Evaluating the Statistics Courses in Terms of the Statistical Literacy: Didactic Pathways of Pre-Service Mathematics Teachers
Bulent Guven 1, Adnan Baki 1, Neslihan Uzun 2 * , Zeynep Medine Ozmen 1, Zeynep Arslan 1
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1 Trabzon University, TURKEY2 Recep Tayyip Erdogan University, TURKEY* Corresponding Author

Abstract

This study intends to determine the statistical literacy levels of pre-service mathematics teachers and to evaluate the contribution of the statistics courses in the elementary mathematics education curriculum to statistical literacy. A mixed methods research design was adopted. The study group consisted of 202 pre-service mathematics teachers enrolled in the Statistics and Probability course. In the data collection process, a pre-test and post-test was administered to determine the pre-service teachers’ statistical literacy before and after the statistical course, and classroom observations were performed to identify the contribution of the statistics course to statistical literacy. The Rasch model was used for validity-reliability analyses, and one-way ANOVA tests were used to analyze the quantitative data. Content analysis was utilized in the analysis of qualitative data, which revealed that statistical literacy levels of pre-service teachers are generally low, generally influencing the competence of pre-service teachers. The pre-service teachers failed in the sample selection component in the pre-test and data interpretation in the post-test, while they were more successful with table and graphs in the pre-test and sample selection in the post-test. The comparative analysis of revealed statistically significant differences in favor of U4 in the pre-test, but in favor of U1 in the post-test. It was concluded that practices included in the statistics lessons could be effective on these differences.

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

INT ELECT J MATH ED, 2021, Volume 16, Issue 2, Article No: em0627

https://doi.org/10.29333/iejme/9769

Publication date: 07 Mar 2021

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Article Downloads: 1363

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