Artificial Intelligence Literacy Scale: Adapting and Validating a Contextualised Scale for Pre-Service Teachers in Northern Malaysia
DOI:
https://doi.org/10.37134/ejoss.vol12.sp.2.2026Keywords:
Artificial Intelligence Literacy, Pre-Service Teachers, Scale Adaptation and Validation, Back-to-back Translation, Content Validity IndexAbstract
Artificial intelligence (AI) is transforming education, making AI literacy a vital competency for teachers. Defined across four dimensions of awareness, usage, evaluation, and ethics, AI literacy enables educators to integrate technology effectively while upholding ethical standards. Although robust instruments exist internationally, Malaysia lacks culturally and linguistically relevant tools for assessing pre-service teachers’ AI literacy. This study adapted and validated the Artificial Intelligence Literacy Scale (AILS) developed by Wang et al. (2023) for use in northern Malaysia. Using back-to-back translation, expert review, and quantitative survey methods with 385 pre-service teachers, the scale underwent face and content validity testing followed by reliability analysis. Results confirmed strong face validity, unanimous content validity (S-CVI = 1.00), and high internal consistency (α = 0.933 overall). The validated scale provides an essential diagnostic tool for teacher education, supporting curriculum design, research, and policy development aimed at cultivating future-ready educators.
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