Investigation of students' use of online information in higher education using eye tracking
Open accessAbstract
To successfully learn using freely available (and non-curated) Internet resources, university students need to search for, critically evaluate and select online information, and verify sources (defined as Critical Online Reasoning, COR). Recent research indicates substantial deficits in COR skills among higher education students. To support students in learning how to critically use online information for their learning, it is necessary to better understand the strategies and practices that might elicit less critically-reflective judgments about online information and thus account for such deficits. To this end, using eye tracking data, we investigate how the COR behaviors of students who critically-reflectively evaluate the credibility of online information (‘high performers’) differ from those of students who do not critically-reflectively evaluate it (‘low performers’): 19 students were divided into high and low performers according to their performance in the newly developed Critical Online Reasoning Assessment (CORA). The fixation and dwell times of both groups during CORA task processing were compared regarding time spent on the different processing steps and eye movements on the visited web pages. The results show noticeable differences between the two groups, indicating that low performers indeed approached the task rather heuristically than systematically, and that COR skills require targeted and effective training in higher education.
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Students must actively develop competencies to evaluate, verify, and ethically use information in academically responsible ways.
“Empirical research consistently shows that digital abundance does not automatically translate into informed judgment; rather, students must actively develop competencies to evaluate, verify, and ethically use information in academically responsible ways (Aladsani, 2025; Kunz et al., 2024; Molerov et al., 2020; Surducan and Valadas, 2025).”
From Information competence and critical thinking in digital environments evidence from university students in Kazakhstan (2026) · cites this paper as Kunz et al., 2024
The Research background and study objective section says abundant online information is not necessarily reliable and that students need to evaluate its credibility and verify it against other sources. It also calls for support in learning to use online information critically. The passages do not address ethical use or academic responsibility, so those parts of the claim are not supported by this source. (LLM, conf=0.88)
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Cited by
Sorted by citations
From credibility to reliance: Trust in generative AI as an academic information source.
Pudasaini, S. (2026) · Information Development · doi:10.1177/02666669261468286 · Cited by 3 · see citing works
Yrymbayeva, N., Yermekova, M., Tezekova, O., Issatayeva, B., Zhubandykova, A., & Tuxanbayev, A. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1809360 · Cited by 2 · see citing works
- Authors
- Kunz, A.-K., Zlatkin-Troitschanskaia, O., Schmidt, S., Nagel, M.-T., & Brückner, S.
- Affiliations
- Johannes Gutenberg University Mainz (DE)
- Venue
- Smart Learning Environments
- Published
- 2024-10-09
- Volume
- 11
- Issue
- 1
- ISSN
- 2196-7091 (ISSN-L)
- OpenAlex
- W4403222223
- Cited by
- 12
- References
- 4
- Citations by year
- 2026: 8 · 2025: 4
- FWCI
- 5.94
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Smart Learning Environments (publishedVersion, cc-by)
- Gutenberg Open Science (submittedVersion, cc-by-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Gutenberg Open Science (cc-by)
- Funders
- RMU Initiativfond
- Johannes Gutenberg-Universität Mainz
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Strategies and Epistemologies
- Social Sciences › Library and Information Sciences › Library Science and Information Literacy
- Social Sciences › Education › Education and Critical Thinking Development
- Keywords
- online information evaluation, source credibility, university students, eye tracking, heuristic processing, information literacy, online learning resources
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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