Making Sense of Uncertainty in the Science Classroom A Bayesian Approach

Open Access
Authors
Publication date 10-2022
Journal Science and Education
Volume | Issue number 31 | 5
Pages (from-to) 1239-1262
Number of pages 24
Organisations
  • Faculty of Social and Behavioural Sciences (FMG) - Psychology Research Institute (PsyRes)
Abstract

Uncertainty is ubiquitous in science, but scientific knowledge is often represented to the public and in educational contexts as certain and immutable. This contrast can foster distrust when scientific knowledge develops in a way that people perceive as a reversals, as we have observed during the ongoing COVID-19 pandemic. Drawing on research in statistics, child development, and several studies in science education, we argue that a Bayesian approach can support science learners to make sense of uncertainty. We provide a brief primer on Bayes’ theorem and then describe three ways to make Bayesian reasoning practical in K-12 science education contexts. There are a) using principles informed by Bayes’ theorem that relate to the nature of knowing and knowledge, b) interacting with a web-based application (or widget—Confidence Updater) that makes the calculations needed to apply Bayes’ theorem more practical, and c) adopting strategies for supporting even young learners to engage in Bayesian reasoning. We conclude with directions for future research and sum up how viewing science and scientific knowledge from a Bayesian perspective can build trust in science.

Document type Article
Note In special issue: Trust in Science and Science Education – Part 1. - With supplementary file
Language English
Published at https://doi.org/10.1007/s11191-022-00341-3
Other links https://www.scopus.com/pages/publications/85130633908
Downloads
s11191-022-00341-3 (Final published version)
Supplementary materials
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