• Education of Primary School Mathematics
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• v.12 no.1
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• pp.31-38
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• 2009

This paper aims to develop a program which cultivates statistical ability for elementary students. For this purpose, I examined the relationship between mathematical thinking and statistical thinking. I developed statistical programs including classification, discussion of data, generating statistical problem and project program. As result, this study suggests implications for further elementary statistical education.

• The Mathematical Education
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• v.50 no.2
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• pp.185-212
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• 2011

The purpose of this study is to analyze whether spreadsheet-used instruction can improve statistical thinking ability and attitude and also to identify what characteristics of statistical thinking is constructed. For this study, a subject of 2 classes were randomly selected among the 12 classes of the 11th grader in D high school and designated one class as the experimental group and the other class as the control group. Eight hours of the spread sheet-used instruction and the traditional textbook-oriented instruction had been carried out in each class. The research findings are as follows. First, the spread sheet-used instruction is shown to be more effective in enhancing statistical thinking than the traditional textbook-oriented instruction. Second, the spread sheet-used instruction is shown to be more effective in improving statistical attitude than the traditional textbook-oriented instruction. Third, students have shown the various characteristics of statistical thinking in the data descriptive process, data arrange-summary process, data representing process, and data analying process through the spread sheet-used instructions. Hence, the spread sheet-used instruction is recommended in teaching statistics.

• School Mathematics
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• v.13 no.1
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• pp.207-227
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• 2011

This study developed a statistical thinking level with constructs framework from based on Jones, Thornton, Langrall, & Mooney (2000) to analyze the 6th graders' thinking level shown on their survey activities. It was modified by 5 constructs framework such as collecting, describing, organizing, representing, and analyzing and interpreting data with four thinking levels, which represent a continuum from idiosyncratic to analytic reasoning. As a result, among four levels such as idiosyncratic level (level 1), transitional level (level 2), quantitative level (level 3), and analytical level (level 4), levels of two through four are shown on statistical thinking levels in this study.

• Research in Mathematical Education
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• v.26 no.3
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• pp.127-146
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• 2023

Statistical thinking has a broad definition but focuses on the context of regression modelling in the present study. To foster students' statistical thinking within the context, teaching should no longer be seen as transfer of knowledge from teacher to students but as a process of engaging with learning activities in which they develop ownership of knowledge. This study aims at collaborative learning contexts; students were divided into small groups in order to increase opportunities for peer collaboration. Each group of students was asked to do a regression project after class. Through doing the project, they learnt to organize and connect previously accrued piecemeal statistical knowledge in an integrated manner. They could also clarify misunderstandings and solve problems through verbal exchanges among themselves. They gave a clear and lucid account of the model they had built and showed collaborative interactions when presenting their projects in front of class. A survey was conducted to solicit their feedback on how peer collaboration would facilitate learning of statistics. Almost all students found their interaction with their peers productive; they focused on the development of statistical thinking with concerted effort.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.105-117
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• 2022

Recently, the number of students taking basic statistics in liberal arts courses at universities nationwide has been increasing significantly. Students who learn statistics only for one semester are more likely to live as consumers than producers of statistical analysis in the future. What consumers need is statistical literacy and thinking skills rather than statistical methods. This paper deals with what points should be considered in order to develop textbooks that improve statistical thinking.

• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.105-110
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• 2004

Decision Analysis(DA) using Value Focused Thinking(VFT) can be an excellent process to deal with hard decisions. The intent of this research is to provide better understanding of the United States Air Force(USAF) officer retention problem. This thesis effort involves building a VFT model to find out more effective alternatives in retaining pilots and non pilots. This model, in conjunction with the results of the post analysis, shows an example of the application of a VFT approach to the USAF officer retention problem.

• Journal of Educational Research in Mathematics
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• v.21 no.2
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• pp.201-220
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• 2011

This study investigates levels of thinking of elementary and middle school students doing their tasks of explaining and dealing with variability. According to results, on the task of explaining variability in the measurement settings five levels of thinking were identified: a lack of understanding of explanation of the causes, an insufficient understanding of the causes, an offer of physical causes, consideration of unexplained causes as the source of variability, and consideration of unexplained causes as quasi-chance variability. Also, in the chance settings five levels of thinking were identified: a lack of understanding of explanation of the causes, an insufficient understanding of the causes, an offer of physical causes, recognition of chance variability, and consideration of causes of distribution. On the task of dealing with variability in both the measurement and chance settings five levels of thinking were identified: a lack of understanding of dealing with variability, no physical control and improper statistical control, no physical control and proper statistical control, physical control and improper statistical control, and physical control and proper statistical control.

• Journal of Gifted/Talented Education
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• v.22 no.3
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• pp.503-525
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• 2012

This study compared levels of mathematically talented students' statistical thinking with those of non-talented students in statistical modeling and sampling distribution understanding. t tests were conducted to test for statistically significant differences between mathematically gifted students and non-gifted students. In case of statistical modeling, for both of elementary and middle school graders, the t tests show that there is a statistically significant difference between mathematically gifted students and non-gifted students. 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. A similar tendency is also present in sampling distribution understanding. These results are thought-provoking results in statistics instruction for mathematically talented students.

• The Mathematical Education
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• v.58 no.3
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• pp.459-481
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• 2019

This study aims to investigate students' statistical thinking through statistical processes in different instructional settings: Teacher-centered instruction vs. student-centered learning. We first developed instructional materials that allowed students to experience all the processes of statistics, including data collection, data analysis, data representation, and interpretation of the results. Using the instructional materials for four classes, we collected and analyzed the data from 57 seventh graders' discourse and artifacts from two different instructional settings using the analytic framework generated on the basis of literature review. The results showed that students felt difficulty particularly in the process of data collection and graph representations. In addition, even though data description has been heavily emphasized for data analysis in statistics education, it is surprisingly discovered that students had a hard time to understand the relationship between data and representations. Also, there were relationships between students' statistical thinking and instructional settings. Even though both groups of students showed difficulty in data collection and graph representations of the data, there were significant differences between the groups in terms of their performance. Whereas students from student-centered learning class outperformed in making decisions considering verification and justification, students from teacher-centered lecture class did better in problems requiring accuracy than the counterpart. The results from the study provide meaningful implications on developing curriculum and instructional methods for statistics education.

• Korean System Dynamics Review
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• v.7 no.1
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• pp.51-65
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• 2006

This research assumes that expanding the depth and range of thinking can be achieved through systems thinking education to the youth. To verify this assumption, degree of expansion of thinking was evaluated after the systems thinking education was done to middle school students in Kyeongi province. As a result, significant statistical difference was found. More variables were presented after systems thinking education. This means education program enhances student's thinking ability. Possibility of systems thinking application can be verified through systems thinking education to the various ranges of students in the future.