Full Text (PDF)
Abstract
In the 21st century, statistical thinking has become necessary for all citizens as this skill is vital for societal literacy. Students with statistical thinking will grasp and apply the problem’s context to develop research and draw conclusions, as well as the coherence of the whole process from asking questions to collecting data, evaluating, and testing hypotheses. Although statistical thinking is increasingly in demand in various emerging vocations, students and teachers find statistics challenging to understand. Thus, the study examines the level of statistical thinking of the process of describing data, organizing and reducing data, representing data, and analyzing and interpreting data among high school students based on gender. The statistical thinking test modification of the framework validation test, code, and subprocess reference was used to collect research data from 35 grade 10 students. The research data were statistically analyzed using the statistical package for social sciences version 23 software through descriptive and inferential statistics, specifically an independent t-test analysis. The findings revealed that none of the students achieved an analytical level of understanding; instead, their general statistical thinking skills were at the transitional level, followed by the idiosyncratic and quantitative levels. The findings also demonstrated no statistically significant gender-related disparities in students’ statistical thinking. The study proposes several recommendations, including the necessity of connecting statistical activities to the reality of students’ life and area of study and emphasizing practical rather than theoretical aspects.
License
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
EURASIA J Math Sci Tech Ed, Volume 20, Issue 4, April 2024, Article No: em2421
https://doi.org/10.29333/ejmste/14358
Publication date: 01 Apr 2024
Online publication date: 14 Mar 2024
Article Views: 1286
Article Downloads: 779
Open Access References How to cite this article