Advertisement

The Mathematical Education of Primary Teachers

  • Maria Teresa TattoEmail author
Chapter

Abstract

This chapter reports the results of a cross-national study designed to examine the mathematics knowledge and the mathematical pedagogical content knowledge attained by prospective primary teachers at the end of their formal preparation and before they begin to teach. The study used survey methods to collect data from nationally representative samples of pre-service university-based teacher education programs and their future teachers in Botswana, Chile, Chinese Taipei, Germany, Malaysia, the Philippines, Poland, Russia, Singapore, Spain, Switzerland, Thailand, and the United States. Descriptive and multivariate analyses show that future teachers’ individual characteristics, such as levels of achievement in previous schooling, programs’ selection policies, and opportunities to learn the content and the pedagogy of the mathematics school curriculum, were associated with higher levels of knowledge and dispositions toward teaching and learning mathematics. Results support teacher education policies directed at (a) raising the level of subject knowledge required for program selection and graduation and (b) increasing the level of complexity and cognitive demand of the opportunities to learn mathematics and mathematics pedagogy offered to future primary mathematics teachers.

References

  1. AERA, APA, & NCME. (2014). Standards for educational and psychological testing. Washington, DC: American Educational Research Association.Google Scholar
  2. Akiba, M., LeTendre, G. K., & Scribner, J. P. (2007). Teacher quality, opportunity gap, and national achievement in 46 countries. Educational Researcher, 36, 369–387.CrossRefGoogle Scholar
  3. An, S., Kulm, G., & Wu, Z. (2004). The pedagogical content knowledge of middle school mathematics teachers in China and the U.S. Journal of Mathematics Teacher Education, 7, 145–172.CrossRefGoogle Scholar
  4. Ball, D. L. (1990a). The mathematical understandings that prospective teachers bring to teacher education. The Elementary School Journal, 90, 449–466.CrossRefGoogle Scholar
  5. Ball, D. L. (1990b). Prospective elementary and secondary teachers’ understanding of division. Journal for Research in Mathematics Education, 21, 132–144.CrossRefGoogle Scholar
  6. Ball, D. L. (1991). Research on teaching mathematics: Making subject matter part of the equation. In J. Brophy (Ed.), Advances in research on teaching (Vol. 2, pp. 1–48). Greenwich, CT: JAI Press.Google Scholar
  7. Ball, D. L. (Chair). (2003). Mathematical proficiency for all students: Toward a strategic research and development program in mathematics education, RAND mathematics study panel. Washington, DC: U.S. Department of Education’s Office of Educational Research and Improvement. Retrieved from http://www.rand.org/pubs/research_briefs/RB8023/index1.html
  8. Ball, D. L., & Bass, H. (2000). Interweaving content and pedagogy in teaching and learning to teach: Knowing and using mathematics. In J. Boaler (Ed.), Multiple perspectives on the teaching and learning of mathematics (pp. 83–104). Westport, CT: Ablex.Google Scholar
  9. Ball, D. L., Lubienski, S., & Mewborn, D. (2001). Research on teaching mathematics: The unsolved problem of teachers’ mathematical knowledge. In V. Richardson (Ed.), Handbook of research on teaching (4th ed.). New York, NY: Macmillan.Google Scholar
  10. Baumert, J., Kunter, M., Blum, W., Brunner, M., Voss, T., Jordan, A., … Tsai, Y.-M. (2010). Teachers’ mathematical knowledge, cognitive activation in the classroom, and student progress. American Educational Research Journal, 47(1), 133–180.CrossRefGoogle Scholar
