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THE DIFFERENCES IN SCORES AND SELF-EFFICACY BY STUDENT GENDER IN MATHEMATICS AND SCIENCE

  • Rachel A. Louis
  • Jean M. Mistele
Article

ABSTRACT

Typically, mathematics and science are seen as linked together, where both subjects involve numbers, critical thinking, and problem solving. Our study aims to develop a better understanding of the connections between student’s achievement scores in mathematics and science, student gender, and self-efficacy. We used the Trends in International Mathematics and Science Study 2007 eighth grade data to answer our research questions and were able to demonstrate that when controlling for self-efficacy, there is a statistically significant difference in the achievement scores between males and females by subject, where females score higher Algebra, but males score higher in the other mathematics subjects. Likewise, we were also able to demonstrate that there is a statistically significant difference in the achievement scores in Earth Science, Physics, and Biology, between males and females where males score higher in science subjects. In both mathematics and science examinations, we controlled for self-efficacy where in mathematics females hold lower self-efficacy then males and in science there is no difference between females and males in terms of self-efficacy. We conjecture that mathematics and science classrooms that consider self-efficacy may impact student’s achievement scores by subject, which can ultimately impact career choices in mathematics- and science-based fields.

KEY WORDS

achievement scores differences by gender self-efficacy subject differences TIMSS 2007 

