Abstract

Based on a synthesis of literature, earlier studies, analyses and observations on high school students, this study developed an initial framework for assessing students’ statistical reasoning about descriptive statistics. Framework descriptors were established across five levels of statistical reasoning and four key constructs. The former consisted of idiosyncratic reasoning, verbal reasoning, transitional reasoning, procedural reasoning, and integrated process reasoning. The latter include describing data, organizing and reducing data, representing data, and analyzing and interpreting data. In contrast to earlier studies, this initial framework formulated a complete and coherent statistical reasoning framework. A statistical reasoning assessment tool was then constructed from this initial framework. The tool was administered to 10 tenth-grade students in a task-based interview. The initial framework was refined, and the statistical reasoning assessment tool was revised. The ten students then participated in the second task-based interview, and the data obtained were used to validate the framework. The findings showed that the students’ statistical reasoning levels were consistent across the four constructs, and this result confirmed the framework’s cohesion. Developed to contribute to statistics education, this newly developed statistical reasoning framework provides a guide for planning learning goals and designing instruction and assessments.

Highlights

  • Today, statistical reasoning has become a ubiquitous part of many disciplines, such as business [1], education, and engineering

  • A statistical reasoning assessment tool was created based upon this initial framework, which was employed during the task-based interview [12]

  • The process of validating the framework was modified from earlier studies [11,16,40,41,42,43] and can be described as follows: 1. Construct the statistical reasoning assessment tool based on the initial framework; 2

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Summary

Introduction

Statistical reasoning has become a ubiquitous part of many disciplines, such as business [1], education, and engineering. Statistical reasoning is a neglected area, compared. This study aims to bridge these gaps by focusing on statistical reasoning about descriptive statistics. In this context, statistical reasoning is defined as ‘the way people reason with statistical ideas and make sense of statistical information. Statistical reasoning is defined as ‘the way people reason with statistical ideas and make sense of statistical information It involves making interpretations based on sets of data or statistical summaries of data, where students need to combine ideas about data and chance to make inferences and interpret statistical results’ [9] (p.101)

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