  11. Begle, E. G. (1979). Critical variables in mathematics education: Findings from a survey of empirical literature. Washington, DC: Mathematics Association of America and the National Council of Teachers of Mathematics.Google Scholar
  12. Blomeke, S., Suhl, U., Kaiser, G., & Dohrmann, M. (2012). Family background, entry selectivity and opportunities to learn: What matters in primary teacher education? An international comparison of fifteen countries. Teaching and Teacher Education, 20(1), 44–55.CrossRefGoogle Scholar
  13. Boaler, J. (2016). Mathematical mindsets. San Francisco, CA: Jossey-Bass.Google Scholar
  14. Boero, P., Dapueto, C., & Parenti, L. (1996). Didactics of mathematics and the professional knowledge of teachers. In A. J. Bishop, M. A. Clements, C. Keitel, J. Patrick, & F. K. S. Leung (Eds.), International handbook of mathematics education (pp. 1097–1122). Dordrecht, The Netherlands: Kluwer.Google Scholar
  15. Bollen, K. A. (1989). A new incremental fit index for general structural equation models. Sociological Methods Research, 17, 303–316.CrossRefGoogle Scholar
  16. Boyd, D., Grossman, P., Hammerness, K., Lankford, H., Loeb, S., McDonald, M., … Wyckoff, J. (2008). Surveying the landscape of teacher education in New York City: Constrained variation and the challenge of innovation. Educational Evaluation and Policy Analysis, 30, 319–343.CrossRefGoogle Scholar
  17. Boyd, D. J., Grossman, P. L., Lankford, H., Loeb, S., & Wycoff, J. (2009). Teacher preparation and student achievement. Educational Evaluation and Policy Analysis, 31(4), 416–440.CrossRefGoogle Scholar
  18. Brese, F., & Tatto, M. T. (Eds.). (2012). User guide for the TEDS-M international database. Amsterdam, The Netherlands: International Association for the Evaluation of Educational Achievement (IEA).Google Scholar
  19. Cochran-Smith, M., & Zeichner, K. (Eds.). (2015). Studying teacher education: The report of the AERA panel on research and teacher education. Mahweh, NJ: Lawrence Erlbaum Publishers.Google Scholar
  20. CCSS (Common Core State Standards). (2016). Key shifts in mathematics. Retrieved from http://www.corestandards.org/other-resources/keyshifts-in-mathematics
  21. Clements, M. A., Bishop, A. J., Keitel, C., Kilpatrick, J., & Leung, F. K. S. (2013). Third international handbook of mathematics education. New York, NY: Springer.CrossRefGoogle Scholar
  22. Coggshall, J. G., Bivona, L., & Reschly, D. J. (2012). Evaluating the effectiveness of teacher preparation program to support accountability. National Comprehensive Center for Teacher Quality. Retrieved from http://files.eric.ed.gov/fulltext/ED543773.pdf
  23. Comiti, C., & Ball, D. L. (1996). Preparing teachers to teach mathematics: A comparative perspective. In A. J. Bishop et al. (Eds.), International handbook of mathematics education (pp. 1123–1153). Dordrecht, The Netherlands: Kluwer.Google Scholar
  24. Conference Board of the Mathematical Sciences (CBMS). (2012). The mathematical education of teachers II. Providence, RI/Washington, DC: American Mathematical Society/Mathematical Association of America. Retrieved from http://cbmsweb.org/MET2/CrossRefGoogle Scholar
  25. Constantine, J., Player, D., Silva, T., Hallgren, K., Grider, M., & Deke, J. (2009). An evaluation of teachers trained through different routes to certification. Retrieved from http://www.mathematica-mpr.com/publications/pdfs/Education/teacherstrained09.pdf
  26. Darling-Hammond, L. (2000). Teacher quality and student achievement: A review of state policy evidence. Educational Policy Analysis Archives, 8, 1.CrossRefGoogle Scholar
  27. Darling-Hammond, L. (2006). Powerful teacher education: Lessons from exemplary programs. San Francisco, CA: Jossey-Bass.Google Scholar
  28. De Ayala, R. J. (2009). The theory and practice of item response theory. New York, NY: The Guilford Press.Google Scholar
