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Influence of Pedagogical Beliefs and Perceived Trust on Teachers’ Acceptance of Educational Artificial Intelligence Tools
Abstract
Advancements in artificial intelligence (AI) have stimulated the development of educational AI tools (EAIT). EAITs intelligently assist teachers in formulating better pedagogical decisions or actions for their students. However, teachers are hardly integrating EAITs, and little is known about their perceptions of EAITs. This study seeks to identify human factors that encourage or restrict teachers’ acceptance of EAITs. We propose a revised technology acceptance model incorporating teachers’ pedagogical beliefs and perceived trust in EAITs. Survey data were collected from 215 teachers in South Korea and analyzed using structural equation modeling. The results indicate that teachers with constructivist beliefs are more likely to integrate EAITs than teachers with transmissive orientations. Furthermore, perceived usefulness, perceived ease of use, and perceived trust in EAITs are determinants to be considered when explaining teachers’ acceptance of EAITs. Among them, the most influential determinant of predicting their acceptance was found to be how easily the EAIT is constructed. Significant implications for researchers and stakeholders regarding the development and integration of EAITs are discussed.
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“the results of a study with teachers from South Korea indicate that teachers with constructivist beliefs are more likely to integrate educational AI-based tools than teachers with transmissive orientations [33].”
From ChatGPT for good? On opportunities and challenges of large language models for education (2023) · cites this paper as [33]
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Metadata
- Authors
- Choi, S., Jang, Y., & Kim, H.
- Affiliations
- Korea University (KR)
- Corresponding author
- Kim, Hyeoncheol
- Venue
- International Journal of Human–Computer Interaction
- Publisher
- Informa UK Limited
- Published
- 2022-04-19
- Volume
- 39
- Issue
- 4
- Pages
- 910-922
- ISSN
- 1044-7318 (ISSN-L)
- 1532-7590
- OpenAlex
- W4224229986
- Cited by
- 294
- References
- 64
- Citations by year
- 2026: 75 · 2025: 104 · 2024: 75 · 2023: 30 · 2022: 10
- FWCI
- 54.19
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Human-Computer Interaction (publishedVersion)
- Funders
- National Research Foundation
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Education › Education and Technology Integration
- Keywords
- teacher acceptance, pedagogical beliefs, perceived trust, constructivist beliefs, technology acceptance model, perceived usefulness, perceived ease of use, teacher perceptions, AI integration in education
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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