ArticleCognitive research: principles and implications2022
Causal theory error in college students' understanding of science studies.
Article in Cognitive research: principles and implications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Causal Interpretations of Correlational Evidence Regarding Violence.Journal of interpersonal violence · 2025Article
- Causal language and inferences in observational rotator cuff database studies published from 2013 to 2022.Journal of orthopaedics · 2025Article
- Numerate people are less likely to be biased by regular science reporting: the critical roles of scientific reasoning and causal misunderstanding.Cognitive research: principles and implications · 2025Article
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Authors and funding
4 authors.
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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.
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