• Journal of the Korean School Mathematics Society
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• v.21 no.2
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• pp.183-206
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• 2018

It arises that teachers' professional competence should be considered not only with a cognitive perspective but also with a situative perspective. In this study, we considered mathematics teacher noticing as situational professional competencies of a mathematics teacher, and explored how mathematics teachers noticing on children's development of reasoning about variability in a video club has changed with the situative perspective. Findings illustrate that the 'interpreting' component among the three components of noticing-attending, interpreting, and deciding how to respond-was critically decisive for the change of the participant teachers' noticing. We also discussed how the video club intervention(the framework of children's development of reasoning about variability) can support the development of teacher noticing as a professional competence. This study has implications on the design of a video club to improve mathematics teacher noticing.

• Journal of Gifted/Talented Education
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• v.23 no.3
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• pp.387-406
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• 2013

This study compared levels of mathematically talented students' statistical thinking with those of non-talented students in the noticing of statistical variability. t tests were conducted to test for statistically significant differences between mathematically gifted students and non-gifted students. Results for the t-test shows that there is no difference between the TE students' and NE students' noticing of variability in the measurement settings. Meanwhile, the t-test results also show that there is a difference between the TM students' and NM students' noticing of variability in the both measurement and chance settings. Table of frequencies of each level, however, shows that levels of mathematically gifted students' thinking were not distributed at the high levels but were overlapped with those of non-gifted students. These results are thought-provoking results in statistics instruction for mathematically talented students.

• School Mathematics
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• v.14 no.4
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• pp.495-516
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• 2012

This study distinguished thinking related to statistical variability into six components - the noticing of variability, the explanation of variability, the control of variability, the modeling of variability, the understanding of samples, and the understanding of sampling distribution and investigated the relationships among the thinking components. This study found that this distinction of thinking components related to statistical variability is reasonable. The results showed that each correlation coefficient of the modeling of variability, the understanding of samples, and the understanding of sampling distribution with regard to the noticing of variability, the explanation of variability, and the control of variability is similar. Based on this results, new variable, the understanding of sampling, has been drawn. The results also showed that while the noticing of variability and the control of variability influence the understanding of sampling, the explanation of variability does not influence it.

• Journal of Educational Research in Mathematics
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• v.21 no.4
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• pp.327-344
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• 2011

This study is the first step for us toward improving high school students' capability of statistical inferences, such as obtaining and interpreting the confidence interval on the population mean that is currently learned in high school. We suggest 5 underlying concepts of 'discretion of contingency and inevitability', 'discretion of induction and deduction', 'likelihood principle', 'variability of a statistic' and 'statistical model', those are necessary to appreciate statistical inferences as a reliable arguing tools in spite of its occasional erroneous conclusions. We assume those 5 concepts above are to be gradually developing in their school periods and Korean mathematics textbooks of grades 1-12 were analyzed. Followings were found. For the right choice of solving methodology of the given problem, no elementary textbook but a few high school textbooks describe its difference between the contingent circumstance and the inevitable one. Formal definitions of population and sample are not introduced until high school grades, so that the developments of critical thoughts on the reliability of inductive reasoning could not be observed. On the contrary of it, strong emphasis lies on the calculation stuff of the sample data without any inference on the population prospective based upon the sample. Instead of the representative properties of a random sample, more emphasis lies on how to get a random sample. As a result of it, the fact that 'the random variability of the value of a statistic which is calculated from the sample ought to be inherited from the randomness of the sample' could neither be noticed nor be explained as well. No comparative descriptions on the statistical inferences against the mathematical(deductive) reasoning were found. Few explanations on the likelihood principle and its probabilistic applications in accordance with students' cognitive developmental growth were found. It was hard to find the explanation of a random variability of statistics and on the existence of its sampling distribution. It is worthwhile to explain it because, nevertheless obtaining the sampling distribution of a particular statistic, like a sample mean, is a very difficult job, mere noticing its existence may cause a drastic change of understanding in a statistical inference.