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Generative Artificial Intelligence in Education, Part One: the Dynamic Frontier
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“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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“Maximizing the benefits while being cautious of its potential limitations is essential (Sallam, 2023).”
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“…questions, support students to conduct individual/collaborative learning and research with human peers (Cooper, 2023; Ye et al., 2023) or with the chatbot (e.g., Pavlik, 2023), or help plan for creative problem solving through generating ideas/concepts for facilitating discussions (Ray, 2023).”
BackgroundChatGPT for Language Teaching and Learning
Kohnke, L., Moorhouse, B. L., & Zou, D. (2023) · RELC Journal · doi:10.1177/00336882231162868 · Cited by 1,371 · cited 2×
“With the natural language capability and 24/7 availability, tools such as ChatGPT can provide convenient assistance to educators whenever it is needed in efficient and effective ways (Kohnke et al., 2023).”
BackgroundExamining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence
Cooper, G. (2023) · Journal of Science Education and Technology · doi:10.1007/s10956-023-10039-y · Cited by 1,263 · cited 1×
“…be simply assigned as a chatbot to answer questions, support students to conduct individual/collaborative learning and research with human peers (Cooper, 2023; Ye et al., 2023) or with the chatbot (e.g., Pavlik, 2023), or help plan for creative problem solving through generating ideas/concepts…”
BackgroundChatGPT for Education and Research: Opportunities, Threats, and Strategies
Rahman, M. M., & Watanobe, Y. (2023) · Applied Sciences · doi:10.3390/app13095783 · Cited by 1,080 · cited 1×
“…and smooth performance while interacting with users, people of all pro-fessions have leveraged this software tool for various tasks and purposes involving text generation, such as composing simple to relative complex textual codes of computer programming (professional) (Rahman & Watanobe, 2023).”
MethodPavlik, J. V. (2023) · Journalism & Mass Communication Educator · doi:10.1177/10776958221149577 · Cited by 972 · cited 1×
“…questions, support students to conduct individual/collaborative learning and research with human peers (Cooper, 2023; Ye et al., 2023) or with the chatbot (e.g., Pavlik, 2023), or help plan for creative problem solving through generating ideas/concepts for facilitating discussions (Ray, 2023).”
BackgroundInteracting with educational chatbots: A systematic review
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“This can result in biased and unbalanced perspectives reflected in the responses generated by the AI applications based on user queries (Mhlanga, 2023).”
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Metadata
- 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
- Licence
- Locations
- TechTrends (publishedVersion)
- Scholar Works (Boise State University) (submittedVersion)
- Topics
- Social Sciences › Education › 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
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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