Factors Influencing the Reported Intention of Higher Vocational Computer Science Students in China to Use AI After Ethical Training: A Study in Guangdong Province

This paper reports a study conducting an in-depth analysis of the impacts of ethical training on the adoption of AI tools among computer science students in higher vocational colleges. These students will serve as the pivotal human factor for advancing the field of AI. Aiming to explore practical models for integrating AI ethics into computer science education, the research seeks to promote more responsible and effective AI application and therefore become a positive influence in the field. Employing a mixed-methods approach, the study included 105 students aged 20–24 from a vocational college in Guangdong Province, a developed region in China. Based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model, a five-point Likert scale was used to evaluate the participants’ perceptions of AI tool usage based on ethical principles. The Structural Equation Modeling (SEM) results indicate that while participants are motivated to adopt AI technologies in certain aspects, performance expectancy negatively impacts their intention and actual usage. After systematically studying and understanding AI ethics, participants attribute a high proportion of responsibility (84.89%) to objective factors and prioritized safety (27.11%) among eight ethical principles. Statistical analysis shows that habit (β = 0.478, p < 0.001) and hedonic motivation (β = 0.239, p = 0.004) significantly influence behavioral intention. Additionally, social influence (β = 0.234, p = 0.008) affects use behavior. Findings regarding factors that influence AI usage can inform a strategic framework for the integration of ethical instruction in AI applications. These findings have significant implications for curriculum design, policy formulation, and the establishment of ethical guidelines for AI deployment in higher educational contexts.

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Publication Details

Journal
Education Sciences
Published
2025-10-24
DOI
https://doi.org/10.3390/educsci15111431
Citations
2
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
4.73
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article

Factors Influencing the Reported Intention of Higher Vocational Computer Science Students in China to Use AI After Ethical Training: A Study in Guangdong Province

Blandina Manditereza, Ka Ian Chan, Patrick Cheong‐Iao Pang, Huiwen Zou et al.
2 citations
Education Sciences
Ethics and Social Impacts of AI
4.73
article

Factors Influencing the Reported Intention of Higher Vocational Computer Science Students in China to Use AI After Ethical Training: A Study in Guangdong Province

Blandina Manditereza, Ka Ian Chan, Patrick Cheong‐Iao Pang, Huiwen Zou, Yi-Huang Shih
article en
2 citations

Abstract

This paper reports a study conducting an in-depth analysis of the impacts of ethical training on the adoption of AI tools among computer science students in higher vocational colleges. These students will serve as the pivotal human factor for advancing the field of AI. Aiming to explore practical models for integrating AI ethics into computer science education, the research seeks to promote more responsible and effective AI application and therefore become a positive influence in the field. Employing a mixed-methods approach, the study included 105 students aged 20–24 from a vocational college in Guangdong Province, a developed region in China. Based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model, a five-point Likert scale was used to evaluate the participants’ perceptions of AI tool usage based on ethical principles. The Structural Equation Modeling (SEM) results indicate that while participants are motivated to adopt AI technologies in certain aspects, performance expectancy negatively impacts their intention and actual usage. After systematically studying and understanding AI ethics, participants attribute a high proportion of responsibility (84.89%) to objective factors and prioritized safety (27.11%) among eight ethical principles. Statistical analysis shows that habit (β = 0.478, p < 0.001) and hedonic motivation (β = 0.239, p = 0.004) significantly influence behavioral intention. Additionally, social influence (β = 0.234, p = 0.008) affects use behavior. Findings regarding factors that influence AI usage can inform a strategic framework for the integration of ethical instruction in AI applications. These findings have significant implications for curriculum design, policy formulation, and the establishment of ethical guidelines for AI deployment in higher educational contexts.

Education SciencesVol. 15(11)
Minghsin University of Science and Technology (TW), University of the Free State (ZA), Macao Polytechnic University (MO)
Openalex Percentile: Top 5%
Ethics and Social Impacts of AI
4.73
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