Abstract
This paper presents recent data on the performance of 247 middle school students on questions concerning average in three contexts. Analysis includes considering levels of understanding linking definition and context, performance across contexts, the relative difficulty of tasks, and difference in performance for male and female students. The outcomes lead to a discussion of the expectations of the curriculum and its implementation, as well as assessment, in relation to students' skills in carrying out procedures and their understanding about the meaning of average in context.
Similar content being viewed by others
References
Australian Curriculum, Assessment and Reporting Authority. (2009). National Assessment Program Literacy and Numeracy. Numeracy non-calculator. Year 9 2009. Sydney: Australian Curriculum, Assessment and Reporting Authority.
Australian Curriculum, Assessment and Reporting Authority. (2010). National Assessment Program Literacy and Numeracy. Numeracy non-calculator. Year 9. Sydney: Australian Curriculum, Assessment and Reporting Authority.
Australian Curriculum, Assessment and Reporting Authority. (2012). The Australian curriculum: mathematics, version 3.0, 23. Sydney: Australian Curriculum, Assessment and Reporting Authority.
Australian Curriculum, Assessment and Reporting Authority. (2013a). General capabilities in the Australian curriculum, January, 2013. Sydney: ACARA.
Australian Curriculum, Assessment and Reporting Authority. (2013b). The Australian curriculum: mathematics, version 5.0, 20. Sydney: Australian Curriculum, Assessment and Reporting Authority.
Australian Curriculum, Assessment and Reporting Authority. (2013c). The Australian curriculum: science, version 5.0, 20. Sydney: Australian Curriculum, Assessment and Reporting Authority.
Australian Education Council. (1991). A national statement on mathematics for Australian schools. Carlton, VIC: Australian Education Council.
Bakker, A., & Derry, J. (2011). Lessons from inferentialism for statistics education. Mathematical Thinking and Learning, 13, 5–26.
Begg, A., & Edwards, R. (1999). Teachers' ideas about teaching statistics. Proceedings of the 1999 Combined Conference of the Australian Association for Research in Education and the New Zealand Association for Research in Education. Melbourne: Australian Association for Research in Education. Retrieved on November 1, 2012 from http://www.aare.edu.au/data/publications/1999/beg99082.pdf
Biggs, J. B., & Collis, K. F. (1982). Evaluating the quality of learning: the SOLO taxonomy. New York: Academic.
Biggs, J. B., & Collis, K. F. (1991). Multimodal learning and the quality of intelligent behaviour. In H. A. H. Rowe (Ed.), Intelligence: reconceptualization and measurement (pp. 57–76). Hillsdale: Lawrence Erlbaum.
Boddington, A. L. (1936). Statistics and their application to commerce (7th ed.). London: Sir Isaac Pitman.
Cai, J. (1995). Beyond the computational algorithm: students’ understanding of the arithmetic average concept. In L. Meira & D. Carraher (Eds.), Proceedings of the 19th Psychology of Mathematics Education Conference (Vol. 3, pp. 144–151). São Paulo: PME Program Committee.
Cai, J. (1998). Exploring students’ conceptual understanding of the averaging algorithm. School Science and Mathematics, 98, 93–98.
Cai, J. (2000). Understanding and representing the arithmetic averaging algorithm: an analysis and comparison of US and Chinese students’ responses. International Journal of Mathematical Education in Science and Technology, 31, 839–855.
Callingham, R. A. (1997). Teachers’ multimodal functioning in relation to the concept of average. Mathematics Education Research Journal, 9, 205–224.
Callingham, R. (2010). Trajectories of learning in middle years' students' statistical development. Refereed paper in C. Reading (Ed.), Data and context in statistics education: Towards an evidence-based society. (Proceedings of the 8th International Conference on the Teaching of Statistics, Ljubljana, Slovenia, July). [CD-ROM] Voorburg, The Netherlands: International Statistical Institute.
Callingham, R., & Watson J. M. (2008). Overcoming research design issues using Rasch measurement: The StatSmart project. In P. Jeffery (Ed.), Proceedings of the AARE annual conference, Fremantle, December, 2007. Retrieved on September 12, 2009 from: http://www.aare.edu.au/07pap/cal07042.pdf
Carmichael, C., & Hay, I. (2009). Gender differences in middle school students' interests in a statistical literacy context. In R. Hunter, B. Bicknell, & T. Burgess (Eds.), Crossing divides: proceedings of the 32nd annual conference of the Mathematics Education Research Group of Australasia (Vol. 1, pp. 97–104). Palmerston North: MERGA.
Cohen, J. (1969). Statistical power analysis for the behavioral sciences. New York: Academic.
Common Core State Standards Initiative (CCSSI). (2010). Common core state standards for mathematics. Washington, DC: National Governors Association for Best Practices and the Council of Chief State School Officers. Retrieved on 29 April, 2012 from http://www.corestandards.org/assets/CCSSI_Math%20Standards.pdf
Denbow, C. H., & Goedicke, V. (1959). Foundations of mathematics. New York: Harper & Row.
Department for Education (England and Wales). (1995). Mathematics in the national curriculum. London: Author.
Dictionary Central. (n.d.). http://www.dictionarycentral.com/definition/average.html
Franklin, C., Kader, G., Mewborn, D., Moreno, J., Peck, R., Perry, M., & Scheaffer, R. (2007). Guidelines for assessment and instruction in statistics education (GAISE) report: a preK-12 curriculum framework. Alexandria, VA: American Statistical Association. http://www.amstat.org/education/gaise/. Retrieved July 3, 2009
Friel, S. N., Mokros, J. R., & Russell, S. J. (1992). Statistics: middles, means, and in-betweens: a unit of study for grades 5–6 [Used numbers: real data in the classroom]. Palo Alto: Dale Seymour.
