Advertisement

The career exploration outcome expectations scale- Turkish: Adaptation and validation

  • Serkan V. SariEmail author
  • Fatih Camadan
Article
  • 11 Downloads

Abstract

This study was conducted to investigate the validity evidence of an adapted scale that was originally developed in a different culture to assess middle school students’ career exploration outcome expectations. The adaptation and validation process included five steps: (a) translation (b) confirmatory factor analysis, (c) measurement invariance studies, (d) calculation of Pearson correlation coefficient between the adapted scale scores and relevant scale scores and (e) calculation of internal consistency. The study sample included 944 middle school students. It was concluded that there is enough evidence to claim that the adapted scale has sufficient language, construct, and concurrent validity. There was also sufficient evidence to claim strong measurement invariance by gender. The internal consistency coefficient of the scale was acceptable (alpha = 0.79). The theoretical and managerial implications of the study were discussed in detail.

Keywords

Career exploration Outcome expectations Adaptation Validation 

Notes

Acknowledgements

We would like to thank Dr. Burak Aydın, our colleague at Recep Tayyip Erdogan University. He provided supervision on how to utilize the programming language R to carry out factor analysis and measurement-invariance analysis.

Compliance with Ethical Standards

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.

Conflict of Interest

Serkan V. Sari declares that there is no conflict of interest and Fatih Camadan declares that there is no conflict of interest.