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References

  1. Anyon, J. (1980). Social class and the hidden curriculum of work. Journal of Education, 162(1), 67–92.Google Scholar
  2. Baker, F. B. (2001). The basics of item response theory. ERIC Clearinghouse on Assessment and evaluation (2nd ed). Retrieved from http://info.worldbank.org/etools/docs/library/117765/Item%20Response%20Theory%20-%20 F%20Baker.pdf
  3. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
  4. Bandura, A. (1994). Self-efficacy. In V. S. Ramachandran (Ed.), Encyclopedia of human behavior (Vol. 4, pp. 71–81). New York: Academic Press.Google Scholar
  5. 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(1), 187–206.CrossRefGoogle Scholar
  6. Beaton, A., Tougas, F., Rinfret, N., Huard, N. & Delisle, M. N. (2007). Strength in numbers? Women and mathematics. European Journal of Psychology of Education, 22(3), 291–306.CrossRefGoogle Scholar
  7. Beller, M. & Gafini, N. (1996). The 1991 international assessment of educational progress in mathematics and science: The gender differences perspective. Journal of Educational Psychology, 88, 365–377. doi: 10.1037/0022-0663.88.2.365.CrossRefGoogle Scholar
  8. Britner, S. I. & Pajares, F. (2006). Sources of science self-efficacy beliefs of middle school students. Journal of Research in Science Teaching, 43(5), 485–499. doi: 10.1002/tea.20131.CrossRefGoogle Scholar
  9. Brown, A. S., & Brown, L. L. (2007). What are science & math test scores really telling U.S.? The Bent of Tau Beta Pi, Winter, 13–1. Retrieved from http://www.tbp.org/pages/publications/Bent/Features/W07Brown.pdf
  10. Brush, L. R. (1985). Cognitive and affective determinants of course preferences and plans. In S. F. Chipman, L. R. Brush & D. M. Wilson (Eds.), Women and mathematics balancing the equation (pp. 123–150). Hillsdale, NJ: Erlbaum.Google Scholar
  11. Chen, P. & Zimmerman, B. (2007). A cross-national comparison study on the accuracy of self-efficacy beliefs of middle-school mathematics students. The Journal of Experimental Education, 75(3), 221–244.CrossRefGoogle Scholar
  12. Chiu, M. M. (2009). Inequalities' harmful effects on both disadvantaged and privileged students: Sources, mechanisms, and strategies. Journal of Educational Research, 3(1/2), 109–127.Google Scholar
  13. Foy, P. & Olson, J. F. (2009). TIMSS 2007 international database and user guide. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.Google Scholar
  14. Frenzel, A. C., Pekrun, R. & Goetz, T. (2007). Girls and mathematics—a hopeless issue? A control-value approach to gender differences in emotions towards mathematics. European Journal of Psychology of Education, 22(4), 497–514.CrossRefGoogle Scholar
  15. Greenwood, J. (1984). Soundoff: My anxieties about math anxiety. Mathematics Teacher, 77(9), 662–663.Google Scholar
  16. Grusec, J. E. (1992). Social learning theory and developmental psychology: The legacies of Robert Sears and Albert Bandura. Developmental Psychology, 28(5), 776–786. doi: 10.1037/0012-1649.28.5.776.CrossRefGoogle Scholar
  17. Holliday, W. G. & Holliday, B. W. (2003). Why using international comparative math and science achievement data from TIMSS is not helpful. The Educational Forum, 67(3), 250–257.CrossRefGoogle Scholar
  18. Hyde, J. S., Fennema, E., Ryan, M., Fros, L. A. & Hopp, C. (1990). Gender comparisons of mathematics attitudes and affect. Psychology of Women Quarterly, 14(3), 299–324.CrossRefGoogle Scholar
  19. Hyde, J. S. & Mertz, J. E. (2009). Gender, culture, and mathematics performance. Proceedings of the National Academy of Sciences of the United States of America, 106(22), 8801–8807. doi: 10.1073/pnas.0901265106.CrossRefGoogle Scholar
  20. Katz, S., Allbritton, D., Aronis, J., Wilson, C. & Soffia, M. L. (2006). Gender, achievement and persistence in an undergraduate computer science program. The Database for Advances in Information Systems, 37(4), 42–57.CrossRefGoogle Scholar
  21. Keith, T. Z. (2006). Multiple regression and beyond. Boston, MA: Pearson.Google Scholar
  22. Ma, X. (1999). A meta-analysis of the relationship between anxiety toward mathematics and achievement in mathematics. Journal for Research in Mathematics Education, 30(5), 520–540.CrossRefGoogle Scholar
  23. Ma, X. & Cartwright, F. (2003). A longitudinal analysis of gender difference in affective outcomes in mathematics during middle and high school. School Effectiveness and School Improvement, 14(4), 413–439.CrossRefGoogle Scholar
  24. Merrill, C. & Daugherty, J. (2010). Stem education and leadership: A mathematics and science partnership approach. Journal of Teaching Education, 21(2), 21–34.Google Scholar
  25. Olson, J. F., Martin, M. O. & Mullis, I. V. S. (2008). TIMSS 2007 technical report. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.Google Scholar
  26. Pajares, F., Britner, S. & Valiante, G. (2000). Relation between achievement goals and self-beliefs of middle school students in writing and science. Contemporary Educational Psychology, 25(4), 406–422. doi: 10.1006/ceps.1999.1027.CrossRefGoogle Scholar
  27. Pajares, F. & Valiante, G. (1999). Grade level and gender differences in the writing self-beliefs of middle school students. Contemporary Educational Psychology, 24(4), 390–405.CrossRefGoogle Scholar
  28. Rutherford, F. J. (1997). Thinking quantitatively about science. In L. A. Steen (Ed.), Why numbers count (pp. 60–74). New York: The College Entrance Board.Google Scholar
  29. Satake, E. & Amato, P. P. (1995). Mathematics anxiety and achievement among Japanese elementary school students. Educational and Psychological Measurement, 55(6), 1000–1007. doi: 10.1177/0013164495055006009.CrossRefGoogle Scholar
  30. Skaalvik, E. M. & Skaalvik, S. (2006). Self-concept and self-efficacy in mathematics: Relation with mathematics motivation and achievement. Proceedings from ICLS ’06 International Conference on Learning Sciences.Google Scholar
  31. Stuart, V. (2000). Math curse or math anxiety? Teaching Children Mathematics, 6(5), 330–335.Google Scholar
  32. Taasoobshirazi, G. & Carr, M. (2008). Gender differences in science: An expertise perspective. Education Psychology Review, 20(2), 149–169.CrossRefGoogle Scholar
  33. The President’s Council of Advisors on Science and Technology (2011). K–12 science, technology, engineering, and math (STEM) education for America’s future. Tech Directions, 70(6), 33–34.Google Scholar
  34. Usher, E. (2009). Sources of middle school students’ self-efficacy in mathematics: A qualitative investigation. American Educational Research Journal, 46(1), 275–314.CrossRefGoogle Scholar
  35. Usher, E. & Pajares, F. (2009). Sources of self-efficacy in mathematics: A validation study. Contemporary Educational Psychology, 34, 89–101.CrossRefGoogle Scholar
  36. Wang, J. (2001). TIMSS primary and middle school data: Some technical concerns. Educational Researcher, 30(6), 17–21. doi: 10.3102/0013189X030006017.CrossRefGoogle Scholar
  37. Wilkins, J. L. M. (2004). Mathematics and science self-concept: An international investigation. The Journal of Experimental Education, 72(4), 331–346.CrossRefGoogle Scholar
  38. Zakaria, E. & Nordin, M. N. (2008). The effects of mathematics anxiety on matriculation students as related to motivation and achievement. Eurasia Journal of Mathematics, Science & Technology Education, 4(1), 27–30.Google Scholar
  39. Zeldin, A. L., Britner, S. L. & Pajares, F. (2008). A comparative study of the self-efficacy beliefs of successful men and women in mathematics, science, and technology careers. Journal of Research in Science Teaching, 45(9), 1036–1058. doi: 10.1002/tea.20195.CrossRefGoogle Scholar

Copyright information

© National Science Council, Taiwan 2011

Authors and Affiliations

  1. 1.Department of Engineering EducationVirginia TechBlacksburgUSA
  2. 2.Department of Mathematics EducationVirginia TechBlacksburgUSA

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