Science, misinformation, and the role of education
Abstract
“Competent outsiders” must be able to evaluate the credibility of science-based arguments
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Science education is uniquely situated to help students develop knowledge, strategies, and dispositions that improve their abilities to evaluate scientific information in online settings.
“While science education cannot bear the burden of solving these challenges alone, it is uniquely situated to help students develop knowledge, strategies, and dispositions that improve their abilities to evaluate scientific information in online settings (Osborne et al., 2022).”
From Learning to evaluate sources of science (mis)information on the internet: Assessing students' scientific online reasoning (2025) · cites this paper as Osborne et al., 2022
As more students turn to the internet as their dominant source of scientific information, researchers have become increasingly interested in the implications for science education.
“As more students turn to the internet as their dominant source of scientific information, researchers have become increasingly interested in the implications for science education (e.g., Osborne & Pimentel, 2022;Polman et al., 2014;Sharon & Baram-Tsabari, 2020).”
From Learning to evaluate sources of science (mis)information on the internet: Assessing students' scientific online reasoning (2025) · cites this paper as Osborne & Pimentel, 2022
Learning to use criteria to gather evidence about a source's expertise is one way that students can critically evaluate information sources while also acknowledging their epistemic dependence.
“Although such assessments can be challenging, learning to use criteria to gather evidence about a source's expertise is one way that students can critically evaluate information sources while also acknowledging their epistemic dependence (e.g., Anderson, 2011;Duncan et al., 2018;Osborne et al., 2022).”
From Learning to evaluate sources of science (mis)information on the internet: Assessing students' scientific online reasoning (2025) · cites this paper as Osborne et al., 2022
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Skating on Thinning Ice: Backyard Citizen Science for Climate Change Awareness
Sperling, E., & Bowen, G. M. (2025) · Postdigital Science and Education · doi:10.1007/s42438-024-00535-8 · Cited by 1 · see citing works
“…and Pimentel (2022, 2024) argue that science education in schools should work towards developing an understanding of three key concepts: • The enacted social practices of the scientific community used to produce reliable knowledge claims (i.e., science facts) (Osborne and Pimentel 2022; 247).”
InfluentialWhat Makes a Competent Outsider?
Sandoval, W. A., Osborne, J. F., Feinstein, N. W., Voitle, F., Kremer, K., Duncan, R. G., Krishnamoorthy, R., & Tan, E. (2025) · Proceedings. · doi:10.22318/icls2025.131794 · Cited by 1 · see citing works
Self-citationWe Don't Need No Education Misinformation
El‐Samad, H. (2022) · GEN Biotechnology · doi:10.1089/genbio.2022.29071.editorial
Cinco mitos sobre a pesquisa científica em turismo
Santos, G. E. D. O. (2023) · Revista Brasileira de Pesquisa em Turismo · doi:10.7784/rbtur.v17.2750
New Techniques for Limiting Misinformation Propagation
Benreguia, B., Arar, C., Moumen, H., & Merzoug, M. A. (2023) · IEEE Access · doi:10.1109/access.2023.3287807
“To achieve this goal, several techniques and strategies are proposed, including locating the diffusion source [1], fact-checking [2], education [3], collaboration [4], transparency [5] and empowering credible sources [6].”
دور تعليم العلوم في مواجهة التضليل العلمي لدى طلاب الجيل Z
الباز, م. م. م. (2023) · إبداعات تربوية · doi:10.21608/eji.2023.306135
Are there 34,000 human emotions? Deconstructing patterns of scientific misinformation
Polfuß, J. (2024) · Accountability in Research · doi:10.1080/08989621.2024.2393813
“Scientists and knowledge mediators should help provide nonscientific actors with the practical means to verify information, and accurately assess scientific credibility (Asimina and Hans-Jorg Trenz 2021; Osborne and Pimentel 2022).”
Biases toward weight, diet, and exercise expressed by health science students and their professors
Clark, J. E., Wiszniak, M. F., Bicomong, R., Sousa, M., Jolivette, D., & Sirois, E. (2026) · Sport Sciences for Health · doi:10.1007/s11332-026-01764-z
“These findings can have long-term and unintentional impact on the quality of recommendations that might be offered within the holistic care of a patient, where the healthcare provider will assume the role of educator along with the accepted role of healer [4, 6, 8, 10, 11, 34].”
InfluentialRethinking Scientific Literacy Based on Covid-19 Experiences from One Caribbean Country
Nazir, J. (2024) · Contemporary trends and issues in science education · doi:10.1007/978-3-031-78586-3_12
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Wissenschaftsvermittlung und Demokratieverständnis on der hochschulischen Lehre
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Super, L., Qin, J., Zhang, L., et al. (2025) · Natural sciences education · doi:10.1002/nse2.70022
“In this “post-truth” era, misinformation spread is increasingly common, even in science, unfortunately (Osborne & Pimentel, 2022; West & Bergstrom, 2021).”
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Inclusion of climate change and planetary health in masters of public health curricula in the UK
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“Climate change education is especially important to counter dis-and misinformation that hinders the much-needed intersectoral action and political engagement to prepare contemporary societies to the multiple challenges brought in or exacerbated by climate change [37].”
Glaubwürdigkeitsurteile zu medialen Repräsentationen des Klimawandels
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Supporting bilingual scientific argumentation through recorded oral feedback
Archila, P. A., de Mejía, A. T., & Molina, J. A. (2026) · International Journal of Bilingual Education and Bilingualism · doi:10.1080/13670050.2026.2632335
“This is especially valuable today, when people are constantly exposed to ‘the plague of misinformation’ (Osborne and Pimentel 2022, 248).”
Desinformação em Ciências e Educação Científica: Uma Revisão da Literatura
Nicolodi, J. C., da Rosa, C. T. W., & Lima, N. W. (2026) · Revista Brasileira de Pesquisa em Educação em Ciências · doi:10.28976/1984-2686rbpec2026u175205
A Competitive Guidance Topic Propagation Model Based on Evolutionary Game Theory
Wang, R., Deng, L., Chen, L., et al. (2026) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2026.3670502
“However, this process is often affected by false or misleading content, making the guidance of public opinion essential for maintaining social stability [1], [2], [3].”
- Authors
- Osborne, J., & Pimentel, D.
- Affiliations
- Stanford University (US)
- Venue
- Science
- Published
- 2022-10-21
- Volume
- 378
- Issue
- 6617
- Pages
- 246-248
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W4306902094
- Semantic Scholar
- 4b28a4e9466adf2064b2f50235168e1c400cf19d
- Cited by
- 115
- References
- 13
- Citations by year
- 2026: 27 · 2025: 35 · 2024: 30 · 2023: 21 · 2022: 2
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Education › Science Education and Pedagogy
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Strategies and Epistemologies
- Keywords
- scientific misinformation, science education, credibility assessment, public understanding of science
- MeSH terms
- Communication, Competency-Based Education, Humans, Science
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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