Research on cross-regional adaptation strategies for AI-enabled teaching devices from an educational equity perspective - Jianjun Chen; Yaoyao Ding; Hanjun Zhang; Xiao Dong; Peng Zhou (PLoS ONE, 2026)
This study investigates the impact of AI-enabled teaching devices on educational equity, focusing on the differences in their effectiveness between economically developed and underdeveloped regions in China, particularly along the Hu Huanyong Line. The research aims to assess whether AI devices can enhance educational outcomes and promote equity in regions with limited resources. Using a mixed-methods approach, the study involved a comparative analysis of eight schools across four cities on both sides of the Hu Huanyong Line. Data were collected through an online questionnaire survey of 247 teachers and an analysis of 620 student exam scores. The findings indicate that AI devices significantly improved teaching effectiveness in economically underdeveloped regions, with an average improvement of 7% to 20% in student performance. The study also revealed that while teachers in underdeveloped regions were generally positive about AI devices, they faced challenges in integrating the technology into their teaching practices due to insufficient familiarity and lack of support mechanisms. The results highlight the potential of AI technology to bridge educational gaps and promote equity by providing high-quality educational resources to under-resourced areas. However, the study emphasizes the need for comprehensive support measures, including teacher training and improved infrastructure, to ensure sustainable educational development. Future research should focus on long-term trends in educational resource investment and the development of culturally appropriate AI devices to further enhance educational equity and sustainable development.