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EURASIA Journal of Mathematics, Science and Technology Education
Volume 13, Issue 5 (May 2017), pp. 1517-1538

DOI: 10.12973/eurasia.2017.00683a

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Research Article

Published online on Jan 09, 2017

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Influence of Career Motivation on Science Learning in Korean High-School Students

Sein Shin, Jun-Ki Lee, & Minsu Ha


Motivation to learn is an essential element in science learning. In this study, the role of career motivation in science learning was examined. In particular, first, a science motivation model that focused on career motivation was tested. Second, the role of career motivation as a predictor of STEM track choice was examined. Third, the effect of gender and academic year on science motivation was explored. The participants of the study were 626 high-school students. We used the Rasch analysis, structural equation modeling, logistic regression, MANOVA for the statistical analyses. It was found that career motivation has direct influences on several motivational factors in science learning, such as grade motivation, need for learning, self-determination, and self-efficacy. Moreover, career motivation was found to be a predictor of students’ STEM track choice. Finally, there were substantial differences in science motivation across gender and academic years. Generally, females and students in higher academic years exhibited a lower level of science motivation. Female students especially showed a low level of career motivation. The findings suggest that it is important to facilitate students’ career motivations to improve their science motivation and promote long-term scientific achievement.

Keywords: career motivation, gender difference, science motivation, STEM track choice, Korean high-school students

