Advertisement

THE ROLE OF TEACHER CHARACTERISTICS AND PRACTICES ON UPPER SECONDARY SCHOOL STUDENTS’ MATHEMATICS SELF-EFFICACY IN NYANZA PROVINCE OF KENYA: A MULTILEVEL ANALYSIS

  • Joshua Gisemba Bagaka’sEmail author
Article

Abstract

The study identified two dimensions of teacher self-efficacy and practices and five dimensions of students’ mathematics self-efficacy and sought to determine the extent to which teacher characteristics and practices can enhance secondary school students’ self-efficacy. Data were collected from 13,173 students in 193 teachers’ classrooms from 141 schools in the 10 districts of Lake Victoria Region of Kenya. Two-level hierarchical linear model revealed that teachers’ frequent use of mathematics homework, their level of interest and enjoyment of mathematics, as well as their ability and competence in teaching mathematics were found to play a key role in promoting students’ mathematics self-efficacy. Teachers’ ability and competence in teaching were also found to be effective in narrowing the gender gap in students’ self-confidence and competence in mathematics. The study recommends that teacher training colleges emphasize such teacher practices and values in order to enhance students’ mathematics self-efficacy, reduce their level of anxiety and fear of mathematics, and consequently, enhance their achievement in mathematics. Professional development opportunities should also be made available to in-service teachers to continually update their knowledge and skills and develop new strategies for teacher effectiveness.

