Abstract

When reasoning about science studies, people often make causal theory errors by inferring or accepting a causal claim based on correlational evidence. While humans naturally think in terms of causal relationships, reasoning about science findings requires understanding how evidence supports—or fails to support—a causal claim. This study investigated college students’ thinking about causal claims presented in brief media reports describing behavioral science findings. How do science students reason about causal claims from correlational evidence? And can their reasoning be improved through instruction clarifying the nature of causal theory error? We examined these questions through a series of written reasoning exercises given to advanced college students over three weeks within a psychology methods course. In a pretest session, students critiqued study quality and support for a causal claim from a brief media report suggesting an association between two variables. Then, they created diagrams depicting possible alternative causal theories. At the beginning of the second session, an instructional intervention introduced students to an extended example of a causal theory error through guided questions about possible alternative causes. Then, they completed the same two tasks with new science reports immediately and again 1 week later. The results show students’ reasoning included fewer causal theory errors after the intervention, and this improvement was maintained a week later. Our findings suggest that interventions aimed at addressing reasoning about causal claims in correlational studies are needed even for advanced science students, and that training on considering alternative causal theories may be successful in reducing casual theory error.

Highlights

  • Causal claims from research studies shared on social media often exceed the strength of scientific evidence (Haber et al, 2018)

  • Our results suggest that causal theory error is common even in college science courses, but interventions focusing on considering alternative theories to a presented causal claim may be helpful

  • Defining causal theory error The tendency to infer causation from correlation— referred to here as causal theory error—is arguably the most ubiquitous and wide-ranging error found in science literature (Bleske-Rechek et al, 2018; Kida, 2006; Reinhart et al, 2013; Schellenberg, 2020; Stanovich, 2009), classrooms (Kuhn, 2012; Mueller & Coon, 2013; Sloman & Lagando, 2003), and media reports (Adams et al, 2019; Bleske-Rechek et al, 2018; Sumner et al, 2014)

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Summary

Introduction

Causal claims from research studies shared on social media often exceed the strength of scientific evidence (Haber et al, 2018). This occurs in journal articles as well; for example, a recent study in Proceedings of the National Academy of Sciences reported a statistical association between higher levels of optimism and longer life spans, concluding, “...optimism serves as a psychological resource that promotes health and longevity” People (including scientists) readily make a mental leap to infer a causal relationship This error in reasoning—cum hoc ergo propter hoc (“with this, because of this”)— occurs when two coinciding events are assumed to be related through cause and effect. Will you? What critical thinking is needed to assess this claim?

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