  29. DeCorte, E., Op’t Eynde, P., & Verschaffel, L. (2002). Knowing what to believe: The relevance of students’ mathematical beliefs for mathematics education. In B. K. Hofer & P. R. Pintrich (Eds.), Personal epistemology: The psychology of beliefs about knowledge and knowing (pp. 297–320). Mahwah, NJ: Erlbaum Associates.Google Scholar
  30. Delaney, S. (2012). A validation study of the use of mathematical knowledge for teaching measures in Ireland. ZDM, 44(3), 427–441.CrossRefGoogle Scholar
  31. Delaney, S. F., Ball, D. L., Hill, H. C., Schilling, S. G., & Zopf, D. A. (2008). Adapting U.S. measures of “mathematical knowledge for teaching” for use in Ireland. Journal of Mathematics Teacher Education, 11, 171–197.CrossRefGoogle Scholar
  32. Delors, J. (1996). Learning, the treasure within. Report of the international commission on education for the twenty-first century. Paris, France: UNESCO.Google Scholar
  33. Deng, Z. (1995). Estimating the reliability of the teacher questionnaire used in the Teacher Education and Learning to Teach (TELT). (National Center for Research on teacher learning technical series, 95, 1). Retrieved from http://ncrtl.msu.edu/HTTP/TSeries/TS%2095-1.pdf
  34. Develay, M. (1998). Didactique et pédagogie. In J. C. Ruano-Borbalan (Ed.), Éduquer et former. Paris, France: Éditions Sciences Humaines.Google Scholar
  35. Even, R., & Ball D. L. (Eds.). (2009). The professional education and development of teachers of mathematics: The 15th ICMI Study (New ICMI study series, Vol. 11). New York, NY: Springer.Google Scholar
  36. Even, R., & Tirosh, D. (2002). Teacher knowledge and understanding of students’ mathematical learning. In L. English (Ed.), Handbook of international research in mathematics education (pp. 219–240). Mahwah, NJ: Laurence Erlbaum.Google Scholar
  37. Fennema, E., & Franke, M. L. (1992). Teachers’ knowledge and its impact. In D. A. Grouws (Ed.), Handbook of research on mathematics teaching and learning (pp. 147–164). New York, NY: Macmillan.Google Scholar
  38. Floden, R. (2002). The measurement of opportunity to learn. In A. C. Porter & A. Gamoran (Eds.), Methodological advances in cross-national surveys of educational achievement (pp. 231–266). Washington, DC: National Academy Press.Google Scholar
  39. Ginsburg, A. S. L., Anstrom, T., & Pollock, E. (2005). What the United States can learn from Singapore’s world-class mathematics system. Washington, DC: American Institutes for Research.Google Scholar
  40. Greenwald, R., Hedges, L. V., & Laine, R. D. (1996). The effect of school resources on student achievement. Review of Educational Research, 66, 361–396.CrossRefGoogle Scholar
  41. Grigutsch, S., Raatz, U., & Törner, G. (1998). Einstellungen gegenüber Mathematik bei Mathematiklehrern (mathematics teachers’ epistemological beliefs about the nature of mathematics). Journal für Mathematik-Didaktik (Journal of Mathematics Education), 19, 3–45.CrossRefGoogle Scholar
  42. Grossman, P., & McDonald, M. (2008). Back to the future: Directions for research in teaching and teacher education. American Educational Research Journal, 45(1), 184–205.CrossRefGoogle Scholar
  43. Grouws, D. A. (Ed.). (1992). Handbook of research on mathematics teaching and learning: A project of the National Council of teachers of mathematics. New York, NY: MacMillan.Google Scholar
  44. Hammer, D., & Elby, A. (2002). On the form of a personal epistemology. In B. K. Hofer & P. R. Pintrich (Eds.), Personal epistemologies: The psychology of beliefs about knowledge and knowing (pp. 169–190). Mahwah, NJ: Erlbaum Associates.Google Scholar
