Can Students Evaluate Online Sources? Learning From Assessments of Civic Online Reasoning
Abstract
To be an informed citizen in today’s information-rich environment, individuals must be able to evaluate information they encounter on the Internet. However, teachers currently have limited options if they want to assess students’ evaluations of digital content. In response, we created a range of short tasks that assess students’ civic online reasoning—the ability to effectively search for, evaluate, and verify social and political information online. Assessments ranged from paper-and-pencil tasks to open Internet search tasks delivered via Google Forms. We outline a process of assessment development in which middle school, high school, and college students in 12 states completed tasks. We present a series of representative tasks and analyses of trends in student performance. Across tasks and grade levels, students struggled to effectively evaluate online claims, sources, and evidence. These results point to a need for curriculum materials that support students’ development of civic online reasoning competencies.
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The assessment rubrics were designed and iterated following a process similar to McGrew et al. (2018), with feedback from Mr. Lewis and another researcher.
“I followed a process similar to McGrew et al. (2018) to design and iterate on each assessment and associated rubric, with feedback from Mr. Lewis and another researcher.”
From Learning to evaluate sources of science (mis)information on the internet: Assessing students' scientific online reasoning (2025) · cites this paper as McGrew et al. (2018)
Researchers have demonstrated that the COR framework supports high school students with effectively evaluating information on websites and social media posts by providing them with stronger heuristics and strategies for making decisions about what information to pay attention to online.
“Researchers have demonstrated that the COR framework supports high school students with effectively evaluating information on websites and social media posts by providing them with stronger heuristics and strategies for making decisions about what information to pay attention to online (Breakstone et al., 2021;McGrew et al., 2018;McGrew, 2020;Wineburg 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 McGrew et al., 2018
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- Authors
- McGrew, S., Breakstone, J., Ortega, T., Smith, M., & Wineburg, S.
- Affiliations
- Stanford University (US)
- Corresponding author
- McGrew, Sarah
- Venue
- Theory & Research in Social Education
- Publisher
- Informa UK Limited
- Published
- 2018-01-08
- Volume
- 46
- Issue
- 2
- Pages
- 165-193
- ISSN
- 0093-3104 (ISSN-L)
- 2163-1654
- OpenAlex
- W2782804901
- Cited by
- 533
- References
- 42
- Citations by year
- 2026: 65 · 2025: 62 · 2024: 76 · 2023: 84 · 2022: 66 · 2021: 69 · 2020: 65 · 2019: 29 · 2018: 17
- FWCI
- 102.42
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Theory & Research in Social Education (publishedVersion)
- Funders
- Robert R. McCormick Foundation
- Spencer Foundation
- Topics
- Social Sciences › Sociology and Political Science › Educator Training and Historical Pedagogy
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Strategies and Epistemologies
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Literacy, Media, and Education
- Keywords
- evaluating online sources, information literacy, digital citizenship, citizenship education, assessment development, online information evaluation, political information, social information, student achievement trends, grade level differences, curriculum materials
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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