From policy to practice: a thematic analysis of generative AI technologies in China’s education sector
Muhammad Farrukh Shahzad, Shuo Xu, Xin An, Muhammad Asif, I. Javed
Abstract
This qualitative study explores the impact of generative AI (GenAI) technologies policy and practice to support learning performance in China's education sector, identifying key factors influencing successful adoption and implementation. Utilizing thematic analysis through NVivo 15, this study draws insights from interviews conducted with teachers and students in China. The analysis highlights the critical themes that shape the effectiveness of generative AI in enhancing educational outcomes. The study uncovers several key themes, including enhancing personalized learning experiences, increasing engagement and motivation, and developing cognitive skills. It also highlights the importance of teacher support, resource allocation, and technological infrastructure. The findings emphasize the need for readiness among both teachers and students, robust institutional policies, ethical considerations, and incorporation of GenAI into the curriculum to maximize its potential in the education sector. This research contributes novel insights into the application of GenAI in education, particularly within the Chinese context. It advances the understanding of how GenAI technologies can be utilized to enhance learning outcomes, offering practical endorsements for educators and policymakers seeking to navigate the complications of generative AI integration in education.