Journal of Science Education and Technology

, Volume 18, Issue 2, pp 163–172 | Cite as

A Cross-Sectional Study of Engineering Students’ Self-Efficacy by Gender, Ethnicity, Year, and Transfer Status

Article

Abstract

This is a cross-sectional study of 519 undergraduate engineering majors’ self-efficacy beliefs at a large, research extensive, Midwestern university. Engineering self-efficacy is an individual’s belief in his or her ability to successfully negotiate the academic hurdles of the engineering program. Engineering self-efficacy was obtained from four variables: self-efficacy 1, self-efficacy 2, engineering career outcome expectations, and coping self-efficacy. The four variables were analyzed using a repeated analysis of variance among levels of gender, ethnicity, years students had been enrolled in their engineering program, and transfer status. No significant differences in mean engineering self-efficacy scores were found by gender, ethnicity, and transfer status. However, significant interactions between gender and the subscales, ethnicity and the subscales, and transfer status and the subscales were found. Significant differences in mean engineering self-efficacy scores were found among years students had been enrolled in the program.

Keywords

Engineering Self-efficacy Gender Ethnicity Transfer 

References

  1. Adelman C (1998) Women and men of the engineering path: a model for analysis of undergraduate careers. U.S. Department of Education and the National Institute for Science Education, Washington, DCGoogle Scholar
  2. Bandura A (1986) Social foundations of thought and action: a social cognitive theory. Prentice-Hall, Englewood CliffsGoogle Scholar
  3. Bandura A (1997) Self-efficacy: the exercise of control. Freeman, New YorkGoogle Scholar
  4. Betz N, Hackett G (1981) The relationship of career-related self-efficacy expectations to perceived career options in college women and men. J Couns Psychol 28(5):399–410. doi: 10.1037/0022-0167.28.5.399 CrossRefGoogle Scholar
  5. Bradburn EM (1995) Engineering gender roles: a self-efficacy model of occupational choice and persistence. Cornell U, US, 1Google Scholar
  6. Brainard S, Carlin L (1998) A six-year longitudinal study of undergraduate women in engineering and science. J Eng Educ 87:369–375Google Scholar
  7. Britner SL, Pajares F (2006) Sources of science self-efficacy beliefs of middle school students. J Res Sci Teach 43:485–499. doi: 10.1002/tea.20131 CrossRefGoogle Scholar
  8. Concannon J, Barrow L (2008) A cross-sectional study of engineering self-efficacy. Proceedings of the 2008 annual meeting of the american society of engineering education and exposition, 24 June 2008 (AC 2008-148). ASEE, PittsburgGoogle Scholar
  9. Goodman Research Group, Inc. (2002) A comprehensive evaluation in engineering programs. Retrieved on 5 July 2007, from http://www.grginc.com
  10. Hackett G, Betz NE (1989) An exploration of the mathematics self-efficacy/mathematics performance correspondence. J Res Math Educ 20:261–273. doi: 10.2307/749515 CrossRefGoogle Scholar
  11. Hackett G, Betz NE, Casas J, Rocha-Singh IA (1992) Gender, ethnicity, and social cognitive factors predicting the academic achievement of students in engineering. J Couns Psychol 39:527–538. doi: 10.1037/0022-0167.39.4.527 CrossRefGoogle Scholar
  12. Johnson D, Stone D, Philliips T (2008) Relations among ethnicity, gender, beliefs, attitudes, and intention to pursue a career in information technology. J Appl Psychol 38:999–1022. doi: 10.1111/j.1559-1816.2008.00336.x CrossRefGoogle Scholar
  13. Lapan RT, Boggs KR, Morrill WH (1989) Self-efficacy as a mediator of investigative and realistic general occupation themes on the Strong-Campbell interest inventory. J Couns Psychol 36:176–182. doi: 10.1037/0022-0167.36.2.176 CrossRefGoogle Scholar
  14. Lent R, Brown SD, Larkin K (1986) Self-efficacy in the prediction of academic performance and perceived career options. J Couns Psychol 33(3):265–269. doi: 10.1037/0022-0167.33.3.265 CrossRefGoogle Scholar
  15. Lent R, Brown S, Larkin K (1987) Comparison of three theoretically derived variables in predicting career and academic behavior: self-efficacy, interest congruence, and consequence thinking. J Couns Psychol 34(3):293–298. doi: 10.1037/0022-0167.34.3.293 CrossRefGoogle Scholar
  16. Lent RW, Brown SD, Hackett G (2000) Contextual supports and barriers to career choice: a social cognitive analysis. J Couns Psychol 34:293–298. doi: 10.1037/0022-0167.34.3.293 CrossRefGoogle Scholar
  17. Lent RW, Sheu H, Schmidt J, Brenner B, Brown S, Gloster C, Schmidt L, Lyons H, Treistman D (2005) Social cognitive predictors of academic interests and goals in engineering: utility for women and students at historically black universities. J Couns Psychol 52:84–92. doi: 10.1037/0022-0167.52.1.84 CrossRefGoogle Scholar
  18. Lent RW, Singley D, Sheu H, Schmidt J, Schmidt L (2007) Relation of social-cognitive factors to academic satisfaction in engineering students. J Career Assess 15:87–97. doi: 10.1177/1069072706294518 CrossRefGoogle Scholar
  19. Lin T, Cheng Y (2007) The influence of teaching with situated learning rationale on 7th graders’ learning in biology. Proceeding of the national association of research in science teaching conference, New OrleansGoogle Scholar
  20. Marra R, Bogue B (2006) Women engineering students self efficacy: a longitudinal multi-institution study. Proceedings of the 2006 women in engineering programs and advocates network conference, PittsburghGoogle Scholar
  21. Mau WC (2003) Factors that influence persistence in science and engineering career aspirations. Career Dev Q 51:234–243Google Scholar
  22. National Science Board (2007) Moving forward to improve engineering education (NSB Publication No. 07-122). Retrieved on-line 19 December 2007 from http://www.nsf.gove/nsb
  23. National Science Foundation (1998) Women, minorities, and persons with disabilities in science and engineering. National Science Foundation, ArlingtonGoogle Scholar
  24. National Science Foundation (2003) Women, minorities, and persons with disabilities in science and engineering. National Science Foundation, ArlingtonGoogle Scholar
  25. National Science Foundation (2007) Science, technology, engineering, and mathematics talent expansion program (STEP) (NSF Publication No. 07–570). National Science Foundation, ArlingtonGoogle Scholar
  26. Office of the University Registrar (2007) Enrollment statistics. Retrieved on 1 June 2007 from http://registrar.missouri.edu
  27. Schaefers KG, Epperson DL, Mauta MM (1997) Women’s career development: can theoretically derived variables predict persistence in engineering majors? J Couns Psychol 44:173–183. doi: 10.1037/0022-0167.44.2.173 CrossRefGoogle Scholar
  28. Seymour E (1995) Guest comment: why undergraduates leave the sciences. Am J Phys 63:199–202. doi: 10.1119/1.17954 CrossRefGoogle Scholar
  29. Seymour E, Hewitt N (1997) Talking about leaving: why undergraduates leave the sciences. Westview Press, BoulderGoogle Scholar
  30. Vogt C (2003) An account of women’s progress in engineering: a social cognitive perspective. J Women Minor Sci Eng 9:217–238. doi: 10.1615/JWomenMinorScienEng.v9.i34.20 CrossRefGoogle Scholar
  31. Weiten W, Lloyd MA (2006) Psychology applied to modern life. Thomson Wadsworth, BelmontGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Westminster CollegeFultonUSA
  2. 2.University of MissouriColumbiaUSA

Personalised recommendations