Epistemic metacognition in context: evaluating and learning online information
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Users' ability to critically evaluate information remains crucial for minimising errors.
“This finding suggests that while ChatGPT assistance was not disproportionately misleading, users' ability to critically evaluate information remains crucial for minimising errors (Mason et al., 2010).”
From “ <scp>ChatGPT</scp> can make mistakes. Check important info.” Epistemic beliefs and metacognitive accuracy in students' integration of <scp>ChatGPT</scp> content into academic writing (2025) · cites this paper as Mason et al., 2010
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- Authors
- Mason, L., Boldrin, A., & Ariasi, N.
- Affiliations
- University of Padua (IT)
- Venue
- Metacognition and Learning
- Published
- 2009-07-28
- Volume
- 5
- Issue
- 1
- Pages
- 67-90
- ISSN
- 1556-1623 (ISSN-L)
- 1556-1631
- OpenAlex
- W2065204878
- Cited by
- 139
- References
- 77
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 4 · 2023: 6 · 2022: 10 · 2021: 11 · 2020: 13 · 2019: 3 · 2018: 10 · 2017: 11 · 2016: 15 · 2015: 5 · 2014: 12 · 2013: 11 · 2012: 10
- FWCI
- 11.73
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Metacognition and Learning (publishedVersion)
- Padua Research Archive (University of Padova) (submittedVersion)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Strategies and Epistemologies
- Social Sciences › Education › Science Education and Pedagogy
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Keywords
- online information searching, evaluating online information, epistemological beliefs, prior knowledge, study approaches, online learning, dinosaur extinction, scientific controversy, justification of knowledge, source evaluation, eighth grade students, individual differences
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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