SUBJECT MATTER KNOWLEDGE FOR TEACHING STATISTICAL ASSOCIATION
 

STEPHANIE A. CASEY

Deerfield High School

scasey@dist113.org

 

ABSTRACT

 

This study seeks to describe the subject matter knowledge needed for teaching statistical association at the secondary level. Taking a practice-based qualitative approach, three experienced teachers were observed as they taught statistical association and interviewed immediately following each observation. Records of practice were assembled to create a compilation document to recreate each of the fifty observed class sessions along with related materials including textbook pages and student work. Analysis of the compilation documents focused on the demands upon teachers' subject matter knowledge involved in the practice of teaching. Findings regarding the knowledge required for teaching correlation coefficient are highlighted, including its computation, interpretation, sensitivity, estimation, and related terminology.

 

Keywords: Statistics education research; Qualitative research; Teacher knowledge

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Statistics Education Research Journal, 9(2), 50-68, http://www.stat.auckland.ac.nz/serj

Ó International Association for Statistical Education (IASE/ISI), November, 2010

 

REFERENCES

 

Bakker, A. (2004). Reasoning about shape as a pattern in variability. Statistics Education

Research Journal, 3(2), 64-83.

      [Online: http://www.stat.auckland.ac.nz/~iase/serj/SERJ3(2)_Bakker.pdf]

Ball, D. L., & Bass, H. (2000a). 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.

Ball, D. L., & Bass, H. (2000b). Making believe: The collective construction of public mathematical knowledge in the elementary classroom. In D. Phillips (Ed.), Yearbook of the National Society for the Study of Education, Constructivism in Education (pp. 193-224). Chicago: University of Chicago Press.

Ball, D. L., & Bass, H. (2003). Toward a practice-based theory of mathematical knowledge for teaching. In B. Davis & E. Simmt (Eds.), Proceedings of the 2002 Annual Meeting of the Canadian Mathematics Education Study Group (pp. 3-14). Edmonton, AB: Canadian Mathematics Education Study Group.

Ball, D., Cole, Y., Delaney, S., Fauskanger, J., Kwon, M., Mosvold, R., & Ng, D. (2009, April). Adapting and using U.S. measures of mathematical knowledge for teaching in other countries: Lessons and challenges. Paper presented at the American Educational Research Association Annual Meeting, San Diego, CA.

Ball, D. L., & Hill, H. C. (2005, April). Knowing mathematics as a teacher. Presentation at the Annual Meeting of the National Council of Teachers of Mathematics, Anaheim, CA.

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., pp. 433-456). New York: Macmillan.

Ben-Zvi, D., & Garfield, J. (2004). Statistical literacy, reasoning, and thinking: Goals, definitions, & challenges. In D. Ben-Zvi & J. Garfield (Eds.), The challenge of developing statistical literacy, reasoning, and thinking (pp. 3-15). Dordrecht, The Netherlands: Kluwer Academic Publishers.

Burgess, T. A. (2007). Investigating the nature of teacher knowledge needed and used in teaching statistics (Unpublished doctoral dissertation). Massey University, Auckland, New Zealand.

Casey, S. (2008). Subject matter knowledge for teaching statistical association (Unpublished doctoral dissertation). Illinois State University, Normal, IL.

College Board (2003). AP statistics 2003 free-response questions form B. New York: Author.

[Online: www.collegeboard.com/prod_downloads/ap/students/statistics/b_statistics_frq_03.pdf]

College Board (2008). AP Statistics course description. New York: Author.

      [Online: apcentral.collegeboard.com/apc/public/repository/ap08_statistics_coursedesc.pdf]

Conference Board of the Mathematical Sciences (2001). The mathematical education of teachers. Washington, DC: Mathematical Association of America; Providence, RI: American Mathematical Society.

delMas, R. C. (2004). A comparison of mathematical and statistical reasoning. In D. Ben-Zvi & J. Garfield (Eds.), The challenge of developing statistical literacy, reasoning, and thinking (pp. 79-95). Dordrecht, The Netherlands: Kluwer Academic Publishers.

Denzin, N. K. (1978). The research act: A theoretical introduction to sociological methods (2nd ed.). New York: McGraw-Hill.

Estepa, A., & Batanero, C. (1996). Judgments of correlation in scatterplots: Students' intuitive strategies and preconceptions. Hiroshima Journal of Mathematics Education, 4, 25-41.

Estepa, A., & Sanchez-Cobo, F. T. (1998). Correlation and regression in secondary school textbooks. In L. Pereira-Mendoza, L. Seu Kea, T. Wee Kee, & W. K. Wong (Eds.), Proceedings of the Fifth International Conference on the Teaching of Statistics (vol. 2, pp. 671-676). Voorburg, The Netherlands: International Statistical Institute.

Estepa, A., & Sanchez-Cobo, F. T. (2003). Evaluacion de la comprension de la correlacion y regression a partir de la resolucion de problemas. Statistics Education Research Journal, 2(1), 54-68.

[Online: http://www.stat.auckland.ac.nz/~iase/serj/SERJ2(1).pdf]

Franklin, C. (2000). Are our teachers prepared to provide instruction in statistics at the K-12 levels? National Council of Teachers of Mathematics Education Dialogues, 10.

  [Online: http://www.nctm.org/resources/content.aspx?id=1776]

Gal, I. (2004). Statistical literacy: Meanings, components, responsibilities. In D. Ben-Zvi & J. Garfield (Eds.), The challenge of developing statistical literacy, reasoning, and thinking (pp. 47-78). Dordrecht, The Netherlands: Kluwer Academic Publishers.

