice, and performance. Journal of Vocational Behavior, 45(1), 79–122.CrossRefGoogle Scholar
  34. Lent, R. W., Brown, S. D., & Hackett, G. (2000). Contextual barriers and supports to career choice: A social cognitive analysis. Journal of Counseling Psychology, 47(1), 36–49.CrossRefGoogle Scholar
  35. Lent, R. W., Brown, S. D., & Hackett, G. (2002). Social cognitive career theory. In D. Brown & Associates (Eds.), Career choice and development (4th ed., pp. 255–311). San Francisco, CA: Jossey-Bass.Google Scholar
  36. Lent, R. W., Brown, S. D., Sheu, H., Schmidt, J., Brenner, B. R., Gloster, C. S., et al. (2005). Social cognitive predictors of academic interests and goals in engineering: Utility for women and students at historically Black universities. Journal of Counseling Psychology, 52(1), 84–92.CrossRefGoogle Scholar
  37. Lent, R. W., Lopez, A. M., Lopez, F. G., & Sheu, H.-B. (2008). Social cognitive career theory and the prediction of interests and choice goals in the computing disciplines. Journal of Vocational Behavior, 73(1), 52–62.CrossRefGoogle Scholar
  38. National Science and Technology Council Subcommittee on Social, Behavioral and Economic Sciences. (2009, January). Social, behavioral, and economic research in the federal context. Retrieved April 17, 2013 from http://www.nsf.gov/sbe/prospectus_v10_3_17_09.pdf.
  39. National Science Foundation. (2011). Women, minorities, and persons with disabilities in science and engineering: 2011. Special Report NSF 11-309. Arlington, VA: National Science Foundation.Google Scholar
  40. National Science Foundation. (2013, January). What we do. Retrieved April 17, 2013 from http://www.nsf.gov/about/what.jsp.
  41. Pryor, J. H., DeAngelo, L., Palucki Blake, L., Hurtado, S., & Tran, S. (2011). The American freshman: National norms fall 2011. Los Angeles: Higher Education Research Institute, UCLA.Google Scholar
  42. Rayman, P., & Brett, B. (1995). Women science majors: What makes a difference in persistence after graduation? Journal of Higher Education, 66(4), 388–414.CrossRefGoogle Scholar
  43. Sax, L. J. (1994). Retaining tomorrow’s scientists: Exploring the factors that keep male and female science majors interested in science careers. Journal of Women and Minorities in Science and Engineering, 1, 45–61.Google Scholar
  44. Sax, L. J. (2001). Undergraduate science majors: Gender differences in who goes to graduate school. The Review of Higher Education, 24(2), 153–172.CrossRefGoogle Scholar
  45. Sax, L. J., & Bryant, A. N. (2006). The impact of college on sex-atypical career choices of women and men. Journal of Vocational Behavior, 68, 52–63.CrossRefGoogle Scholar
  46. Seymour, E., & Hewitt, N. M. (1997). Talking about leaving: Why undergraduates leave the sciences. Boulder, CO: Westview Press.Google Scholar
  47. Soldner, M., Rowan-Kenyon, H., Inkelas, K. K., Garvey, J., & Robbins, C. (2012). Supporting students’ intentions to persist in STEM disciplines: The role of living-learning programs among other social–cognitive factors. The Journal of Higher Education, 83(3), 311–336. CrossRefGoogle Scholar
  48. Szelényi, K., & Inkelas, K. K. (2011). The role of living-learning programs in women’s plans to attend graduate school in STEM fields. Research in Higher Education, 52(4), 349–369.CrossRefGoogle Scholar
  49. Tidball, M. E., Smith, D. G., Tidball, C. S., & Wolf-Wendel, L. E. (1999). Taking women seriously: Lessons and legacies for educating the majority. Phoenix, AZ: The American Council on Education and The Oryx Press.Google Scholar
  50. Xie, Y., & Shauman, K. A. (2003). Women in science: Career processes and outcomes. Cambridge, MA: Harvard University Press.Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Katalin Szelényi
    • 1
  • Nida Denson
    • 2
  • Karen Kurotsuchi Inkelas
    • 3
  1. 1.Department of Leadership in EducationUniversity of Massachusetts BostonBostonUSA
  2. 2.University of Western SydneySydneyAustralia
  3. 3.University of VirginiaCharlottesvilleUSA

Personalised recommendations