Using data analysis projects to promote statistical thinking in an introductory statistics course: a basis for curriculum materials development
Statistical thinking has long been a topic of discussion and a generally agreed upon goal for statistics instruction. Statistics involves distinctive and powerful ways of thinking. Statistics is a general intellectual method that applies wherever data, variation, and chance appear. Any introductor...
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| Format: | Article |
| Language: | English |
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Association of Indonesian Scholars of History Education (ASPENSI)
2014
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| Online Access: | http://irep.iium.edu.my/42219/ http://irep.iium.edu.my/42219/ http://irep.iium.edu.my/42219/1/06.nik_.suryani.uiim_.my_.8.14.pdf |
| Summary: | Statistical thinking has long been a topic of discussion and a generally agreed upon goal for statistics
instruction. Statistics involves distinctive and powerful ways of thinking. Statistics is a general intellectual method
that applies wherever data, variation, and chance appear. Any introductory course should take as its main goal helping
students to learn the basic elements of statistical thinking. Many advanced courses would be improved by a more
explicit emphasis on those same basic elements. Those elements were described as: the need for data; the importance
of data production; the omnipresence of variability; and the quantification and explanation of variability. The use of
data analysis projects provides also students with the opportunity to demonstrate their ability to apply and integrate
statistical knowledge and skills in analysing information statistically. This paper will describe the projects and types
of statistical analysis that had been selected by 31 counselling students enrolled in an introductory statistics course
at the undergraduate level. Content analysis was carried out on their final report of the projects and survey was used
to elicit their experiences of working on the projects. These findings will eventually be the basis for the development
of curriculum materials to help instructors and their students implement data analysis projects in their respective
classrooms.
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