DEVELOPING YOUNG STUDENTSí INFORMAL

INFERENCE SKILLS IN DATA ANALYSIS

 

efi paparistodemou

European University Cyprus

e.paparistodemou@euc.ac.cy

 

MARIA MELETIOU-MAVROTHERIS

European University Cyprus

m.mavrotheris@euc.ac.cy

 

Abstract

 

This paper focuses on developing studentsí informal inference skills, reporting on how a group of third grade students formulated and evaluated data-based inferences using the dynamic statistics data-visualization environment TinkerPlotsTM (Konold &Miller, 2005), software specifically designed to meet the learning needs of students in the early grades. Children analyzed collected data using TinkerPlots as an investigation tool, and made a presentation of their findings to the whole school. Findings from the study support the view that statistics instruction can promote the development of learnersí inferential reasoning at an early age, through an informal, data-based approach. They also suggest that the use of dynamic statistics software has the potential to enhance statistics instruction by making inferential reasoning accessible to young learners.

 

Keywords: Statistics education research, Elementary education, TinkerPlots, Informal statistical inference

 

 

 

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Statistics Education Research Journal, 7(2), 83-106, http://www.stat.auckland.ac.nz/serj

International Association for Statistical Education (IASE/ISI), May, 2008

 

 

 

References

 

Bakker, A. (2002). Route-type and landscape-type software for learning statistical data analysis. In B. Phillips (Ed.), Developing a statistically literate society: Proceedings of the Sixth International Conference on Teaching Statistics, Cape Town, South Africa. [CD-ROM]. Voorburg, The Netherlands: International Statistical Institute.
[Online: http://www.stat.auckland.ac.nz/~iase/publications/1/7f1_bakk.pdf]

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]

Ben-Zvi, D. (2000). Toward understanding the role of technological tools in statistical learning. Mathematical Thinking and Learning, 2, 127-155.

Ben-Zvi, D. (2006). Scaffolding studentsí informal inference and argumentation. In A. Rossman & B. Chance (Eds.), Working cooperatively in statistics education: Proceedings of the Seventh International Conference on Teaching Statistics, Salvador, Brazil. [CDROM]. Voorburg, The Netherlands: International Statistical Institute.
[Online: http://www.stat.auckland.ac.nz/~iase/publications/17/2D1_BENZ.pdf]

Ben-Zvi, D., & Arcavi, A. (2001). Junior high school studentsí construction of global views of data and data representations. Educational Studies in Mathematics, 45(1), 35-65.

Burgess, R. (1984). In the Field. New York: Routledge.

GAISE Report (2005). Guidelines for assessment and instruction in statistics education: A Pre-K-12 Curriculum Framework. Alexandria, VA: The American Statistical Association.
[Online: http://www.amstat.org/education/gaise]

Garfield, J., & Ahlgren, A. (1998). Difficulties in learning basic concepts in probability and statistics: Implications for research. Journal for Research in Mathematics Education, 19, 44-63.

Gordon, F. S., & Gordon, S. P. (1992). Sampling + Simulation = Statistical Understanding. In F. S. Gordon (Ed.), Statistics for the twenty-first century (pp. 207- 216). Washington, DC: The Mathematical Association of America.

Green, D. G. (1982). A survey of probability concepts in 3000 students aged 11-16. In D.V. Grey (Ed.), Proceedings of the First International Conference on Teaching Statistics (pp. 766-783). London: Statistics Teaching Trust.

Hammerman, J., & Rubin, A. (2003). Reasoning in the presence of variability. In C. Lee (Ed.), Reasoning about Variability: A Collection of Current Research Studies [CDROM]. Dordrecht, The Netherlands: Kluwer Academic Publisher.

Johnston-Wilder, P., Ainley, J., & Pratt, D. (2007, August). Thinking-in-change about informal inference. Paper presented at the Fifth International Research Forum on Statistical Reasoning, Thinking, and Literacy (SRTL-5), University of Warwick, UK.

Konold, C., & Higgins, T. (2002). Highlights of related research. In S. J. Russell, D. Schifter, & V. Bastable (Eds.), Developing mathematical ideas: Working with data (pp. 165-201). Parsippany, NJ: Seymour.

Konold, C., & Miller, C. D. (2005). TinkerPlots: Dynamic Data Explorations. Emeryville, CA: Key Curriculum Press.

Makar, K., & Confrey, J. (2007). Moving the context of modeling to the forefront. In W. Blum, P. Galbraith, H-W. Henn, & M. Niss (Eds.), Modelling and applications in mathematics education. New York: Springer.

