Author
Listed:
- Yipeng Zhao
- Yan Li
- Yuyao Xiao
- Haodong Chang
- Bo Liu
Abstract
The swift incorporation of artificial intelligence (AI) into higher education has significantly propelled the digital transformation of education. This advancement is crucial for educators aiming to augment teaching quality through AI technologies, such as ChatGPT. However, the acceptance of ChatGPT among college students remains underexplored. This paper aims to clarify the determinants influencing college students’ acceptance of ChatGPT and to facilitate its widespread adoption in higher education. To achieve this, we integrate the Technology Readiness Index (TRI), Technology Acceptance Model (TAM), and Theory of Planned Behavior (TPB) to develop a novel research framework. Employing a mixed-method approach that includes PLS-SEM and fsQCA, we analyze data from 298 Chinese college students. Our findings indicate that discomfort and insecurity adversely affect Perceived Ease of Use (PEU) and Perceived Usefulness (PU) in the context of ChatGPT adoption. Additionally, both PEU and PU positively impact attitudes, which, in conjunction with Subjective Norms (SN) and Perceived Behavioral Control (PBC), bolster the intention to accept ChatGPT. Insights from fsQCA reveal that the acceptance of ChatGPT among students is not driven by a singular factor but by an amalgamation of these elements, underscoring the complex nature of technology adoption. The paper concludes with practical recommendations for educators and designers to refine curriculum design and teaching methodologies, boost student engagement and learning efficacy, and promote the broader adoption of educational technology.
Suggested Citation
Yipeng Zhao & Yan Li & Yuyao Xiao & Haodong Chang & Bo Liu, 2024.
"Factors Influencing the Acceptance of ChatGPT in High Education: An Integrated Model With PLS-SEM and fsQCA Approach,"
SAGE Open, , vol. 14(4), pages 21582440241, October.
Handle:
RePEc:sae:sagope:v:14:y:2024:i:4:p:21582440241289835
DOI: 10.1177/21582440241289835
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:sagope:v:14:y:2024:i:4:p:21582440241289835. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.