I Putu Ade Andre Payadnya, Gusti Ayu Made Arna Putri, I Ketut Suwija, Sompob Saelee and I Gusti Agung Ngurah Trisna Jayantika
Artificial intelligence (AI) is increasingly used in education, yet its cultural impact, especially in Southeast Asian mathematics education, remains underexplored. This gap is…
Abstract
Purpose
Artificial intelligence (AI) is increasingly used in education, yet its cultural impact, especially in Southeast Asian mathematics education, remains underexplored. This gap is significant because understanding cultural adaptation is essential for AI tools to effectively enhance learning in diverse classrooms. This study examines how AI can be integrated into mathematics education across Southeast Asia, focusing on specific cultural practices such as communal learning styles, respect for hierarchical structures and the role of local languages, as well as educators’ perspectives.
Design/methodology/approach
A mixed-methods approach was used, combining quantitative data from questionnaires with qualitative insights from interviews with educators across ten Southeast Asian countries. The study included 543 respondents in total with the numbers is varying in each country, targeting high school teachers experienced in using AI in teaching.
Findings
The findings revealed that educators in Singapore are most confident in AI’s adaptability to cultural contexts, whereas those in Myanmar and Laos face challenges due to infrastructure limitations. Interviews highlighted the need to customize AI tools to align with students’ cultural backgrounds, including language preferences and traditional learning practices, for effective implementation. Teacher training and access to technology, especially in rural areas, were also identified as critical factors.
Originality/value
This study addresses a critical gap in understanding AI’s cultural implications in Southeast Asia, providing insights into how cultural values, language and educational practices influence the integration of AI in mathematics education. The findings highlight the need for culturally responsive AI tools and targeted improvements in infrastructure and teacher training for successful implementation.