K-8 Preservice Teachers’ Statistical Thinking When Determining Best Measure of Center

Ha Nguyen, Eryn M. Maher, Gregory Chamblee, Sharon Taylor
490 288

Abstract


The purpose of this study was to determine K-8 preservice teacher (PST) candidates’ statistical thinking when selecting the best center representation for the given data. Forty-four PSTs enrolled in a Statistics and Probability for K-8 Teachers course in a university located in the southeastern region of the United States were asked to complete a 2007 National Assessment of Educational Progress test item. All 44 PSTs’ data were qualitatively analyzed for correctness and statistical thinking strategies used. Findings were that most PSTs either incorrectly selected the mean, rather than median, as the best measure of center for the given data or did not use appropriate statistical reasoning when explaining their answers. Future research includes modifying the explanation component so PSTs must better explain their statistical thinking for their choice of best measure of center using the context of the problem. Future research could also include implementing a pre- and post-test design with the post-test item embedded in the final exam. This design will provide additional understanding of how much knowledge PSTs bring to the course versus how much they learn in the course and provide incentive for giving thoughtful consideration for their answers.

Keywords


Preservice teachers, Statistics, Mean, Median

Full Text:

PDF

References


Nguyen, H., Maher, E. M., Chamblee, G., & Taylor, S. (2023). K-8 preservice teachers’ statistical thinking when determining best measure of center. International Journal of Education in Mathematics, Science, and Technology (IJEMST), 11(2), 440-454. https://doi.org/10.46328/ijemst.2365




DOI: https://doi.org/10.46328/ijemst.2365

Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 International Journal of Education in Mathematics, Science and Technology

 

 
International Journal of Education in Mathematics, Science and Technology (IJEMST) 
 
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Editors: Mack Shelley & Ismail Sahin

Place of Publication: Turkey & Name of Publisher: Ismail Sahin

ISSN: 2147-611X (Online)