Cited by 197Digital literacy in educationGender and Technology in EducationLiteracy, Media, and Education

Measuring digital literacy across three age cohorts: Exploring test dimensionality and performance differences

Jin, Kuan-Yu, Reichert, Frank, Cagasan, Louie P., de la Torre, Jimmy, Law, Nancy·2020·Computers & Education

Integrity signals

Registry

Crossref · 10.1016/j.compedu.2020.103968

Cites

54 of 54 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

3 of the 57 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Jin, K.-Y., Reichert, F., Cagasan, L. P., de la Torre, J., & Law, N.
Affiliations
  • University of Hong Kong (HK)
  • University of the Philippines System (PH)
Corresponding author
Reichert, Frank
Venue
Computers & Education
Publisher
Elsevier BV
Published
2020-11
Volume
157
Pages
103968
ISSN
0360-1315 (ISSN-L)
OpenAlex
W3040322941
Cited by
178
References
57
Citations by year
2026: 25 · 2025: 39 · 2024: 31 · 2023: 41 · 2022: 23 · 2021: 15 · 2020: 4
FWCI
19.52
Type
journal article
Language
en
Open access
closed
Locations
Computers & Education (publishedVersion)
Funders
Research Grants Council, University Grants Committee
Topics
  • Physical Sciences › Computer Science › Information Systems › Digital literacy in education
  • Social Sciences › Gender Studies › Gender and Technology in Education
  • Social Sciences › Arts and Humanities › Literature and Literary Theory › Literacy, Media, and Education
Keywords
digital literacy, age cohorts, test dimensionality, gender gap, elementary school students, high school students, item response models, digital literacy assessment

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 ›

Are you an author, or do you see a problem with this page? Request a review