Journal of Statistics and Data Science Education (May 2022)

Think-Aloud Interviews: A Tool for Exploring Student Statistical Reasoning

  • Alex Reinhart,
  • Ciaran Evans,
  • Amanda Luby,
  • Josue Orellana,
  • Mikaela Meyer,
  • Jerzy Wieczorek,
  • Peter Elliott,
  • Philipp Burckhardt,
  • Rebecca Nugent

DOI
https://doi.org/10.1080/26939169.2022.2063209

Abstract

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Think-aloud interviews have been a valuable but underused tool in statistics education research. Think-alouds, in which students narrate their reasoning in real time while solving problems, differ in important ways from other types of cognitive interviews and related education research methods. Beyond the uses already found in the statistics literature—mostly validating the wording of statistical concept inventory questions and studying student misconceptions—we suggest other possible use cases for think-alouds and summarize best-practice guidelines for designing think-aloud interview studies. Using examples from our own experiences studying the local student body for our introductory statistics courses, we illustrate how research goals should inform study-design decisions and what kinds of insights think-alouds can provide. We hope that our overview of think-alouds encourages more statistics educators and researchers to begin using this method. Supplementary materials for this article are available online.

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