Between Regulation and Accessibility: How Chinese University Students Navigate Global and Domestic Generative AI

TL;DR

This study explores how Chinese university students navigate access to global and domestic generative AI tools amidst regulatory barriers, highlighting their strategies, challenges, and the cultural factors influencing AI adoption in education.

Contribution

It provides new insights into AI adoption in non-Western contexts, emphasizing political, linguistic, and cultural influences on students' interactions with generative AI.

Findings

Students use workarounds like VPNs to access global AI tools.

Domestic AI tools face content filtering and output limitations.

Accessibility and cultural relevance influence AI engagement.

Abstract

Despite the rapid proliferation of generative AI in higher education, students in China face significant barriers in accessing global tools like ChatGPT due to regulations and constraints. Grounded in the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model, this study employs qualitative interviews to investigate how Chinese university students interact with both global and domestic generative AIs in the learning process. Findings reveal that engagement is shaped by accessibility, language proficiency, and cultural relevance. Students often employ workarounds (e.g., VPNs) to access global generative AIs, raising ethical and privacy concerns. Domestic generative AIs, while offering language and cultural advantages, are limited by content filtering and output constraints. This research contributes to understanding generative AI adoption in non-Western contexts by highlighting the complex interplay of political, linguistic, and cultural factors. It advocates for human-centered, multilingual, domestic context-sensitive AI integration to ensure equitable and inclusive digital learning environments.