The Adoption of Artificial Intelligence of Selected International Chinese Educators Enrolled as Graduate Students in the College of Education of St. Paul University Manila

PhD Brian S. Bantugan, Xue Li, Lu Liu, Yang Liu, Xinge Wang, Meiyuan Yang and Xinyuan Zhang
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PhD Brian S. Bantugan: Faculty Member, St. Paul University Manila
Xue Li: Graduate Student, St. Paul University Manila
Lu Liu: Graduate Student, St. Paul University Manila
Yang Liu: Graduate Student, St. Paul University Manila
Xinge Wang: Graduate Student, St. Paul University Manila
Meiyuan Yang: Graduate Student, St. Paul University Manila
Xinyuan Zhang: Graduate Student, St. Paul University Manila

International Journal of Research and Scientific Innovation, 2024, vol. 11, issue 2, 133-146

Abstract: This study explored the past adoption process of artificial intelligence among six Chinese educators enrolled as international graduate students at the College of Education, St. Paul University Manila. It aimed to understand the stages, social facilitators, and relevant institutional structures in their adoption. The participants, educators from the North China School of Science and Technology, responded to seven questions about their AI experience. Written responses were collected on January 17, 2024, and underwent deductive thematic analysis. The findings, validated by participants, contributed insights into the educators’ past AI adoption journey within the academic setting. The study revealed seven stages in AI adoption facilitated by social situations and supported by institutional factors. The adoption of artificial intelligence (AI) by international graduate student educators involves phases from initial exposure to implementation and post-reflection. Decision-making considers compatibility and institutional expectations, while challenges in implementation include managing dual roles. To ensure responsible AI adoption, recommended policies cover ethical guidelines, mandatory training, data privacy, intellectual property, transparency, and misuse prevention. Balanced AI integration, collaboration, and regular training on ethics and societal impact are crucial.

Date: 2024
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