Keyword: AI literacy

ABSTRACT: Generative artificial intelligence (AI) is rapidly transforming important areas of human activity, yet adults’ acceptance of generative AI applications remains insufficiently understood. This cross-sectional study examined the acceptance of generative AI applications among 460 adults recruited through online convenience sampling. Data were collected using the generative artificial intelligence acceptance scale (GAIAS), a validated instrument based on dimensions derived from the unified theory of acceptance and use of technology (UTAUT). The scale comprised four dimensions: performance expectancy, effort expectancy, facilitating conditions, and social influence. Participants reported moderate to high overall acceptance of generative AI. Effort expectancy, reflecting perceived ease of use (PEOU), received the highest mean score, followed by performance expectancy, reflecting perceived usefulness (PU), whereas social influence received the lowest mean score. This descriptive pattern indicates that perceived usability and usefulness were rated more positively than perceived social influence within the present sample. After Holm-Bonferroni correction across the 25 primary comparisons, statistically significant group differences remained for age and educational level in overall generative AI acceptance, performance expectancy, and effort expectancy. No multiplicity-adjusted differences were identified according to gender, personal computer ownership, or previous computer training. The age- and education-related findings should not be interpreted as evidence of linear relationships, independent effects, or causation. Within this digitally connected convenience sample, the findings indicate that PEOU and PU were more prominent dimensions of generative AI acceptance than social influence. Age- and education-related group differences were also observed. However, the cross-sectional design, online convenience sampling, and marked subgroup imbalances limit causal interpretation and generalizability to the wider adult population. The findings may nevertheless inform the development of accessible generative AI tools and targeted digital-literacy initiatives.

ABSTRACT: The rapid integration of artificial intelligence (AI) into higher education is reshaping how future educators are prepared for multilingual, multicultural, and ethically complex environments. This study employed a mixed-methods sequential explanatory design to investigate how educators and students in Luxembourg and Ukraine perceive and adopt AI in teacher preparation. In Luxembourg, AI was largely framed as a tool to extend inclusive, multilingual practices and institutional innovation, whereas in Ukraine, it was often adopted out of necessity under conditions of crisis and infrastructural disruption. Quantitative analyses demonstrated that perceived benefits of AI were positively correlated with readiness for instructional integration (r = 0.61, p < .001), while ethical concerns were negatively correlated with willingness to adopt AI (r = –0.45, p < .001). No significant group differences were observed in overall reported levels of ethical concern (t(140) = 1.25, p = .21), though qualitative findings revealed striking contrasts in the nature of these concerns. Luxembourgish participants expressed preventative concerns about quality and pedagogy, while Ukrainian participants described immediate ethical dilemmas shaped by wartime conditions, including studying in bomb shelters and balancing personal safety with academic integrity. Findings highlight that while AI can enhance instructional innovation, it simultaneously amplifies inequalities through language bias and access gaps. The study contributes by linking empirical insights to instructional design frameworks (ADDIE, TPACK) and multicultural education theory, offering concrete guidance for teacher preparation in both stable and crisis-affected contexts.