  45. Henry, G. T., Bastian, K. C., & Smith, A. A. (2012). Scholarships to recruit the “best and brightest” into teaching: Who is recruited, where do they teach, how effective are they, and how long do they stay? Educational Researcher, 41(3), 83–92.CrossRefGoogle Scholar
  46. Hiebert, J., Gallimore, R., Garnier, H., Givvin, K. B., Hollingsworth, H., Jacobs, J., et al. (2003). Teaching mathematics in seven countries: Results from the TIMSS 1999 video study (NCES 2003–013). Washington, DC: U.S. Department of Education.Google Scholar
  47. Hiebert, J., & Grouws, D. A. (2007). The effects of classroom mathematics teaching on students’ learning. In F. K. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 371–404). Charlotte, NC: Information Age Publishing.Google Scholar
  48. Hill, H., & Ball, D. L. (2009). The curious––and crucial––Case of mathematical knowledge for teaching. Phi Delta Kappan, 91(2), 68–71.CrossRefGoogle Scholar
  49. Hill, H., Sleep, C. L., Lewis, J. M., & Ball, D. L. (2007). Assessing teachers’ mathematical knowledge: What matters and what evidence counts? In F. K. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 111–155). Charlotte, NC: Information Age.Google Scholar
  50. Hill, H. C. (2007). Mathematical knowledge of middle school teachers: Implications for the no child left behind policy initiative. Educational Evaluation and Policy Analysis, 29, 95–114.CrossRefGoogle Scholar
  51. Hill, H. C., Rowan, B., & Ball, D. L. (2005). Effects of teachers’ mathematical knowledge for teaching on student achievement. American Educational Research Journal, 42(2), 371–406.CrossRefGoogle Scholar
  52. Hu, L.-T., & Bentler, P. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55.CrossRefGoogle Scholar
  53. Husen, T. (Ed.). (1967). International study of achievement in mathematics: A comparison of twelve countries (Vol. 1). New York, NY: Wiley.Google Scholar
  54. Ingvarson, L., Beavis, A., Danielson, C., Ellis, L., & Elliott, A. (2005). An evaluation of the Bachelor of Learning Management at Central Queensland University. Canberra, Australia: Australian Government Department of Education, Science and Technology.Google Scholar
  55. Ingvarson, L., Beavis, A., & Kleinhenz, E. (2007). Factors affecting the impact of teacher education courses on teacher preparedness: Implications for accreditation policy. European Journal of Teacher Education, 30(4), 351–381.CrossRefGoogle Scholar
  56. Kennedy, M. (2016). Parsing the practice of teaching. Journal of Teacher Education, 67(1), 6–17.CrossRefGoogle Scholar
  57. Kilpatrick, J., & Swafford, J. (Eds.). (2002). Helping children learn mathematics. Washington, DC: National Academy Press. Retrieved from www.nap.edu/books/0309084318/htmlGoogle Scholar
  58. Kilpatrick, J., Swafford, J., & Findell, B. (Eds.). (2001). Adding it up: Helping children learn mathematics. Washington, DC: National Academy Press.Google Scholar
  59. Lappan, G. (2000). A vision of learning to teach for the 21st century. School Science and Mathematics, 100(6), 319–326.CrossRefGoogle Scholar
  60. Lortie, D. (1975). Schoolteacher: A sociological study. Chicago, IL: University of Chicago Press.Google Scholar
  61. Luschei, T. F. (2011). In search of good teachers: Patterns of teacher quality in two Mexican states. Comparative Education Review, 56, 69–97.CrossRefGoogle Scholar
  62. Ma, L. (1999). Knowing and teaching elementary mathematics: Teachers’ understanding of fundamental mathematics in China and the United States. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  63. Marsh, H. W., Balla, J. R., & McDonald, R. P. (1988). Goodness-of-fit indices in confirmatory factor analysis: The effect of sample size. Psychological Bulletin, 102, 391–410.CrossRefGoogle Scholar
