本土化、多元化、均衡化:人工智能在国际中文教育中的应用探析

Localization, Diversification and Equalization: Explorations on Application of Artificial Intelligence in International Chinese Language Education

进入21世纪以来,国际中文教育在快速发展的同时,本土化、多元化、均衡化(“三化”)问题也日益凸显。研究基于SAMR模型对人工智能技术应用于国际中文教育进行理论分析,探讨应用人工智能化解“三化”难题的实施路径。本土化方面,利用人工智能技术推动教学模式变革、加强师资培训和提升教育体验,从而促进中文教学的本土融入、扩大本土师资力量、提升学习主动性;多元化方面,人工智能技术助推教育方式改革、拓宽学习方式、增强教育服务,从而支持多元化学习,满足多元人才培养需求;均衡化方面,应用人工智能技术构筑共享平台、开展双师教学和线上教育,化解教育资源不均衡问题、促进教育公平。研究还分析了人工智能应用于国际中文教育所面临的技术发展水平国别差异、参与者技术素养不足以及配套资源缺乏三个挑战并提出相应对策。

Since the beginning of 21 st century, with the rapid development of international Chinese language education, the issue of localization, diversification and equalization(“Sanhua”) have also become increasingly prominent. Based on SAMR model, this paper analyzes artificial intelligence technology in Chinese language education and discusses the implementation path of applying artificial intelligence to solve the issue of “Sanhua”. In terms of localization, the artificial intelligence technology is used to promote the reform of teaching model, strengthen the teacher training and improve the educational experience, so as to promote the local integration of Chinese language teaching, expand the local teachers and enhance the learning initiative;In terms of diversity, artificial intelligence technology can promote the reform of educational methods, expand learning methods and enhance educational services, so as to support diversified learning and meet the needs of diversified training for professionals;In terms of equalization, artificial intelligence technology can be applied to build a sharing platform, carry out dual-teacher teaching and online teaching, resolve the imbalance of educational resources and promote educational equity. This paper also analyzes the three challenges of the application of artificial intelligence in international Chinese language education, including the variations in the level of technological development across different countries, the stakeholders’ insufficient technical literacy and the insufficiency of supporting resources. Finally, corresponding countermeasures against the three challenges are proposed.