A Study on Undergraduate Students' Willingness to Use GAI Based on the Technology Acceptance Model 3

The rapid development and widespread application of generative artificial intelligence (GAI) have provided university students with personalized learning opportunities. This study offers a new perspective on the application of GAI in the educational field by analyzing undergraduate students' technology acceptance of generative artificial intelligence. Using the Technology Acceptance Model (TAM3), this study examines students' usage behaviors of generative AI. Data were collected through a survey, and structural equation modeling was employed for systematic analysis. The findings reveal that university students demonstrate a high level of acceptance of generative artificial intelligence. This study provides new insights into the application of generative AI in education and holds significant theoretical and practical implications for promoting the use of generative AI among undergraduate students.

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Publication Details

Published
2025-04-18
DOI
https://doi.org/10.1109/cste64638.2025.11092086
Citations
1
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
4.17

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article

A Study on Undergraduate Students' Willingness to Use GAI Based on the Technology Acceptance Model 3

Shi-Qing Peng, Zhihai Qiu, Junyu Lu
1 citations
Technology Adoption and User Behaviour
4.17
article

A Study on Undergraduate Students' Willingness to Use GAI Based on the Technology Acceptance Model 3

Shi-Qing Peng, Zhihai Qiu, Junyu Lu
article en
1 citations

Abstract

The rapid development and widespread application of generative artificial intelligence (GAI) have provided university students with personalized learning opportunities. This study offers a new perspective on the application of GAI in the educational field by analyzing undergraduate students' technology acceptance of generative artificial intelligence. Using the Technology Acceptance Model (TAM3), this study examines students' usage behaviors of generative AI. Data were collected through a survey, and structural equation modeling was employed for systematic analysis. The findings reveal that university students demonstrate a high level of acceptance of generative artificial intelligence. This study provides new insights into the application of generative AI in education and holds significant theoretical and practical implications for promoting the use of generative AI among undergraduate students.

South China Normal University (CN), Central China Normal University (CN)
National Social Science Fund of China
Quality Education
Openalex Percentile: Top 5%
Technology Adoption and User Behaviour
4.17
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