  64. Martin, M. O., & Mullis, I. V. S. (2008). Ensuring comparative validity: Quality control in IEA studies. Retrieved from http://www.iea.nl/fileadmin/user_upload/General_Assembly/49th_GA/GA49_ensuring_comparative_validity.pdf
  65. McDonnell, L. M. (1995). Opportunity to learn as a research concept and a policy instrument. Educational Evaluation and Policy Analysis, 17(3), 305–322.CrossRefGoogle Scholar
  66. Mewborn, D., & Tyminski, A. (2006). Lortie’s apprenticeship of observation revisited. For the Learning of Mathematics, 26(3), 30–32.Google Scholar
  67. Mewborn, D. S., & Stinson, D. W. (2007). Learning to teach as assisted performance. Teachers College Record, 109, 1457–1487.Google Scholar
  68. Meyer, J. P. (2011). jMetrik (version 2.1) [computer software]. Charlottesville, VA: University of Virginia. Retrieved from http://www.itemanalysis.com
  69. Monk, D. H. (1994). Subject area preparation of secondary mathematics and science teachers and student achievement. Economics of Education Review, 13(2), 125–145.CrossRefGoogle Scholar
  70. Mullens, J. E., Murnane, R. J., & Willett, J. B. (1996). The contribution of training and subject matter knowledge to teaching effectiveness: A multilevel analysis of longitudinal evidence from Belize. Comparative Education Review, 40(2), 139–157.CrossRefGoogle Scholar
  71. Mullis, I. V. S., Martin, M. O., Foy, P., & Arora, A. (2012). TIMSS 2011 international results in mathematics. Chestnut Hill, MA: TIMSS and PIRLS International Study Center, Boston College.Google Scholar
  72. National Center for Analysis of Longitudinal Data in Education Research. (2012). CALDER conversations, topic 1: Evaluating teacher training programs [online discussion]. Washington, DC: Author. Retrieved from http://www.caldercenter.org/calder-conversations-tpps.cfm
  73. National Commission on Mathematics and Science Teaching for the 21st Century. (2000). Before it’s too late: A report to the nation. Retrieved from http://www.ed.gov/americacounts/glenn/toc.html
  74. National Mathematics Advisory Panel. (2008). Foundations for success: The final report of the National Mathematics Advisory Panel. Washington, DC: U.S. Department of Education.Google Scholar
  75. National Science Board (2004). A statement of the national science board: In support of the math and science partnership program at the national science foundation. Retrieved from http://www.nsf.gov/nsb/documents/2004/nsb_msp_statement2.pdf
  76. NCTM. (2014). Principles to actions: Ensuring mathematical success for all. Reston, VA: NCTM.Google Scholar
  77. NRC (National Research Council). (2010). Preparing teachers: Building evidence for sound policy. Washington, DC: The National Academies Press.Google Scholar
  78. Op ’T Eynde, P., De Corte, E., & Verschaffel, L. (2002). Framing students’ mathematics related beliefs: A quest for conceptual clarity and a comprehensive categorization. In G. Leder, E. Pehkonen, & G. Törner (Eds.), Beliefs: A hidden variable in mathematics education (pp. 13–38). Boston, MA: Kluwer Academic Publishing.CrossRefGoogle Scholar
  79. Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Newbury Park, CA: Sage.Google Scholar
  80. Raudenbush, S.W., Bryk, A. S, & Congdon, R. (2004). HLM 6 for Windows [Computer software]. Lincolnwood, IL: Scientific Software International, Inc.Google Scholar
  81. Reckase, M. D., McCrory, R., Floden, R. E., Ferrini-Mundy, J., & Senk, S. L. (2015). A multidimensional assessment of teachers’ knowledge of algebra for teaching: Developing an instrument and supporting valid inferences. Educational Assessment, 20(4), 249–267.CrossRefGoogle Scholar
  82. Sahlberg, P. (2007). Education policies for raising student learning: The Finnish approach. Journal of Education Policy, 22(2), 147–171.CrossRefGoogle Scholar