References

  1. Akin, A., & Akkaya, O. (2015). The validity and reliability study for the Turkish version of the social efficacy and social outcome expectations scale. Bartin University Journal of Faculty of Education, 4(1), 204–213.  https://doi.org/10.14686/BUEFAD.2015111025.CrossRefGoogle Scholar
  2. Bacanlı, F. (2006). Career search self-efficacy scale: Validity and reliability studies. Educational Sciences: Theory & Practice, 6(2), 301–330.Google Scholar
  3. Bandura, A. (1986). The explanatory and predictive scope of self-efficacy theory. Journal of Social and Clinical Psychology, 4(3), 359–373.  https://doi.org/10.1521/jscp.1986.4.3.359.CrossRefGoogle Scholar
  4. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman.Google Scholar
  5. Betz, N. E., & Luzzo, D. A. (1996). Career assessment and the career decision-making self efficacy scale. Journal of Career Assessment, 4(4), 413–428.  https://doi.org/10.1177/106907279600400405.CrossRefGoogle Scholar
  6. Betz, N. E., & Voyten, K. (1997). Efficacy and outcome expectations influence career exploration and decidedness. The Career Development Quarterly, 46(2), 179–189.  https://doi.org/10.1002/j.2161-0045.1997.tb01004.x.CrossRefGoogle Scholar
  7. Betz, N. E., Klein, K. L., & Taylor, K. M. (1996). Evaluation of a short form of the career decision-making self-efficacy scale. Journal of Career Assessment, 4(1), 47–57.  https://doi.org/10.1177/106907279600400103.CrossRefGoogle Scholar
  8. Betz, N. E., Hammond, M. S., & Multon, K. D. (2005). Reliability and validity of five-level response continua for the career decision self-efficacy scale. Journal of Career Assessment, 13(2), 131–149.  https://doi.org/10.1177/1069072704273123.CrossRefGoogle Scholar
  9. Bozgeyikli, H. (2004). Development of career decision-making self-efficacy scale. Journal of Institute of Social Sciences, 11, 221–234.Google Scholar
  10. Chou, M. J., & Lee, H. C. (2013). The differences and stability of children’s career expectations. American Journal of Applied Sciences, 10(6), 615–623.  https://doi.org/10.3844/ajassp.2013.615.623.CrossRefGoogle Scholar
  11. Cohen, L., Manion, L., & Morrison, K. (2013). Research methods in education (5th ed.). New York, London: Routledge Falmer.CrossRefGoogle Scholar
  12. Cupani, M., Minzi, M. C., Perez, R., & Pautassi, R. M. (2010). An assessment of a social cognitive model of academic performance in mathematics in Argentinean middle school students. Learning and Individual Differences, 20(6), 659–663.  https://doi.org/10.1016/j.lindif.2010.03.006.CrossRefGoogle Scholar
  13. Desharnais, R., Bouillon, J., & Godin, G. (1986). Self-efficacy and outcome expectations as determinants of exercise adherence. Psychological Reports, 59(3), 1155–1159.  https://doi.org/10.2466/pr0.1986.59.3.1155.CrossRefGoogle Scholar
  14. Duffy, R. D., & Lent, R. W. (2008). Relation of religious support to career decision self-efficacy in college students. Journal of Career Assessment, 16(3), 360–369.  https://doi.org/10.1177/1069072708317382.CrossRefGoogle Scholar
  15. Ekinci, N. (2017). Pre-service teachers’ motivational factors affecting their teaching profession and field choices. Elementary Education Online, 16(2), 394–405.Google Scholar
  16. Ferry, T. R., Fouad, N. A., & Smith, P. L. (2000). The role of family context in a social cognitive model for career-related choice behavior: A math and science perspective. Journal of Vocational Behavior, 57(3), 348–364.  https://doi.org/10.1006/jvbe.1999.1743.CrossRefGoogle Scholar
  17. Fouad, N. A., & Guillen, A. (2006). Outcome expectations: Looking to the past and potential future. Journal of Career Assessment, 14(1), 130–142.  https://doi.org/10.1177/1069072705281370.CrossRefGoogle Scholar
  18. Fouad, N. A., Smith, P. L., & Enochs, L. (1997). Reliability and validity evidence for the middle school self-efficacy scale. Measurement and Evaluation in Counseling and Development, 30(1), 17–31.Google Scholar
  19. Godding, P. R., & Glasgow, R. E. (1985). Self-efficacy and outcome expectations as predictors of controlled smoking status. Cognitive Therapy and Research, 9(5), 583–590.CrossRefGoogle Scholar
  20. Gushue, G. V. (2006). The relationship of ethnic identity, career decision-making self-efficacy and outcome expectations among Latino/a high school students. Journal of Vocational Behavior, 68(1), 85–95.  https://doi.org/10.1016/j.jvb.2005.03.002.CrossRefGoogle Scholar