Key words

mathematics anxiety mathematics self-efficacy multilevel analysis relative competence in mathematics teacher effectiveness 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ackers, J., Migoli, J., & Nzomo, J. (2001). Identifying and addressing the causes of declining participation rates in Kenyan primary schools. International Journal of Educational Development, 21, 361–374.CrossRefGoogle Scholar
  2. Ai, X. (2002). Gender differences in growth in mathematics achievement: Three-level longitudinal and multilevel analyses of individual, home, and school influences. Mathematical Thinking and Learning, 4(1), 1–22.CrossRefGoogle Scholar
  3. Amutabi, M. N. (2003). Political interference in the running of education in post-independence Kenya: A critical retrospection. International Journal of Educational Development, 23, 127–144.CrossRefGoogle Scholar
  4. Ashcraft, M. H. (2002). Math anxiety: Personal, educational, and cognitive consequences. Current Directions in Psychological Science, 11, 181–185.CrossRefGoogle Scholar
  5. Bandura, A. (1986). Social foundations of thought and action. A social cognitive theory. Englewood Cliffs: Prentice Hall.Google Scholar
  6. Betz, N. E. (1989). Implications of the null environment hypothesis for women’s career development and for counseling psychology. The Counseling Psychologist, 17, 136–144.CrossRefGoogle Scholar
  7. Betz, N. E. (1992). Career assessment: A review of critical issues. In S. D. Brown & R. W. Lent (Eds.), Handbook of counseling psychology (2nd ed., pp. 453–484). New York: Wiley.Google Scholar
  8. Githua, B. N., & Mwangi, J. G. (2003). Students’ mathematics self-efficacy and motivation to learn mathematics: Relationship and gender differences among Kenya’s secondary-school students in Nairobi and Rift Valley Provinces. International Journal of Educational Development, 23, 487–499.CrossRefGoogle Scholar
  9. Glewwe, P., Kremer, M., & Moulin, S. (2007, August). Many children left behind? Textbooks and test scores in Kenya. NBER Working Paper No. w13300. Retrieved from SSRN: http://ssrn.com/abstract = 1005902.
  10. Goddard, R. D., & Goddard, Y. L. (2001). A multilevel analysis of the relationship between teacher and collective efficacy in urban schools. Teaching and Teacher Education, 0, 1–12.Google Scholar
  11. Hyde, J. S., Fennema, E., & Lamon, S. J. (1990a). Gender differences in mathematics performance: A meta-analysis. Psychological Bulletin, 107, 139–155.CrossRefGoogle Scholar
  12. Hyde, J. S., Fennema, E., Ryan, M., Frost, L. A., & Hopp, C. (1990b). Gender comparisons of mathematics attitude and affect: A meta-analysis. Psychology of Women Quarterly, 14, 299–324.CrossRefGoogle Scholar
  13. KCSE: Mangu and Starehe shine (2008, February 29). Daily Nation, p. 1.Google Scholar
  14. Kenney-Benson, G. A., Pomerantz, E. M., Ryan, A. M., & Patrick, H. (2006). Sex differences in math performance: The role of children’s approach to schoolwork. Development Psychology, 42(1), 11–26.CrossRefGoogle Scholar
  15. Kimball, M. M. (1989). A new perspective on women’s math achievement. Psychological Bulletin, 105, 198–214.CrossRefGoogle Scholar
  16. King, K. (2007). Balancing basic and post-basic education in Kenya: National versus international policy agendas. International Journal of Educational Development, 27, 358–370.CrossRefGoogle Scholar
  17. Lapan, R. T., Shaughnessy, P., & Boggs, K. (1996). Efficacy expectations and vocational interests between sex and choice of math/science college majors: A longitudinal study. Journal of Vocational Behavior, 49, 277–291.CrossRefGoogle Scholar
  18. Lent, R. W., Lopez, F. G., & Bieschke, K. J. (1993). Predicting mathematics-related choice and success behaviors: Test of an expanded social cognitive model. Journal of Vocational Behavior, 42, 223–236.CrossRefGoogle Scholar
  19. Linn, M. C., & Hyde, J. S. (1989). Gender, mathematics, and science. Educational Researcher, 18(8), 17–27.Google Scholar
  20. Marsh, H. W. (1996). Structure of artistic self-concept for performing arts and non-performing arts students in a performing arts high school: ‘Setting the stage’ with multi-group confirmatory factor analysis. Journal of Educational Psychology, 88(3), 461–477.CrossRefGoogle Scholar
  21. Marx, D. M., & Roman, J. S. (2002). Female role models: Protecting women’s math test performance. Personality and Social Psychology Bulletin, 28, 1183–1193.CrossRefGoogle Scholar
  22. Meece, J. L., Parsons, J. E., Kaczala, C. M., Goff, S. B., & Futterman, R. (1982). Sex differences in math achievement: Towards a model of academic choice. Psychological Bulletin, 91, 324–348.CrossRefGoogle Scholar
  23. Meece, J. L., Wigfield, A., & Eccles, J. S. (1990). Predictors of math anxiety and its influence on young adolescents’ course enrollment intentions and performance in mathematics. Journal of Educational Psychology, 82, 60–70.CrossRefGoogle Scholar
  24. Mwangi, J. G., & McCaslin, N. L. (1994). The motivation of Kenyan’s Rift Valley extension agents. Journal of Agricultural Education, 35(3), 35.CrossRefGoogle Scholar
  25. Ngware, M. W. (2002). Gender participation in technical training institutions: An assessment of the Kenyan case. Eastern Africa Social Science Research Review, XVIII(1), 21–33.CrossRefGoogle Scholar
  26. Pajares, F. (1996). Self-efficacy beliefs and mathematical problem-solving of gifted students. Contemporary Educational Psychology, 21, 325–344.CrossRefGoogle Scholar
  27. Pajares, F., & Graham, L. (1999). Self-efficacy, motivation constructs, and mathematics performance of entering middle school students. Contemporary Educational Psychology, 24, 124–139.CrossRefGoogle Scholar
  28. Raudenbush, S. W., & Bryk, A. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Newbury Park: Sage.Google Scholar
  29. Raudenbush, S. W., Bryk, A. S., Cheong, Y. F., & Congdon, R. (2001). HLM6: Hierarchical linear and nonlinear modeling. Chicago: Scientific International Software International.Google Scholar
  30. Saunders, J., Davis, L., Williams, T., & Williams, J. H. (2004). Gender differences in self-perceptions and academic outcomes: A study of African American high school students. Journal of Youth and Adolescence, 33(1), 81–90.CrossRefGoogle Scholar
  31. Stevens, J. P. (2002). Applied multivariate statistics for the social sciences (4th ed.). Mahwah: Lawrence Erlbaum Associates.Google Scholar
  32. Tabachnick, B. G., & Fidell, L. S. (1996). Using multivariate statistics (3rd ed.). New York: Harper Collins College Publishers.Google Scholar
  33. Western schools make comeback in exam results (2007, December 22). Saturday Nation, p. 3.Google Scholar

Copyright information

© National Science Council, Taiwan 2010

Authors and Affiliations

  1. 1.Cleveland State UniversityClevelandUSA

Personalised recommendations