  83. Sahlberg, P. (2010). The secret to Finland’s success: Educating teachers. Stanford: Stanford Center for Opportunity Policy in Education. Research Brief. Retrieved from http://edpolicy.stanford.eduGoogle Scholar
  84. Santibañez, L. M. (2002). Why we should care if teachers get A’s: Impact on student achievement in Mexico. Unpublished doctoral dissertation, Stanford University School of Education, Stanford.Google Scholar
  85. Schilling, S. G., & Hill, H. C. (2007). Assessing measures of mathematical knowledge for teaching: A validity argument approach. Measurement: Interdisciplinary Research and Perspectives, 5(2–3), 70–80.Google Scholar
  86. Schmidt, W., Blömeke, S., & Tatto, M. T. (2011). Teacher education matters. A study of middle school mathematics teacher preparation in six countries. New York, NY: Teachers College Press.Google Scholar
  87. Shulman, L. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 57(1), 1–22.CrossRefGoogle Scholar
  88. Simon, M. A., & Blume, G. W. (1994). Building and understanding multiplicative relationships: A study of prospective elementary teachers. Journal for Research in Mathematics Education, 25, 472–494.CrossRefGoogle Scholar
  89. Staub, F. C., & Stern, E. (2002). The nature of teachers’ pedagogical content beliefs matters for students’ achievement gains: Quasi-experimental evidence from elementary mathematics. Journal of Educational Psychology, 94(2), 344–355.CrossRefGoogle Scholar
  90. Stigler, J. W., Gallimore, R., & Hiebert, J. (2000). Using video surveys to compare classrooms and teaching across cultures: Examples and lessons from the TIMSS and TIMSS-R video studies. Educational Psychologist, 35, 87–100.CrossRefGoogle Scholar
  91. Stigler, J. W., & Hiebert, J. (1997). Understanding and improving classroom mathematics instruction: An overview of the TIMSS video study. Phi Delta Kappan, 79(1), 14–21.Google Scholar
  92. Tatto, M. T. (1996). Examining values and beliefs about teaching diverse students: Understanding the challenges for teacher education. Educational Evaluation and Policy Analysis, 18, 155–180.CrossRefGoogle Scholar
  93. Tatto, M. T. (1998). The influence of teacher education on teachers’ beliefs about purposes of education, roles and practice. Journal of Teacher Education, 49, 66–77.CrossRefGoogle Scholar
  94. Tatto, M. T. (1999a). Improving teacher education in rural México: The challenges and tensions of constructivist reform. Teaching and Teacher Education, 15, 15–35.CrossRefGoogle Scholar
  95. Tatto, M. T. (1999b). The socializing influence of normative cohesive teacher education on teachers’ beliefs about instructional choice. Teachers and Teaching, 5, 111–134.CrossRefGoogle Scholar
  96. Tatto, M. T. (2008). Teacher policy: A framework for comparative analysis. Prospects: Quarterly Review of Comparative Education, 38, 487–508.CrossRefGoogle Scholar
  97. Tatto, M. T. (Ed.). (2013). The Teacher Education and Development Study in Mathematics (TEDS-M). Policy, Practice, and Readiness to Teach Primary and Secondary Mathematics in 17 Countries: Technical Report. Amsterdam, The Netherlands: International Association for the Evaluation of Student Achievement.Google Scholar
  98. Tatto, M. T. (2017). The Role of Comparative and International Research in Developing Capacity to Study and Improve Teacher Education. In M. A. Peters, B. Cowie, & I. Menter (Eds.), A companion to research in teacher education. Singapore: Springer.Google Scholar
  99. Tatto, M. T., & Coupland, D. (2003). Teaching and measuring attitudes in teacher education. In J. Raths & A. McAninch (Eds.), Teacher beliefs and classroom performance: The impact of teacher education (advances in teacher education) (Vol. 6, pp. 123–181). Greenwich, CT: Information Age Publishing.Google Scholar
