Gender Disparities in Artificial Intelligence Acceptance in Sabah

Abstract

The education landscape in Malaysia has undergone a comprehensive transformation with Industrial Revolution 4.0 technologies such as artificial intelligence (AI). However, unequal AI acceptance based on gender reduces diversity in classroom AI practices and limits the positive impact of AI use among teachers. Therefore, the purpose of this study is to investigate the moderating effects of gender on AI acceptance among secondary school science teachers in Sabah based on the Unified Theory of Acceptance and Use of Technology (UTAUT). A quantitative study of 345 science teachers from secondary schools selected through a simple random sampling technique. Data were collected using a questionnaire of 48 items. Subsequently, pls structural equation modeling (PLS SEM) which involve Multi-Group Analysis (MGA) and slope analysis were used to evaluate the theoretical model. The findings confirmed that gender moderates the relationship between social influences and facilitating condition with behavioral intention. These findings provided helpful information for stakeholders and educational institutions to design specific program in order to reduce the gender gap in AI acceptance in science teaching.