Common origins of diverse misconceptions: cognitive principles and the development of biology thinking
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Many ideas in the biological sciences seem especially difficult to understand, learn, and teach successfully. Our goal in this feature is to explore how these difficulties may stem not from the complexity or opacity of the concepts themselves, but from the fact that they may clash with informal, intuitive, and deeply held ways of understanding the world that have been studied for decades by psychologists. We give a brief overview of the field of developmental cognitive psychology. Then, in each of the following sections, we present a number of common challenges faced by students in the biological sciences. These may be in the form of misconceptions, biases, or simply concepts that are difficult to learn and teach, and they occur at all levels of biological analysis (molecular, cellular, organismal, population, and ecosystem). We then introduce the notion of a cognitive construal and discuss specific examples of how these cognitive principles may explain what makes some misconceptions so alluring and some biological concepts so challenging for undergraduates. We will argue that seemingly unrelated misconceptions may have common origins in a single underlying cognitive construal. These ideas emerge from our own ongoing cross-disciplinary conversation, and we think that expanding this conversation to include other biological scientists and educators, as well as other cognitive scientists, could have significant utility in improving biology teaching and learning.
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We often think and deliberate about intelligence with an anthropocentric conception of our own intelligence as an obvious and unambiguous reference.
“We often think and deliberate about intelligence with an anthropocentric conception of our own intelligence in mind as an obvious and unambiguous reference.”
From Human- versus Artificial Intelligence (2021) · cites this paper as Coley and Tanner, 2012
The section “Misconceptions Related to Anthropocentric Thinking” describes using humans as a familiar reference when reasoning about unfamiliar biological species or processes. It does not address deliberation about intelligence or characterize human intelligence as an obvious, unambiguous reference. (LLM, conf=0.85)
Experimental — accuracy not yet measuredWe tend to use this anthropocentric conception as a basis for reasoning about other, less familiar phenomena of intelligence, such as other forms of biological and artificial intelligence.
“We tend to use this conception as a basis for reasoning about other, less familiar phenomena of intelligence, such as other forms of biological and artificial intelligence (Coley and Tanner, 2012).”
From Human- versus Artificial Intelligence (2021) · cites this paper as Coley and Tanner, 2012
The section “Misconceptions Related to Anthropocentric Thinking” describes reasoning about unfamiliar biological species or processes by analogy to humans. It does not address reasoning about intelligence specifically or extend the point to artificial intelligence. (LLM, conf=0.88)
Experimental — accuracy not yet measuredPrior literature advocated for interdisciplinary, collaborative research between biology education researchers and biology learning sciences, developmental cognitive psychologists, and other discipline-based education researchers to bring diverse perspectives, resulting in more and better solutions.
“For example, prior literature advocated for interdisciplinary, collaborative research between biology education researchers and biology learning sciences [49], developmental cognitive psychologists [50], and other discipline-based education researchers (e.g., physics education, chemistry education, geosciences education [51] to bring diverse perspectives, viewpoints, experiences, and expertise to”
From "It let me merge my love of teaching with research": A qualitative investigation of the career pathways of biology education researchers. (2024) · cites this paper as [50]
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Experimental — accuracy not yet measuredA(G)I definitions use human intelligence as a central basis or analogy for reasoning about A(G)I.
“Finally, like what is also frequently seen in the field of biology, these A(G)I definitions use human intelligence as a central basis or analogy for reasoning about the—less familiar—phenomenon of A(G)I (Coley and Tanner, 2012).”
From Human- versus Artificial Intelligence (2021) · cites this paper as Coley and Tanner, 2012
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References 57 · Cited by 193
- Authors
- Coley, J. D., & Tanner, K. D.
- Affiliations
- Northeastern University (US)
- San Francisco State University (US)
- Corresponding author
- Tanner, Kimberly D.
- ORCID
- Coley, John D.
- Venue
- CBE—Life Sciences Education
- Published
- 2012-09
- Volume
- 11
- Issue
- 3
- Pages
- 209-215
- ISSN
- 1931-7913 (ISSN-L)
- PMC
- PMC3433289
- OpenAlex
- W2137607910
- Cited by
- 193
- References
- 57
- Citations by year
- 2026: 10 · 2025: 19 · 2024: 19 · 2023: 18 · 2022: 20 · 2021: 22 · 2020: 15 · 2019: 19 · 2018: 12 · 2017: 11 · 2016: 8 · 2015: 5 · 2014: 6 · 2013: 9
- FWCI
- 31.09
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc-sa
- Locations
- CBE—Life Sciences Education (publishedVersion, cc-by-nc-sa)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion, cc-by-nc-sa)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Education › Science Education and Pedagogy
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Evolution and Science Education
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Keywords
- misconceptions, biology education, cognitive construal, intuitive thinking, cognitive biases, undergraduate biology students, conceptual change, teaching biology
- MeSH terms
- Biology, Cognition, Humans, Learning, Psychology, Thinking, Ecosystem, Comprehension
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