Cited by 40Educational Games and GamificationInnovations in Medical EducationInnovative Teaching Methods

Fun with pharmacology: Winning students over with kahoot! Game-based learning

Bryant, Susan G., Correll, Jennifer M., Clarke, Brandy M.·2018·Journal of Nursing Education

Integrity signals

Registry

Crossref · 10.3928/01484834-20180420-15

Cites

3 of 3 references verified0 citation errors · 0 not checkable

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Claims the paper makes

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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?

  • The process of creating realistic incorrect answers requires students to think critically.

    “This process requires students to think critically (Bryant et al., 2018).”

    From The effect of using Kahoot! for learning – A literature review (2020) · cites this paper as Bryant et al., 2018

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Authors
Bryant, S. G., Correll, J. M., & Clarke, B. M.
Affiliations
Davidson County Community College (US)
Venue
Journal of Nursing Education
Publisher
SLACK, Inc.
Published
2018-05
Volume
57
Issue
5
Pages
320-320
ISSN
  • 0148-4834 (ISSN-L)
  • 1938-2421
OpenAlex
W2801979336
Cited by
40
References
3
Citations by year
2025: 3 · 2024: 5 · 2023: 9 · 2022: 8 · 2021: 7 · 2020: 5 · 2019: 3
FWCI
7.37
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Nursing Education (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Psychology › Developmental and Educational Psychology › Educational Games and Gamification
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
  • Social Sciences › Education › Innovative Teaching Methods
Keywords
Kahoot, game-based learning, pharmacology education, nursing students, student engagement, gamification
MeSH terms
Education, Nursing, Humans, Pharmacology, Teaching, Video Games

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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.

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