Cited by 118Artificial Intelligence in EducationArtificial Intelligence in Healthcare and EducationArtificial Intelligence Applications

Generative Artificial Intelligence in Education, Part One: the Dynamic Frontier

Hsu, Yu-Chang, Ching, Yu-Hui·2023·TechTrends

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Registry

Crossref · 10.1007/s11528-023-00863-9

Cites

20 of 20 references verified0 citation errors · 0 not checkable

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  • The majority of existing work on ChatGPT in academia consists of conceptual and opinion-based discussions and quantitative surveys aimed at specific groups.

    “The majority of existing work consists of conceptual and opinion-based discussions (e.g., Farrelly & Baker, 2023;Hsu & Ching., 2023;Sohail et al., 2023;Yu, 2023), along with quantitative surveys aimed at specific groups (e.g., Hammour et al., 2023;Tangadulrat et al., 2023).”

    From Widen the debate: What is the academic community’s perception on ChatGPT? (2024) · cites this paper as Hsu & Ching., 2023

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Authors
Hsu, Y.-C., & Ching, Y.-H.
Affiliations
Boise State University (US)
Corresponding author
Hsu, Yu-Chang
Venue
TechTrends
Published
2023-06-07
Volume
67
Issue
4
Pages
603-607
ISSN
  • 1559-7075 (ISSN-L)
  • 8756-3894
OpenAlex
W4379651111
Cited by
118
References
18
Citations by year
2026: 27 · 2025: 38 · 2024: 41 · 2023: 12
FWCI
27.70
Type
journal article
Language
en
Open access
closed
Locations
  • TechTrends (publishedVersion)
  • Scholar Works (Boise State University) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
Keywords
generative AI, ChatGPT, artificial intelligence in education, educational technology, future of education, AI ethics, technology adoption

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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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