Developing a validated assessment of artificial intelligence literacy for Chinese university students based on educational objectives taxonomy
Sijia Han, Yuting Zhang
Zhejiang Normal University
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摘要与影响
Artificial intelligence (AI) literacy is a concept that has received increasing research focus due to the wide integration of AI technology into education. However, there are few available scales for assessing AI literacy in university students that are deeply grounded in a theoretical model. Thus, this study aims to develop and validate a questionnaire for use in the Chinese higher education context. Based on Bloom’s Taxonomy and existing relevant literature, we proposed a five-construct structure with 63 items for this scale. Using survey data from 386 participants, we employed an exploratory factor analysis (EFA) to determine the underlying factorial constructs. A further sample of 401 participants underwent a confirmatory factor analysis (CFA) to test the latent domains, reliability, and validity of the structure. The findings significantly identified an updated AI literacy model with five dimensions, namely AI knowledge, AI application, AI attitude, AI ethics, and AI innovation. This first scale with clear capacity categories for measuring Chinese university students’ levels of AI literacy is regionally unique. It could contribute to the advancement of AI literacy in research, as well as the evaluation of students’ knowledge and skills and the promotion of effective usage in practice.
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计算机 / AIOnline Learning and Analytics
Technology-Enhanced Education Studies · Educational Innovations and Challenges
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