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Comparative Perspectives on Generative AI Integration: Student Experiences in an Asia–Pacific, European, and African Context
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DOI：10.1007/s40299-026-01136-8.png)
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Abstract
En 中文
The rapid integration of generative artificial intelligence (GenAI) into higher education has raised critical questions regarding cross-cultural variability in adoption and ethical perception. This study investigates university students’ GenAI use across three distinct socio-technical contexts: China (state-driven technological ecosystem), Ireland (EU regulatory framework), and Kenya (emerging digital economy). Grounded in a multi-dimensional contextual framework integrating an adapted Technology Acceptance Model (TAM), we examined how national infrastructures, educational pressures, and governance discourses shape student engagement. A mixed-methods survey was administered simultaneously to 580 undergraduates and postgraduates. Multivariate analysis of variance revealed significant cross-national differences in usage frequency, perceived academic impact, and ethical concerns (p < 0.001). Chinese students reported one of the highest usage frequencies (alongside Kenyan students) but the lowest ethical concerns, utilizing predominantly local platforms (e.g., DeepSeek). Irish students demonstrated moderate usage with heightened ethical vigilance regarding academic integrity. Kenyan students exhibited highest AI familiarity despite resource constraints, leveraging AI to bridge educational gaps. Findings demonstrate that GenAI adoption is fundamentally mediated by contextual factors rather than cultural typologies alone. We propose context-sensitive policy frameworks that move beyond universalist approaches to AI integration in higher education. This study contributes empirical evidence for culturally responsive AI governance in diverse educational ecosystems. Comparative study of GenAI adoption across Asia–Pacific, Europe, and Africa. Significant cross-national differences in usage, impact, and ethics. China has the highest usage, low ethics concerns and uses mostly DeepSeek. Ireland has a moderate usage, high ethics concerns and uses mainly ChatGPT. Kenya has the highest familiarity despite constraints, leveraging AI to bridge gaps. Contextual factors mediate adoption more than cultural dimensions.
Keywords:
Cross-cultural projects
Cultural and social implications
Teaching/learning strategies
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