Advancing educational equity in rural China: the impact of AI devices on teaching quality and learning outcomes for sustainable development
Ronghui Chen, Yuanyuan Wu, Zhe Chen, Peng Zhou
Abstract
This study investigates the impact of AI-assisted teaching on teaching quality and learning outcomes in rural schools in China, aiming to promote educational equity and sustainable educational growth. Through questionnaire surveys of 268 teachers and controlled experiments in 12 schools (4 urban, 8 rural), we assess whether AI-integrated Mixed Reality (MR) devices can enhance educational experiences in resource-constrained environments, supporting sustainable development. The research integrates the Technology Readiness Index (TRI), Innovation Diffusion Theory (IDT), and Technology Acceptance Model (TAM) to propose a comprehensive framework for studying teachers' acceptance of these devices. Results indicate that AI-assisted teaching significantly improves teaching quality and learning outcomes, particularly in natural science courses, with rural schools showing greater gains (15.69% score improvement vs. 10.27% urban). Education investment in such technologies can reduce urban-rural disparities. Future research should explore subject-specific applications, strengthen teacher training, and enhance technical support to achieve educational equity and sustainable educational growth.