Makar, K., & Rubin, A. (2007, August). Beyond the bar graph: Teaching informal statistical inference in primary school. Paper presented at the Fifth InternationalResearch Forum on Statistical Reasoning, Thinking, and Literacy (SRTL-5), University of Warwick, UK.

Meletiou-Mavrotheris, M. (2003). Technological tools in the introductory statistics classroom: effects on student understanding of inferential statistics. International Journal of Computers for Mathematical Learning, 8(3), 265-297.

National Council of Teachers of Mathematics (NCTM). (2000). Principles and Standards for School Mathematics. Reston, VA: Author.

Paparistodemou, E. (2004). Childrenís Expressions of Randomness: Constructing Probabilistic Ideas in an Open Computer Game. Unpublished doctoral dissertation, Institute of Education, University of London.

Paparistodemou, E., & Meletiou, M. (2007, August). Enhancing reasoning about statistical inference in 8-year-old students. Paper presented at the Fifth International Research Forum on Statistical Reasoning, Thinking, and Literacy (SRTL-5), University of Warwick, UK.

Paparistodemou, E., Noss, R., & Pratt, D. (2008). The Interplay Between Fairness and Randomness in a Spatial Computer Game. International Journal of Computers for Mathematical Learning, 13(2), 89-110.

Pfannkuch, M. (2006). Informal inferential reasoning. In A. Rossman & B. Chance (Eds.), Working cooperatively in statistics education: Proceedings of the Seventh International Conference on Teaching Statistics, Salvador, Brazil. [CDROM]. Voorburg, The Netherlands: International Statistical Institute.
[Online: http://www.stat.auckland.ac.nz/~iase/publications/17/6A2_PFAN.pdf]

Pratt, D. (1998). The Construction of Meanings In and For a Stochastic Domain of Abstraction. Unpublished doctoral dissertation, Institute of Education, University of London.

Pratt, D. (2000). Making sense of the total of two dice. Journal of Research in Mathematics Education, 31, 602-625.

Rubin, A., Bruce, B., & Tenney, Y. (1990, April). Learning about sampling: Trouble at the core of statistics. Paper Presented at the Annual Meeting of the American Educational Research Association, Boston.

Rubin, A. (2005). Math that matters. In K. Mayer (Ed.), Threshold (pp. 22-31). Cambridge: TERC.

Rubin, A., Hammerman, J., & Konold, C. (2006). Exploring informal inference with interactive visualization software. In A. Rossman & B. Chance (Eds.), Working cooperatively in statistics education: Proceedings of the Seventh International Conference on Teaching Statistics, Salvador, Brazil. [CDROM]. Voorburg, The Netherlands: International Statistical Institute.
[Online: http://www.stat.auckland.ac.nz/~iase/publications/17/2D3_RUBI.pdf]

Watson, J. M. (2006). Statistical literacy at school New Jersey: LEA.

Watson, J. (2007, August). Facilitating beginning inference with TinkerPlots for novice grade 7 students. Paper presented at the Fifth International Research Forum on Statistical Reasoning, Thinking, and Literacy (SRTL-5), University of Warwick, UK.

Wegerif, R., & Mercer, N. (1997). Using computer-based text analysis to integrate qualitative and quantitative methods in research on collaborative learning. Language and Education, 11(4), 271Ė86.

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

Shaughnessy J. M., Ciancetta M., Best K., & Canada D. (2004, April). Studentsí attention to variability when comparing distributions. Paper presented at the 82nd Annual Meeting of the National Council of Teachers of Mathematics, Philadelphia, PA.

Sorto, M. A. (2006). Identifying content knowledge for teaching statistics. In A. Rossman & B. Chance (Eds.), Working cooperatively in statistics education: Proceedings of the Seventh International Conference on Teaching Statistics, Salvador, Brazil. [CDROM]. Voorburg, The Netherlands: International Statistical Institute.
[Online: http://www.stat.auckland.ac.nz/~iase/publications/17/C130.pdf]

Stohl, H., & Tarr, J. E. (2002). Using multi-representational computer tools to make sense of inference. In D. Mewborn (Ed.), Proceedings of the Twenty-fourth Annual Meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education. Athens, GA: Columbus, OH: ERIC Clearinghouse for Science Mathematics and Environmental Education.

Zieffler, A., delMas, R., Garfield, J., & Gould, R. (2007, August). Studying the development of college studentsí informal reasoning about statistical inference. Paper presented at the Fifth International Research Forum on Statistical Reasoning, Thinking, and Literacy (SRTL-5), University of Warwick, UK.

 

 

EFI PAPARISTODEMOU

5 Ellados Street

2003 Nicosia

Cyprus