Title: AI-driven personalised curriculum framework for enhancing cross-cultural learning: a case study in Chinese cultural education at Guilin Tourism University

Authors: Yun Tang; Chaohua Su

Addresses: Guilin Tourism University, Guilin, Guangxi, China ' Guangxi Normal University, Guilin, Guangxi, China

Abstract: With the accelerated pace of globalisation and the rapid advancement of artificial intelligence (AI) technology, international student education is confronted with unprecedented opportunities and challenges. Existing international education systems often suffer from a lack of personalisation and static content delivery, failing to fully address the diverse and personalised learning needs of international students. Drawing on the Constructivist Learning Theory and Intercultural Communication Competence Model, and integrating the application scenarios of AI technology, this study proposes a comprehensive AI-driven personalised curriculum framework for enhancing cross-cultural learning, taking Chinese cultural education for international students at Guilin Tourism University as a case study. The framework, structured around four key components - goal setting, content creation, teaching implementation, and evaluation feedback - utilises AI to dynamically tailor learning paths, generate multimodal resources and provide real-time feedback. Implementation at Guilin Tourism University has shown promising results, including increased student engagement, satisfaction and skill acquisition in Chinese cultural understanding. This framework not only improves the learning outcomes of Chinese culture among international students but also offers insights for broader applications in international education and policy-making, highlighting the potential of AI to revolutionise cross-cultural education.

Keywords: AI-assisted teaching; international student education; Chinese culture; curriculum system; cross-cultural communication.

DOI: 10.1504/IJIPT.2026.152214

International Journal of Internet Protocol Technology, 2026 Vol.19 No.1, pp.44 - 52

Received: 24 Mar 2025
Accepted: 07 Jun 2025
Published online: 11 Mar 2026 *

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