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A Framework for Assessing High School Students' Statistical Reasoning.

Shiau Wei Chan1, Zaleha Ismail2, Bambang Sumintono3

  • 1Department of Production and Operation Management, Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia.

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Summary
This summary is machine-generated.

This study introduces a new framework to assess high school students' statistical reasoning in descriptive statistics. The framework, validated with tenth graders, shows consistent reasoning levels across key data analysis constructs.

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Area of Science:

  • Statistics Education
  • Educational Psychology

Background:

  • Existing frameworks for assessing statistical reasoning are incomplete or lack coherence.
  • There is a need for a comprehensive model to understand students' statistical thinking in descriptive statistics.

Purpose of the Study:

  • To develop and validate a statistical reasoning framework for high school students focusing on descriptive statistics.
  • To create a reliable assessment tool based on the developed framework.

Main Methods:

  • Literature synthesis, analysis of prior studies, and student observations informed the initial framework development.
  • A statistical reasoning assessment tool was created and administered to ten tenth-grade students in task-based interviews.
  • The framework and tool were refined and validated through a second round of interviews.

Main Results:

  • The study established a five-level framework (idiosyncratic to integrated process reasoning) and four key constructs (describing, organizing, representing, analyzing data).
  • Student statistical reasoning levels were found to be consistent across the four constructs, confirming the framework's cohesion.
  • The refined assessment tool demonstrated validity in measuring statistical reasoning.

Conclusions:

  • The newly developed statistical reasoning framework offers a complete and coherent model for descriptive statistics.
  • This framework serves as a valuable guide for educators in setting learning goals and designing instruction and assessments.
  • The findings contribute to advancing the field of statistics education by providing a robust tool for evaluating student understanding.