A study of developing administrative Staff's conceptual understanding of generative artificial intelligence through professional Development: Evaluation of a course using tests, surveys and thematic analysis of reflective writings

Emerging research underscores the growing importance of artificial intelligence (AI) literacy for administrative staff as AI technologies continue to reshape the labor market. However, there remains a limited study about the curriculum components of AI literacy for administrative staff. This study a...

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Bibliographic Details
Main Authors: Siu Cheung Kong, Wenxi Hu
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:Computers and Education: Artificial Intelligence
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Online Access:http://www.sciencedirect.com/science/article/pii/S2666920X25000840
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Summary:Emerging research underscores the growing importance of artificial intelligence (AI) literacy for administrative staff as AI technologies continue to reshape the labor market. However, there remains a limited study about the curriculum components of AI literacy for administrative staff. This study aims to bridge this gap by designing and evaluating a professional development programme for administrative staff grounded in a four-dimensional AI literacy framework. A total of 62 administrative staff from diverse professional backgrounds participated in a 30-h course on understanding Generative Artificial Intelligence (GenAI) and its applications. Pre- and post-course conceptual tests and acceptance surveys demonstrated significant improvements in participants' conceptual understanding of GenAI as well as acceptance of using GenAI. Additionally, a thematic analysis of participants’ self-reflective writing revealed increased awareness of the importance of developing metacognitive abilities in using GenAI tools, increased acceptance of using AI tools at workplace, and heightened social awareness regarding AI integration in the workplace. This study contributes to both empirical research and theory-building by providing a structured approach to AI literacy development, tailored for administrative professionals. The findings offer a framework for equipping administrative staff with the essential skills needed for AI-integrated workplaces, reducing barriers to AI literacy across diverse sectors.
ISSN:2666-920X