  1. Ahmed, W., van der Werf, G., Kuyper, H., & Minnaert, A. (2013). Emotions, self-regulated learning, and achievement in mathematics: A growth curve analysis. Journal of Educational Psychology, 105(1), 150–161.
  2. Arbona, C. (2000). The development of academic achievement in school aged children: Precursors to career development. In Lent, R. & Brown. S. (Eds.), Handbook of counseling psychology (pp. 270-309). New York: John Wiley.
  3. Anderman, E. M., & Midgley, C. (1997). Changes in achievement goal orientations, perceived academic competence, and grades across the transition to middle-level schools. Contemporary Educational Psychology, 22(3), 269–298.
  4. Balakrishnan, B. & Low, F. S. (2016). Learning Experience and Socio-Cultural Influences on Female Engineering Students’ Perspectives on Engineering Courses and Careers. Minerva, 54(2), 219-239.
  5. Bandura, A. (1986). Social Foundations of Thought and Action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall.
  6. Bandura, A. (1991). Social cognitive theory of self-regulation. Organizational Behavior and Human Decision Process, 50, 248-287.
  7. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.
  8. Bandura, A., Barbaranelli, C., Caprara, G. V., & Pastorelli, C. (2001), Self-efficacy beliefs as shapers of children's aspirations and career trajectories. Child Development, 72, 187–206.
  9. Bandura, A., & Schunk, D. H. (1981). Cultivating competence, self-efficacy, and intrinsic interest through proximal self-motivation. Journal of Personality and Social Psychology, 41, 586–598.
  10. Bong, M. (2004). Classroom culture as a source for the mismatch between Korean students’ performance and motivation. East West Education, 21, 1-18.
  11. Bong, M., Kim, H., Shin, J. H., Lee, S., & Lee, H. (2008). Exploration of socio-cultural factors affecting Korean adolescents’ motivation. Korean Journal of Psychological and Social Issues, 14(1), 319-348.
  12. Boone, W. J., & Scantlebury, K. (2006). The role of Rasch analysis when conducting science education research utilizing multiple-choice tests. Science Education, 90(2), 253–269.
  13. Britner, S. L. (2008), Motivation in high school science students: A comparison of gender differences in life, physical, and earth science classes. Journal of Research in Science Teaching, 45(8), 955–970.
  14. Brophy, J. (2004). Motivating students to learn (2nd ed.). Mahwah, NJ: Erlbaum.
  15. Chang, Y. (2014). Science Motivation Across Asian Countries: Links among Future-Oriented Motivation, Self-Efficacy, Task Values, and Achievement Outcomes. The Asia-Pacific Education Researcher, 24(1), 247–258.
  16. Dabney, K., P., Tai, R. H., Almarode, J. T., Miller-Friedmann, J. L., Sonnert, G., Sadler, P. M., Hazari, Z. (2012). Out-of-School Time Science Activities and Their Association with Career Interest in STEM. International Journal of Science Education, Part B. 2(1).
  17. DeBacker, T. K., & Nelson, R. M. (2000). Motivation to learn science: Differences related to gender, class type, and ability level. Journal of Educational Research, 93(4), 245–254.
  18. de Bilde, J., Vansteenkiste, M., & Lens, W. (2011). Understanding the association between future time perspective and self-regulated learning through the lens of self-determination theory. Learning and Instruction, 21(3), 332–344.
  19. Deci, E., & Ryan, R. (Eds.) (2002). Handbook of Self-Determination Research. Rochester, NY: University of Rochester Press.
  20. DeWitt, J., Archer, L., Osborne, J., Dillon, J., Willis, B., & Wong, B. (2011). High aspirations but low progression: The science aspirations-careers paradox amongst minority ethnic students. International Journal of Science and Mathematics Education, 9(2), 243–271.
  21. De Volder, M. L., & Lens, W. (1982). Academic achievement and future time perspective as a cognitive-motivational concept. Journal of Personality and Social Psychology, 42, 566-571.
  22. Domene, J., Socholotiuk, K., & Woitowicz, L. A. (2011). Academic motivation in post-secondary students. Canadian Journal of Education, 34(1), 99-127.
  23. Elliot, A. J., McGregor, H. A. (2001). A 2 ⅹ 2 Achievement goal framework. Journal of Personality and Social Psychology, 80(3), 501-519.
  24. Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values and goals. Annual Review of Psychology, 53, 109-132.
  25. Eccles, J., Wigfield, A., Harold, R. D., & Blumenfeld, P. (1993). Age and Gender Differences in Children's Self- and Task Perceptions during Elementary School. Child Development, 64(3), 830–847.
  26. Glynn, S. M., Taasoobshirazi, G., & Brickman, P. (2007). Nonscience majors learning science: A theoretical model of motivation. Journal of Research in Science Teaching, 44(8), 1088–1107.
  27. Glynn, S. M., Taasoobshirazi, G., & Brickman, P. (2009). Science motivation questionnaire: Construct validation with nonscience majors. Journal of Research in Science Teaching, 46(2), 127–146.
  28. Glynn, S. M., Brickman, P., Armstrong, N., & Taasoobshirazi, G. (2011). Science Motivation Questionnaire II: Validation with Science Majors and Nonscience Majors. Journal of Research in Science Teaching, 48(10), 1159-1176.
  29. Ha, M., & Lee, J. K., (2012). Exploring variables related to students' understanding of the convergence of basic and applied science. Journal of the Korean Association for Science Education, 32(2), 320-220.