  21. Hazari, Z., Sonnert, G., Sadler, P. M., & Shanahan, M. C. (2010). Connecting high school physics experiences, outcome expectations, physics identity, and physics career choice: A gender study. Journal of Research in Science Teaching, 47(8), 978–1003.  https://doi.org/10.1002/tea.20363.CrossRefGoogle Scholar
  22. Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55.  https://doi.org/10.1080/10705519909540118.CrossRefGoogle Scholar
  23. Işık, E. (2010). Effects of a social cognitive career theory-based group intervention on career decision self efficacy and vocational outcome expectations among undergraduate students. Doctoral Thesis. Cukurova University, Turkey.Google Scholar
  24. Kenny, M. E., Blustein, D. L., Chaves, A., Grossman, J. M., & Gallagher, L. A. (2003). The role of perceived barriers and relational support in the educational and vocational lives of urban high school students. Journal of Counseling Psychology, 50(2), 142–155.  https://doi.org/10.1037/0022-0167.50.2.142.CrossRefGoogle Scholar
  25. Kline, R. B. (2011). Principles and practice of structural equation modeling. New York: The Guilford Press.Google Scholar
  26. Lent, R. W. (2013). Career-life preparedness: Revisiting career planning and adjustment in the new workplace. The Career Development Quarterly, 61(1), 2–14.Google Scholar
  27. Lent, R. W., & Brown, S. D. (2006). On conceptualizing and assessing social cognitive constructs in career research: A measurement guide. Journal of Career Assessment, 14(1), 12–35.  https://doi.org/10.1177/1069072705281364.CrossRefGoogle Scholar
  28. Lent, R. W., Sheu, H. B., Singley, D., Schmidt, J. A., Schmidt, L. C., & Gloster, C. S. (2008). Longitudinal relations of self-efficacy to outcome expectations, interests, and major choice goals in engineering students. Journal of Vocational Behavior, 73(2), 328–335.  https://doi.org/10.1016/j.jvb.2008.07.005.CrossRefGoogle Scholar
  29. McWhirter, E. H., Crothers, M., & Rasheed, S. (2000). The effects of high school career education on social–cognitive variables. Journal of Counseling Psychology, 47(3), 330–341.  https://doi.org/10.1037/0022-0167.47.3.330.CrossRefGoogle Scholar
  30. Metheny, J., McWhirter, E. H., & O'Neil, M. E. (2008). Measuring perceived teacher support and its influence on adolescent career development. Journal of Career Assessment, 16(2), 218–237.  https://doi.org/10.1177/1069072707313198.CrossRefGoogle Scholar
  31. Millsap, R. E., & Yun-Tein, J. (2004). Assessing factorial invariance in ordered-categorical measures. Multivariate Behavioral Research, 39, 479–515.CrossRefGoogle Scholar
  32. Muthén, L. K., & Muthén, B. O. (1998-2015). Mplus user’s guide (7th ed.). Los Angeles: Muthén & Muthén.Google Scholar
  33. Niles, S. P., & Harris-Bowlsbey, J. E. (2013). Career development interventions in the 21st century (4th edn). Boston: Pearson Education Limited.Google Scholar
  34. Noack, P., Kracke, B., Gniewosz, B., & Dietrich, J. (2010). Parental and school effects on students’ occupational exploration: A longitudinal and multilevel analysis. Journal of Vocational Behavior, 77(1), 50–57.  https://doi.org/10.1016/j.jvb.2010.02.006.CrossRefGoogle Scholar
  35. Oliveira, Í. M., Taveira, M. D. C., Cadime, I., & Porfeli, E. J. (2016). Psychometric properties of a career exploratory outcome expectations measure. Journal of Career Assessment, 24(2), 380–396.CrossRefGoogle Scholar
  36. Özyürek, R., & Atıcı, M. K. (2002). Determining sources which are effective in university students’ career decision making. Turkish Psychological Counseling and Guidance Journal, 2(17), 33–42.Google Scholar
  37. Patton, W. A., & Porfeli, E. J. (2007). Career exploration for children and adolescents. In V. Skorikov & W. A. Patton (Eds.), Career development in childhood and adolescence. Rotterdam: Sense Publishers.Google Scholar
  38. Porfeli, E. J., Wang, C., & Hartung, P. J. (2008). Family transmission of work affectivity and experiences to children. Journal of Vocational Behavior, 73(2), 278–286.  https://doi.org/10.1016/j.jvb.2008.06.001.CrossRefGoogle Scholar
  39. Porfeli, E. J., Lee, B., & Weigold, I. K. (2012). A multidimensional measure of work valences. Journal of Vocational Behavior, 80(2), 340–350.  https://doi.org/10.1016/j.jvb.2011.09.004.CrossRefGoogle Scholar
  40. R Core Team. (2016). R: A language and environment for statistical computing. Vieanna: R Foundation for Statistical Computing.Google Scholar
