Abstract
What is an appropriate structure for reporting a study of tertiary students’ understanding of statistical inference, following an Action Research paradigm?
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References
delMas, R., Garfield, J., & Chance, B. (1999). A model of classroom research in action: Developing simulation activities to improve students’ statistical reasoning. Journal of Statistics Education, 7(3). Retrieved from http://www.amstat.org/publications/jse.
Garfield, J., & Ahlgren, A. (1988). Difficulties in learning basic concepts in probability and statistics: Implications for research. Journal for Research in Mathematics Education, 19(1), 44–63.
Gliner, J., Leech, N., & Morgan, G. (2002). Problems with null hypothesis significance testing (NHST): What do the textbooks say? The Journal of Experimental Education, 71(1), 83–92.
Hammersley, M. (1993). On the teacher as researcher. Educational Action Research, 1(3), 425–445.
Krause, K., Bochner, S., & Duchesne, S. (2007). Educational psychology for learning and teaching. South Melbourne, VIC: Thomson.
Lane, D., & Peres, S. (2006). Interactive simulations in the teaching of statistics: Promise and pitfalls. In Phillips B (Ed.), Developing a statistically literate society (Proceedings of the 7th international conference on teaching statistics, Salvador, Brazil) [CDRom]. Voorburg, The Netherlands: International Statistics Institute.
Masters, G., & Wright, B. (1997). The partial credit model. In W. van der Linden & R. Hambleton (Eds.), Handbook of modern item response theory (pp. 101–122). New York: Springer.
Mills, G. (2007). Action research: A guide for the teacher researcher. Upper Saddle River NJ: Merrill Prentice Hall.
National Research Council. (2002). Scientific research in education. Washington DC: National Academy Press.
Noffke, S. (1994). Action research: Towards the next generation. Educational Action Research, 2(1), 9–21.
Perkins, D., & Simmons, R. (1988). Patterns of misunderstanding: An integrative model for science, math and programming. Review of Educational Research, 58(3), 303–326.
Popper, K. (1963). Conjectures and refutations. London: Routledge and Kegan Paul.
Shavelson, R., Phillips, D., Towne, L., & Feuer, M. (2003). On the science of education design studies. Educational Researcher, 32(1), 25–28.
Steffe, L., Thompson, P., & Von Glaserfield, E. (2001). Teaching experiment methodology: Underlying principles and essential elements. In S. Carver & D. Klahr (Eds.), Cognition and instruction: Twenty-five years of progress (pp. 205–226). Mahwah, NJ: Laurence Erlbaum and Associates.
Strike, K., & Posner, G. (1985). A conceptual change view of learning and understanding. In L. West & A. Pines (Eds.), Cognitive structure and conceptual change (pp. 259–266). New York: Academic Press.
Yilmaz, M. (1996). The challenge of teaching statistics to non-specialists. Journal of Statistics Education, 4(1). Retrieved from http://www.amstat.org/publications/jse.
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Reaburn, R. (2018). Students’ Understanding of Statistical Inference: Implications for Teaching. In: Kember, D., Corbett, M. (eds) Structuring the Thesis. Springer, Singapore. https://doi.org/10.1007/978-981-13-0511-5_12
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DOI: https://doi.org/10.1007/978-981-13-0511-5_12
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