References
- Smith JP, Disessa A, Roschelle J. Misconceptions reconceived: a constructivist analysis of knowledge in transition. J Learn Sci. 1994;3(2):115–163.
- Bransford JD, Donovan SM. How students learn: history, mathematics, and science in the classroom. Washington (DC): National Academies Press; 2005.
- Shaughnessy JM. Problem-solving derailers: the influence of misconceptions on problem-solving performance. In: Silver EA, editor. Teaching and learning mathematical problem solving. Hillsdale (NJ): Lawrence Erlbaum Associates; 1985. p. 399–415.
- Kaplan J, Fisher D, Rogness N. Lexical ambiguity in statistics: how students use and define the words: association, average, confidence, random and spread. J Stat Educ. 2010;18(2). Available from: http://www.amstat.org/publications/jse/v18n2/abstracts.html
- Kim H, Fukawa-Connelly T, Cook S. Student understanding of symbols in introductory statistics courses. In: Brown S, Larsen S, Marrongelle K, Oehrtman M, editors. Proceedings of the 15th Annual Conference on Research in Undergraduate Mathematics Education. Portland (OR); 2012. p. 73–79; Available from: http://sigmaa.maa.org/rume/Site/Proceedings.html
- Franklin C, Kader G, Mewborn D, et al. Guidelines for assessment and instruction in statistics education (GAISE) report. Alexandría: American Statistical Association; 2007.
- Mayen S, Diaz C, Batanero C. Students’ semiotic conflicts in the concept of median. Stat Educ Res J. 2009;8(2):74–93.
- Watier N, Lamontagne C, Chartier S. What does the mean mean? J Stat Educ. 2011;19(2). Available from: http://www.amstat.org/publications/jse/v19n2/abstracts.html
- Peters S. Robust understanding of statistical variation. Stat Educ Res J. 2011;10(1):52–88.
- Watson J. The influence of variation and expectation on the developing awareness of distribution. Stat Educ Res J. 2009;8(1):32–61.
- Zieffler A, Garfield J. Modeling the growth of students’ covariational reasoning during an introductory statistics course. Stat Educ Res J. 2009;8(1):7–31.
- Bond M, Perkins S, Ramirez C. Students’ perceptions of statistics: an exploration of attitudes, conceptualizations, and context knowledge of statistics. Stat Educ Res J. 2012;11(2):86–94.
- Schau C, Emmioglu E. Do introductory statistics courses in the United States improve students’ attitudes? Stat Educ Res J. 2012;11(2):86–94.
- Sfard A. On the dual nature of mathematical conceptions: reflections on processes and objects as different sides of the same coin. Educ Stud Math. 1991;22:1–36.
- Ewing T. A study of certain factors involved in changes of opinion. J Soc Psychol. 1942;16:63–88.
- Osgood CE, Tannenbaum PH. The principle of congruity in the prediction of attitude change. Psychol Rev. 1955;62:42–55.
- Wood W. Retrieval of attitude-relevant information from memory: effects of susceptibility to persuasion and on intrinsic motivation. J Personal Soc Psychol. 1982;42:798–810.
- Wood W, Kallgren C. Communicator attributes and persuasion: recipients’ access to attitude-relevant information in memory. Personal Soc Psychol Bull. 1988;14:172–182.
- Lord C, Ross L, Lepper M. Biased assimilation and attitude polarization: the effects of prior theories on subsequently considered evidence. J Personal Soc Psychol. 1979;37:2098–2109.
- Miller A, McHoskey J, Bane C, et al. The attitude polarization phenomenon: role of response means, attitude extremity, and behavioral consequences of reported attitude change. J Personal Soc Psychol. 1993;64:561–574.
- Knuth EJ, Alibali MW, McNeil NM, et al. Middle school students’ understanding of core algebraic concepts: equivalence and variable. ZDM. 2005;37(1):68–76.
- Küchemann D. Children's understanding of numerical variables. Math Sch. 1978;7:23–26.
- Kim H, Fukawa-Connelly T. Transfer of critical thinking disposition from mathematics to statistics. In: Brown S, Karakok G, Roh KH, Oehrtman M, editors. Proceedings of the 16th Annual Conference on Research in Undergraduate Mathematics Education. Denver (CO); 2013. p. 145–151. Available from: http://sigmaa.maa.org/rume/Site/Proceedings.html
- Moore D. New pedagogy and new content: the case of statistics. Int Stat Rev. 1997;65:123–165.
- Mokros J, Russell S. Children's concepts of average and representativeness. J Res Math Educ. 1995;26(1):20–39.
- Cook S, Fukawa-Connelly T. Toward a theory of symbol sense in undergraduate statistics. In: Brown S, Larsen S, Marrongelle K, Oehrtman M, editors. Proceedings of the 15th Annual Conference on Research in Undergraduate Mathematics Education. Portland (OR); 2012. p. 134–148. Available from: http://sigmaa.maa.org/rume/Site/Proceedings.html
- delMas R, Liu Y. Exploring students’ conceptions of the standard deviation. Stat Educ Res J. 2005;4(1):55–82.
- Goldin GA. Observing mathematical problem solving through task-based interviews. In: Teppo A, editor. Qualitative research methods in mathematics education. Monograph number 9. Reston (VA): National Council of Teacher of Mathematics; 1997. p. 40–62.
- Strauss A, Corbin J. Basics of qualitative research: grounded theory procedures and techniques. London: Sage; 1990.
- Tall D, Vinner S. Concept image and concept definition in mathematics, with particular reference to limits and continuity. Educ Stud Math. 1981;12(2):151–169.