  41. Rasheed, A. S., McWhirter, E. H., & Chronister, K. M. (2005). Self-efficacy and vocational outcome expectations for adolescents of lower socioeconomic status: A pilot study. Journal of Career Assessment, 13(1), 40–58.  https://doi.org/10.1177/1069072704270273.CrossRefGoogle Scholar
  42. Robbins, S. B. (1985). Validity estimates for the career decision-making self-efficacy scale. Measurement and Evaluation in Counseling and Development, 18(2), 64–71.CrossRefGoogle Scholar
  43. Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48, 1–36. http://lavaan.ugent.be/. Accessed 21 Apr 2017.CrossRefGoogle Scholar
  44. Sarı, S.V. (2014). The effect of social-cognitive learning theory based group intervention on the students’ career search self efficacy. Doctoral Thesis. Karadeniz Technical University, Turkey.Google Scholar
  45. Sarıkaya, T., & Khorshid, L. (2009). Examining the factors affecting the selection of the university students: The choice of the profession of university students. Journal of Turkish Educational Sciences, 7(2), 393–423.Google Scholar
  46. Satorra, A., & Bentler, P. M. (2010). Ensuring postiveness of the scaled difference chi-square test statistic. Psychometrika, 75(2), 243–248.CrossRefGoogle Scholar
  47. semTools Contributors (2016). semTools: Useful tools for structural equation modeling. R package version 0.4-14. Retrieved http://cran.r-project.org/package=semTools.
  48. Solberg, V. S., Good, G. E., Nord, D., Holm, C., Hohner, R., Zima, N., Heffernan, M., & Malen, A. (1994). Assessing career search expectations: Development and validation of the career search efficacy scale. Journal of Career Assessment, 2(2), 111–123.  https://doi.org/10.1177/106907279400200202.CrossRefGoogle Scholar
  49. Sousa, V. D., & Rojjanasrirat, W. (2011). Translation, adaptation and validation of instruments or scales for use in cross-cultural health care research: A clear and user-friendly guideline. Journal of Evaluation in Clinical Practice, 17(2), 268–274.  https://doi.org/10.1111/j.1365-2753.2010.01434.x.CrossRefPubMedGoogle Scholar
  50. Stumpf, C. A., Colarelli, S. M., & Hartman, K. (1983). Development of the Career Exploration Survey (CES). Journal of Vocational Behavior, 22(2), 191–226.  https://doi.org/10.1016/0001-8791(83)90028-3.CrossRefGoogle Scholar
  51. Super, D. E. (1980). A life-span, life-space approach to career development. Journal of Vocational Behavior, 16(3), 282–298.  https://doi.org/10.1016/0001-8791(80)90056-1.CrossRefGoogle Scholar
  52. Swanson, J. L., & Gore, P. A. (2000). Advances in vocational psychology theory and research. In S. D. Brown & R. W. Lent (Eds.), Handbook of counseling psychology (3rd ed., pp. 233–269). Hoboken: Wiley.Google Scholar
  53. Taveira, M. D. C., & Moreno, M. L. R. (2003). Guidance theory and practice: The status of career exploration. British Journal of Guidance and Counselling, 31(2), 189–208.  https://doi.org/10.1080/0306988031000102360.CrossRefGoogle Scholar
  54. Tekkaya, C., Çakıroglu, J., & Özkan, Ö. (2002). Turkish preservice science teachers’ understanding of science, self efficacy beliefs and attitudes toward science teaching. New Orleans: NARST 2002 (National Association for Research in Science Teaching).Google Scholar
  55. Tippmann, S. (2015). Programming tools: Adventures with R: A guide to the popular, free statistics and visualization software that gives scientists control of their own data analysis. Nature, 7532, 109.Google Scholar
  56. Tracey, T. J., Lent, R. W., Brown, S. D., Soresi, S., & Nota, L. (2006). Adherence to RIASEC structure in relation to career exploration and parenting style: Longitudinal and idiothetic considerations. Journal of Vocational Behavior, 69, 248–261.  https://doi.org/10.1016/j.jvb.2006.02.001.CrossRefGoogle Scholar
  57. Tunç, G. Ç., Akansel, N., & Özdemir, A. (2010). Factors affecting career choices of nursing and health officer program students. Maltepe University Nursing Science and Art Review, 3(1), 24–31.Google Scholar
  58. Wu, A. D., Li, Z., & Zumbo, B. D. (2007). Decoding the meaning of factorial invariance and updating the practice of multi-group confirmatory factor analysis: A demonstration with TIMSS data. Practical Assessment, Research and Evaluation, 12(3), 1–26.Google Scholar
  59. Zunker, V.G. (2002). Career counseling: Applied concepts of life planning. Wadsworth Group, Brooks, Cole.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Psychological Counseling and GuidanceRecep Tayyip Erdogan UniversityRizeTurkey

Personalised recommendations