Generative AI and TCM Teaching Materials

Wang Yue; Sheiladevi Sukumaran

doi:10.33152/jmphss-9.3.2

Wang Yue Faculty of Education, Languages, Psychology and Music, SEGi University, Kuala Lumpur, Malaysia
Sheiladevi Sukumaran Faculty of Education, Languages, Psychology and Music, SEGi University, Kuala Lumpur, Malaysia

DOI: https://doi.org/10.33152/jmphss-9.3.2

Keywords: Generative Artificial Intelligence (GenAI), Traditional Chinese Medicine (TCM), Teaching material development, Higher education, Sustainable Development Goals (SDG), Educational technology, AI in education, TCM educators, Instructional content quality, China, Technology integration in pedagogy

Abstract

The growing role of Generative Artificial Intelligence (GenAI) in transforming education poses both opportunities and challenges for achieving Sustainable Development Goal 4 (Quality Education) through curriculum innovation, particularly in specialized fields like Traditional Chinese Medicine (TCM). This research examines the effect of GenAI utilization on teachers' assessments of teaching content quality among TCM educators in Shandong, China, with an investigation into its interactive role with teachers' perceptions. A total of 213 TCM educators from schools and academic institutions responded to a standardized survey, and data were analyzed through descriptive statistics, ANOVA, and Partial Least Squares Structural Equation Model (PLS-SEM). The findings indicate a statistically significant positive correlation existed between GenAI utilization efficacy and educators' assessments of material quality (β= 0.371, p < 0.001), with educators’ ratings improving significantly on such factors as material clarity, originality, as well as teaching order and organization. Mediation analysis also attested to teachers' perception playing an important mediation role in this correlation (β= 0.470, p < 0.001), citing that educators' confidence and positive perspectives on GenAI utilization enhance its pedagogical value. The model explained 22.1% of the variance in material quality ratings by educators, and utilization and perception were shown to be major predictors. The ANOVA findings also corroborated that GenAI utilization was significantly correlated with differences in different levels of rating material quality (F (1,211) = 7.017, p = 0.009). These findings reinforce how embracing GenAI tools and cultivating a positive teacher attitude is key to realizing its pedagogical value in its entirety. The research provides actionable insights for policymakers, curriculum developers, and school leaders in implementing AI in culturally established areas, noting that meaningful teacher engagement and support are crucial to leveraging technology for Sustainable Development Goal 4 (Quality Education).