  30. Hirschi, A. (2010). Positive adolescent career development: The role of intrinsic and extrinsic work values. Career Development Quarterly, 58(3), 276-287.
  31. Ho, E. S. C. (2009). Characteristics of East Asian Learners: What We Learned from PISA. Educational Research Journal, 24(2), 327.
  32. Huang, G. H. C & Gove, M. (2015). Confucianism, Chines families, and academic achievement: Exploring how Confucianism and Asian descendant parenting practices influence children’s academic achievement. In Khine, M. S. (Ed.), Science Education in East Asia (pp. 41-66). Retrieved from
  33. Husman, J., & Lens, W. (1999). The role of the future in student motivation. Educational Psychologist, 34, 113-125.
  34. Jacobs, J. E., Lanza, S., Osgood, D. W., Eccles, J. S., & Wigfield, A. (2002), Changes in Children’s Self-Competence and Values: Gender and Domain Differences across Grades One through Twelve. Child Development, 73, 509–527.
  35. Jerrim, J. (2015). Why do East Asian children perform so well in PISA? An investigation of Western-born children of East Asian descent. Oxford Review of Education, 41(3), 310–333.
  36. Keith, T. Z. (1993). Causal influences on school learning. In: H. J. Walberg (Ed.), Analytic methods for educational productivity (pp. 21–47). Greenwich, CT: JAI Press.
  37. Kember, D. (2000). Misconceptions about the learning approaches, motivation and study practices of Asian students. Higher Education, 40(1), 99 – 121.
  38. Kim, S., & Lee, J. H. (2010). Private Tutoring and Demand for Education in South Korea. Economic Development and Cultural Change, 58(2), 259-296.
  39. Kjærnsli, M., & Lie, S. (2011). Students’ preference for science careers: International comparisons based on PISA 2006. International Journal of Science Education, 33(1), 121–144.
  40. Lam, C. C., Ho, E. S. C., & Wong, N. Y. (2002). Parents’ beliefs and practices in education in confucian heritage cultures: The Hong Kong case. Journal of Southeast Asian Education, 3(1), 99-114.
  41. Lee, J. K. (2006). Educational fever and South Korean higher education. Revista Electrónica de Investigación y Educativa, 8 (1). Retrieved May 29, 2016 from:
  42. Leibham, M. B., Alexander, J. M., & Johnson, K. E. (2013), Science Interests in Preschool Boys and Girls: Relations to Later Self-Concept and Science Achievement. Science Education, 97(4), 574–593.
  43. 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.
  44. Lent, R. W., Brown, S. D., & Hackett, G. (2000). Contextual supports and barriers to career choice: A social cognitive analysis. Journal of Counseling Psychology, 47(1), 36-49.
  45. Leung, F. K. S. (2001) In search of an east Asian identity in mathematics education. Educational Studies in Mathematics, 47(1), 35–51.
  46. Marginson, S. (2011). Higher education in East Asia and Singapore: Rise of the Confucian Model. Higher Education, 61(5), 587–611.
  47. Martin, M. O., Mullis, I. V. S., Foy, P., & Stanco, G. M. (2012). TIMSS 2011 International Results in Science. Chestnut Hill, MA: TIMSS & PIRLS International Study Center. Boston College.
  48. Meece, J. L., Glienke, B. B., & Burg, S. (2006). Gender and motivation. Journal of School Psychology, 44(5), 351−373.
  49. Meece, J. L. & Jones, M. G. (1996), Gender differences in motivation and strategy use in science: Are girls rote learners? Journal of Research in Science Teaching, 33(4), 393–406.
  50. Miller, R. B., & Brickman, S. J. (2004). A model of future-oriented motivation and self-regulation. Educational Psychology Review, 16(1), 9–33.
  51. Miller, P. H., Blessing, J. S., & Schwartz, S. (2006). Gender differences in high-school students’ views about science. International Journal of Science Education, 28(4), 363–381.
  52. Ministry of Education. (1997). The school curriculum of the Republic of Korea. Retrieved from
  53. Ministry of Education. (2015a). 2015 Plan for Ministry of Education. Retrieved from
  54. Ministry of Education. (2015b). The 2015 Revised Science Curriculum (Report No. 2015-74). Sejong: Ministry of Education.
  55. Ministry of Education Science and Technology. (2011). The 2009 Revised Science Curriculum (Report No. 2009-41). Seoul: Ministry of Education Science and Technology.
  56. Ministry of Education & Korean Educational Development Institute. (2014). Brief Statistics on Korean Education. Seoul, Korea.
  57. Murayama, K., Pekrun, R., Lichtenfeld, S. & vom Hofe, R. (2013). Predicting Long-Term Growth in Students' Mathematics Achievement: The Unique Contributions of Motivation and Cognitive Strategies. Child Development, 84(4), 1475–1490.
  58. Myeong, J. O., & Crawley, F. E. (1993), Predicting and understanding Korean high school students' science-track choice: Testing the theory of reasoned action by structural equation modeling. Journal of Research in Science Teaching, 30(4), 381–400.
  59. Nauta, M. M., Kahn, J. H., Angell, J. W., & Cantarelli, E. A. (2002). Identifying the antecedent in the relation between career interests and self-efficacy: Is is one, the other, or both? Journal of Counseling Psychology, 49(3), 290-301.
  60. Neumann, I., Neumann, K., & Nehm, R. H. (2011). Evaluating instrument quality in science education: Rasch based analyses of a nature of science test. International Journal of Science Education, 33, 1373–1405.
  61. Orthner, D. K., Akos, P., Rose, R., Jones-Sanpei, H., Mercado, M., & Woolley, M. E. (2010). CareerStart: A Middle School Student Engagement and Academic Achievement Program. Children Schools, 32(4), 223-234.
