EXAMINING THE STUDENTS' STATISTICAL LITERACY CONCERNING THE REPRESENTATION AND ANALYSIS OF THE DATA AND INTERPRETATION OF THE RESULTS

Date

2023-7

Author

Elma, Sinem Elif

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Statistical literacy is inevitable for conscious citizenship and adjusting to the fastdeveloping world. Students should be able to represent and analyze data and interpret the results before graduating from middle school (Ministry of National Education, 2018). Therefore, the study aims to investigate the statistical literacy levels of eighth graders enrolled in schools in different regions of Turkey regarding an unfamiliar real-life context such as COVID-19 and a familiar real-life context such as daily diet, using the last two statistical process components: representation and analysis of the data and interpretation of the results. The data were collected from 248 eight grade students in different regions of Turkey, including Ankara, Kars, Kayseri, and Istanbul, with convenience sampling. The open-ended survey consisted of a contextual task and twelve questions related to the Covid-19 pandemic and daily diet. The questions were prepared by considering the national curriculum objectives of the Turkish mathematics curriculum (2018) and the National Council of Teachers of Mathematics standards (2000). Data were analyzed with the four-stage framework of Sharma, Doyle, Shandil, and Talakia'atu (2011). Since relational thinking is first expected in level 3, the levels are categorized such that the first two are in the low statistical literacy category, and the last two are in the high statistical literacy category. The results show that in the COVID-19 task, 98.39% of students were found to have low-level statistical literacy, while 1.61% were found to have high- level statistical literacy. In the daily diet task, 91.53% of the students were found to have low-level statistical literacy, while 8.47% had high-level statistical literacy.

Subject Keywords

Statistical Literacy, Representation and Analysis of the Data, Interpretation of Results, Contextual Tasks

URI

https://hdl.handle.net/11511/105124

Collections

Graduate School of Natural and Applied Sciences, Thesis