Gal, I. (1995). Statistical tools and statistical literacy: the case of the average. Teaching Statistics, 17, 97–99.
Gal, I., Rothschild, K., & Wagner, D. A. (1990, April). Statistical concepts and statistical reasoning in school children: convergence or divergence? Paper presented at the meeting of the American Educational Research Association, Boston
Goodchild, S. (1988). School pupils' understanding of average. Teaching Statistics, 10, 77–81.
Green, D. (1993). Data analysis: what research do we need? In L. Pereira-Mendoza (Ed.), Introducing data analysis in the schools: who should teach it? (pp. 219–239). Voorburg: International Statistical Institute.
Hardiman, P. T., Well, A. D., & Pollatsek, A. (1984). Usefulness of a balance model in understanding the mean. Journal of Educational Psychology, 76(5), 792–801.
Jacobbe, T., & Fernandes de Carvalho, C. (2011). Teachers' understanding of average. In C. Batanero, G. Burrill, C. Reading, & A. Rossman (Eds.), Teaching statistics in school mathematics—challenges for teaching and teacher education (pp. 199–209). New York: Springer.
Kirkpatrick, E. M. (Ed.). (1983). Chambers 20th century dictionary. Edinburgh: Chambers.
Konold, C., & Pollatsek, A. (2002). Data analysis as the search for signals in noisy processes. Journal for Research in Mathematics Education, 33, 259–289.
Leavy, A., & O’Loughlin, N. (2006). Preservice teachers’ understanding of the mean: moving beyond the arithmetic average. Journal of Mathematics Teacher Education, 9, 53–90.
Leon, M. R., & Zawojewski, J. S. (1991). Use of the arithmetic mean: an investigation of four properties, issues and preliminary results. In D. Vere-Jones (Ed.), Proceedings of the third International Conference on Teaching Statistics (School and general issues, Vol. 1, pp. 302–306). Voorburg: International Statistical Institute.
Mevarech, Z. (1983). A deep structure model of students' statistical misconceptions. Educational Studies in Mathematics, 14, 415–429.
Ministry of Education. (1992). Mathematics in the New Zealand curriculum. Wellington: Ministry of Education.
Mokros, J., & Russell, S. J. (1995). Children’s concepts of average and representativeness. Journal for Research in Mathematics Education, 26, 20–39.
National Council of Teachers of Mathematics. (1989). Curriculum and evaluation standards for school mathematics. Reston: National Council of Teachers of Mathematics.
National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics. Reston: National Council of Teachers of Mathematics.
National Council of Teachers of Mathematics. (2006). Curriculum focal points for prekindergarten through grade 8 mathematics: a quest for coherence. Reston: National Council of Teachers of Mathematics.
Pendlebury, C. (1896). Arithmetic (9th ed.). London: George Bell and Sons.
Pendlebury, C., & Robinson, F. E. (1928). New school arithmetic. London: G. Bell and Sons.
Pollatsek, A., Lima, S., & Well, A. D. (1981). Concept or computation: students' understanding of the mean. Educational Studies in Mathematics, 12, 191–204.
Rao, C. R. (1975). Teaching of statistics at the secondary level: an interdisciplinary approach. International Journal of Mathematical Education in Science and Technology, 6, 151–162.
Reed, S. K. (1984). Estimating answers to algebra word problems. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10, 778–790.
Shaughnessy, J. M. (1997). Missed opportunities in research on the teaching and learning of data and chance. In F. Biddulph & K. Carr (Eds.), People in mathematics education (Proceedings of the 20th annual conference of the Mathematics Education Research Group of Australasia, vol. 1, pp. 6–22), Waikato, NZ: MERGA
Smith, B. (1866). A shilling book of arithmetic for national and elementary schools. Cambridge: Macmillan and Co.
Strauss, S., & Bichler, E. (1988). The development of children’s concept of the arithmetic average. Journal for Research in Mathematics Education, 19, 64–80.
Watson, J. (2008). Eye colour and reaction time: an opportunity for critical statistical reasoning. Australian Mathematics Teacher, 64(3), 30–40.
Watson, J. M., & Callingham, R. A. (2003). Statistical literacy: a complex hierarchical construct. Statistics Education Research Journal, 2(2), 3–46.
Watson, J., & Chick, H. (2012). Average revisited in context. In J. Dindyal, L. P. Cheng, & S. F. Ng (Eds.), Mathematics education: expanding horizons (Proceedings of the 35th annual conference of the Mathematics Education Research Group of Australasia, eBook (pp. 753–760). Singapore: MERGA, Inc.
Watson, J. M., & Kelly, B. A. (2005). The winds are variable: student intuitions about variation. School Science and Mathematics, 105, 252–269.
Watson, J. M., & Moritz, J. B. (1999). The development of concepts of average. Focus on Learning Problems in Mathematics, 21(4), 15–39.
Watson, J. M., & Moritz, J. B. (2000). The longitudinal development of understanding of average. Mathematical Thinking and Learning, 2(1&2), 11–50.
Acknowledgments
This project was funded by Australian Research Council Grant No. LP0669106. An earlier version of some of these results was presented at the Mathematics Education Research Group of Australasia conference in Singapore, 2012 (Watson and Chick 2012).
Author information
Authors and Affiliations
Corresponding author
Appendices
Appendix 1
Appendix 2
Rights and permissions
About this article
Cite this article
Watson, J., Chick, H. & Callingham, R. Average: the juxtaposition of procedure and context. Math Ed Res J 26, 477–502 (2014). https://doi.org/10.1007/s13394-013-0113-4
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13394-013-0113-4