  62. Pajars, F. (2007). Culturealizing educational psychology. In Farideh, S. & Rumjahn, H. (Eds.), Culture, Motivation and Learning (pp. 19-42). Retrieved from
  63. Park, H. (2008). Test of Group invariance for the structural model among motivation, self-concept and student achievement: Using PISA 2006 data. Journal of Educational Evaluation, 21(3), 43-67.
  64. Pintrich, P. R. (2003). A Motivational Science Perspective on the Role of Student Motivation in Learning and Teaching Contexts. Journal of Educational Psychology, 95(4), 667–686.
  65. Riegle-Crumb, C., Moore, C., & Ramos-Wada, A. (2011). Who wants to have a career in science or math? exploring adolescents’ future aspirations by gender and race/ethnicity. Science Education, 95(3), 458–476.
  66. Ryan, R. M., & Deci, E. L. (2000) Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25, 54–67.
  67. Schneider, B., & Lee, Y. (1990). A model for academic success: The school and home environment of East Asian students. Anthropology & Education Quarterly, 21(4), 358-377.
  68. Schunk, D.H., Pintrich, P.R., & Meece, J.L. (2008). Motivation in education: Theory, research and applications. 3rd ed. Upper Saddle River, NJ: Pearson.
  69. Seth, M. J. (2002). Education fever: society, politics, and the pursuit of schooling in South Korea. University of Hawaii Press, Honolulu.
  70. Shin, J., Lee, H., McCarthy-Donovan, A., Hwang, H., Yim, S., & Seo, E. (2015). Home and Motivational Factors Related to Science-Career Pursuit: Gender differences and gender similarities. International Journal of Science Education, 37(9), 1478-1503.
  71. Simons, J., Dewitte, S., & Lens, W. (2004). The role of different types of instrumentality in motivation, study strategies, and performance: know why you learn, so you’ll know what you learn! The British Journal of Educational Psychology, 74(3), 343–60.
  72. Simpkins, S. D., Price, C. D. & Garcia, K. (2015), Parental support and high school students' motivation in biology, chemistry, and physics: Understanding differences among latino and caucasian boys and girls. Journal of Research in Science Teaching, 52(10), 1386–1407.
  73. Skaalvik, E. M., Federici, R. A., & Klassen, R. M. (2015). Mathematics achievement and self-efficacy: Relations with motivation for mathematics. International Journal of Educational Research, 72, 129-136.
  74. Stuckey, M., Hofstein, A., Mamlok-Naaman, R., & Eliks, I. (2013) The meaning of ‘relevance’ in science education and its implications for the science curriculum. Studies in Science Education, 49(1), 1-34.
  75. Sweet, R., Nissinen, K., & Vuorinen, R. (2014). An analysis of the career development items in PISA 2012 and of their relationship to the characteristics of countries, schools, students and families. Jyväskylä, Finland: University of Jyväskylä. ELGPN Research Paper, No. 1. Retrieved from
  76. Sweet, S. N., Fortier, M. S., Strachan, S. M., & Blanchard, C. M. (2012). Testing and integrating self-determination theory and self-efficacy theory in a physical activity context. Canadian Psychology/Psychologie Canadienne, 53(4), 319–327.
  77. Tabachnick, S. E., Miller, R. B., & Relyea, G. E. (2008). The relationships among students’ future-oriented goals and subgoals, perceived task instrumentality, and task-oriented self-regulation strategies in an academic environment. Journal of Educational Psychology, 100(3), 629–642.
  78. Tai, R. H., Qi Liu, C., Maltese, A. V, & Fan, X. (2006). Career choice. Planning early for careers in science. Science (New York, N.Y.), 312(5777), 1143–1144.
  79. Tracey, T. J. G. (2002). Development of interests and competency beliefs: A 1-year longitudinal study of fifth- to eighth-grade students using the ICA–R and structural equation modeling. Journal of Counseling Psychology, 49, 148–163.
  80. Vedder-Weiss, D., & Fortus, D. (2012), Adolescents' declining motivation to learn science: A follow-up study. Journal of Research in Science Teaching, 49(9), 1057–1095.
  81. Walberg, H. J., & Tsai, S. L. (1983). Matthew effects in education. American Educational Research Journal, 20(3), 359-373.
  82. Wang, M.-T., Eccles, J. S., & Kenny, S. (2013). Not Lack of Ability but More Choice: Individual and Gender Differences in Choice of Careers in Science, Technology, Engineering, and Mathematics. Psychological Science, 24(5), 770–775.
  83. Wang, T. L., & Berlin, D. (2010). Construction and validation of an instrument to measure Taiwanese elementary students’ attitudes toward their science class. International Journal of Science Education, 32(18), 2413-2428.
  84. Wang, X. (2013). Why Students Choose STEM Majors: Motivation, High School Learning, and Postsecondary Context of Support. American Educational Research Journal, 50(5), 1081–1121.
  85. Woolley, M. E., Rose, R. a., Orthner, D. K., Akos, P. T., & Jones-Sanpei, H. (2013). Advancing Academic Achievement Through Career Relevance in the Middle Grades: A Longitudinal Evaluation of CareerStart. American Educational Research Journal, 50(6), 1309–1335.
  86. Wright, B. D., & Linacre, J. M. (1994). Reasonable mean-square fit values. Rasch. Measurement Transactions, 8(3), 370.
  87. Zhu, Y., & Leung, F. K. S. (2011). Motivation and achievement: Is there an East Asian model? International Journal of Science and Mathematics Education, 9(5), 1189–1212.
  88. Zimmerman, B. J. (2000). Self-Efficacy: An essential motive to learn. Contemporary Educational Psychology, 25, 82–91.