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A Comparative Study on AI Education Models for Young People in Singapore and the Greater Bay Area - Based on Curriculum System and Teaching Methods

Author(s)

Chen Ziqian, Sun Meihuizi, Tong Jie, Liu Minlu, Li Hangyang

Affiliation(s)

Teesside University, Middlesbrough, Tees Valley TS1 3BX UK

Abstract

This study examines the similarities and differences in AI education models for young people in the Greater Bay Area and Singapore from both curriculum systems and teaching methods. The study finds that the Greater Bay Area adopts a 'state-led, tiered progression' curriculum framework, emphasizing the completeness of the knowledge system and value guidance, with a teacher-centered approach to teaching. In contrast, Singapore has developed an 'application-oriented, flexible autonomy' curriculum structure, focusing on practical skills development and implementing problem-based learning strategies. These differences stem from the deep-seated influences of educational traditions and social cultures: the Greater Bay Area emphasizes systematic inheritance and collectivism, while Singapore integrates multiculturalism and innovation. The study provides theoretical references for the localization of AI education practices and international learning.

Keywords

Artificial Intelligence Education; China-Singapore Comparison; Curriculum System; Teaching Method; Cultural Influence

References

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