Exploring the Path to High-Quality Development of International Chinese Education Empowered by Artificial Intelligence
TL;DR
Five priorities are proposed: context-specific technical standards, sustained teacher development, localized and adaptive learning resources, data and algorithm governance, and staged evaluation before large-scale adoption before large-scale adoption.
Abstract
Artificial intelligence is entering international Chinese language education through conversational systems, automated feedback, learning analytics, and immersive environments. This article uses a SWOT framework to examine the educational value and implementation conditions of these applications. The analysis draws on research in artificial intelligence in education, technology-assisted language learning, intercultural education, and recent policy documents. AI can extend access to instruction, support differentiated practice, and reduce routine work in lesson preparation and assessment. Its educational value is constrained by weak pragmatic understanding, unreliable generated content, uneven digital infrastructure, privacy risks, and cultural bias. The central issue is therefore the quality of institutional use, not the mere availability of a model or platform. The article proposes five priorities: context-specific technical standards, sustained teacher development, localized and adaptive learning resources, data and algorithm governance, and staged evaluation before large-scale adoption. These priorities place teachers in control of instructional decisions while using AI for tasks in which rapid analysis, feedback, and resource generation can add demonstrable value.