Gagné, R. M. (1985). The conditions of learning. New York: Holt, Rinehart, & Winston.

Garfield, J. & Ben-Zvi, D. (2004). Research on statistical literacy, reasoning, and thinking: Issues, challenges, and implications. In D. Ben-Zvi & J. Garfield (Eds.), The challenge of developing statistical literacy, reasoning, and thinking (pp. 397–409). Dordrecht, The Netherlands: Kluwer Academic Publishers.

Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory. Chicago: Aldine.

Groth, R. E. (2006). Analysis of an online case discussion about teaching stochastics.

Mathematics Teacher Education and Development, 7, 53-71.

Groth, R. E. (2007). Toward a conceptualization of statistical knowledge for teaching. Journal for Research in Mathematics Education, 38(5), 427-437.

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.

Hill, H. C., Schilling, S. G., & Ball, D. L. (2004). Developing measures of teachers' mathematical knowledge for teaching. Elementary School Journal, 105(1), 11-30.

Kettenring, J., Lindsay, B., & Siegmund, D. (Eds.) (2003). Statistics: Challenges and opportunities for the 21st century. National Science Foundation Report.

[Online: http://www.stat.psu.edu/~Ebgl/nsf_report.pdf]

McKenzie, C. R. M., & Mikkelsen, L. A. (2007). A Bayesian view of covariation assessment. Cognitive Psychology, 54(1), 33-61.

Merriam, S. B. (1998). Qualitative research and case study applications in education. San Francisco: Jossey-Bass Publishers.

Ministry of Education. (1992). Mathematics in the New Zealand curriculum. Wellington, NZ: Author.

Moore, D. (2004). Foreword. In D. Ben-Zvi & J. Garfield (Eds.), The challenge of developing statistical literacy, reasoning, and thinking (pp. ix–x). Dordrecht, The Netherlands: Kluwer Academic Publishers.

Moritz, J. (2004). Reasoning about covariation. In D. Ben-Zvi & J. Garfield (Eds.), The challenge of developing statistical literacy, reasoning, and thinking (pp. 227-255). Dordrecht, The Netherlands: Kluwer Academic Publishers.

National Board for Professional Teaching Standards. (2001). Adolescence and Young Adulthood Mathematics Standards (2nd ed.). Arlington, VA: Author.

[Online: http://www.nbpts.org/userfiles/File/aya_math_standards.pdf]

National Council for Accreditation of Teacher Education/NCTM. (2003). Program Standards. Reston, VA: Authors.

      [Online: http://www.nctm.org/uploadedFiles/Math_Standards/NCTMSECONStandards.pdf]

National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics. Reston, VA: Author.

National Council of Teachers of Mathematics. (2005). Highly qualified teachers: A position of the National Council of Teachers of Mathematics. NCTM News Bulletin, 42(3), 4.

National Council of Teachers of Mathematics. (2009). Focus in high school mathematics: Reasoning and sense making. Reston, VA: Author.

National Research Council. (2001). Knowing and learning mathematics for teaching: Proceedings of a workshop. Washington, DC: National Academy Press.

Patton, M. Q. (1990). Qualitative evaluation and research methods (2nd ed.). Thousand Oaks, CA: Sage Publications.

Qualifications and Curriculum Authority. (2007). The National Curriculum 2007. Earlsdon Park, Coventry: Author.

[Online: http://curriculum.qcda.gov.uk]

RAND Mathematics Study Panel. (2003). Mathematical proficiency for all students: Toward a strategic research and development program in mathematics education. Washington, DC: Office of Education Research and Improvement, U.S. Department of Education.

Senk, S., Viktora, S., Usisking, Z., Ahbel, N., Highstone, V., Witonsky, D., et al. (1998). Functions, Statistics, and Trigonometry (2nd ed.). Glenview, IL: Scott Foresman and Company.

Shaughnessy, J. M. (2007). Research on statistics learning and reasoning. In F. Lester, Jr. (Ed.), Second handbook of research on mathematics teaching and learning (pp. 957-1009). Reston, VA: NCTM.

Sorto, M. A. (2004). Prospective middle school teachers’ knowledge about data analysis and its application to teaching (Unpublished doctoral dissertation). Michigan State University, Ann Arbor, MI.

Sotos, A. E. C., Vanhoof, S., Van Den Noortgate, W., & Onghena, P. (2009). The transitivity misconception of Pearson's correlation coefficient. Statistics Education Research Journal, 8(2), 33-55.

[Online: http://www.stat.auckland.ac.nz/~iase/serj/SERJ8(2)_Sotos.pdf]

Stake, R. E. (1995). The art of case study research. Thousand Oaks, CA: Sage Publications.

Wild, C. J., & Pfannkuch, M. (1999). Statistical thinking in empirical enquiry. International Statistical Review, 67(3), 223-265.

Wilson, P. S. (2004, August). GAISE report discussion. Presentation at the Joint Statistical Meetings, Toronto, Canada.

[Online: http://www.amstat.org/education/gaise/WilsonJSM04.ppt]

Yackel, E., & Hanna, G. (2003). Reasoning and proof. In J. Kilpatrick, W. G. Martin, & D. Schifter (Eds.), A research companion to the principles and standards for school mathematics (pp. 227-236). Reston, VA: NCTM.

Yates, D. S., Moore, D. S., & McCabe, G. P. (1999). The Practice of Statistics: TI-83 Graphing Calculator Enhanced. New York: W.H. Freeman.

 

STEPHANIE a. cASEY

Deerfield High School

1959 North Waukegan Road

Deerfield, Illinois 60015

USA