  100. Tatto, M. T., & Kularatna, N. G. (1993). The interpersonal dimension of teacher education: Comparing distance education with two other programs in Sri Lanka. International Journal of Educational Research, 19, 755–778.CrossRefGoogle Scholar
  101. Tatto, M. T., Nielsen, H. D., Cummings, W. C., Kularatna, N. G., & Dharmadasa, D. H. (1993). Comparing the effectiveness and costs of different approaches for educating primary school teachers in Sri Lanka. Teaching and Teacher Education, 9, 41–64.CrossRefGoogle Scholar
  102. Tatto, M. T., Rodriguez, M., Reckase, M., Smith, W., & Pippin, J. (forthcoming). The first five years of mathematics teaching (FIRSTMATH): Concepts, methods and strategies for comparative international research. Dordrecht, Netherlands: Springer.Google Scholar
  103. Tatto, M. T., Schwille, J., Senk, S., Ingvarson, L., Peck, R., & Rowley, G. (2008). Teacher Education and Development Study in Mathematics (TEDS-M): Conceptual framework. Teacher Education and Development International Study Center, Michigan State University, East Lansing, MI, and IEA.Google Scholar
  104. Tatto, M. T., Schwille, J., Senk, S. L., Ingvarson, L., Rowley, G., Peck, R., … Reckase, M. (2012). Policy, practice, and readiness to teach primary and secondary mathematics in 17 countries. Findings from the IEA teacher education and development study in mathematics (TEDS-M). Amsterdam, The Netherlands: International Association for the Evaluation of Student Achievement.Google Scholar
  105. Tatto, M. T., & Hordern, J. (2017). The configuration of teacher education as a professional field of practice: A comparative study of mathematics education. In J. Furlong & G. Whitty (Eds.), Knowledge and the Study of Education: an international exploration (pp. 255–274). Oxford, UK: Oxford Comparative Education Series, Symposium Books.Google Scholar
  106. UNESCO. (1998). Global monitoring report: Teachers and teaching in a changing world. Paris, France: Author.Google Scholar
  107. UNESCO. (2014). Teaching and learning: Achieving quality for all: Global monitoring report. Paris, France: Author.Google Scholar
  108. UNESCO. (2016). Education for people and planet: Creating sustainable futures for all. Global education monitoring report. Paris: UNESCO. Retrieved from http://unesdoc.unesco.org/images/0024/002457/245752e.pdf
  109. UNESCO’s International Standard Classification of Education (ISCED). (2007). Paris: UNESCO Institute for Statistics. Retrieved from http://www.uis.unesco.org/Education/Pages/international-standard-classification-of-education.aspx
  110. Van Dooren, W., Verschaffel, L., & Onghena, P. (2002). The impact of pre-service teachers’ content knowledge on their evaluation of students’ strategies for solving arithmetic and algebra word problems. Journal for Research in Mathematics Education, 33(5), 319–351.CrossRefGoogle Scholar
  111. Wayne, A. J., & Youngs, P. (2003). Teacher characteristics and student achievement gains: A review. Review of Educational Research, 73(1), 89–122.CrossRefGoogle Scholar
  112. Wilkins, J. L. M., & Brand, B. R. (2004). Change in preservice teachers’ beliefs: An evaluation of a mathematics methods course. School Science and Mathematics, 104(5), 226–232.CrossRefGoogle Scholar
  113. Wu, M., Adams, R., Wilson, M., & Haldane, S. (2007). ACER conquest: Generalised item response modelling software (Version 2.0). Melbourne, Australia: Australian Council for Educational Research (ACER).Google Scholar
  114. Zeichner, K., & Conklin, H. (2005). Teacher education programs. In M. Cochran-Smith & K. Zeichner (Eds.), Studying teacher education (pp. 645–736). New York, NY: Routledge.Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Mary Lou Fulton Teachers CollegeArizona State UniversityTempeUSA

Personalised recommendations