中国正面临着严峻的来华留学生质量问题，核心在于：大幅增加的政府奖学金投入是否真的招到了高质量学生。本项目以“一带一路”国家为研究对象，首次引入人工智能机器学习方法，利用大数据训练机器模型，科学回答4方面问题：奖学金是如何促进华留学生规模增长的、奖学金导致来华留学生质量提高了还是下降了、奖学金是否是留学生来华求学的最根本原因、奖学金对申请人的投放是否科学精准。本项目人工智能机器学习研究方法的使用具有创新价值，首次在国际学界对政府奖学金与来华留学生规模、质量关系作出科学回答，首次对政府奖学金与学生留学行为选择做出因果推断，首次对政府奖学金投放与申请人质量之间的关系作出因果推断，将为来华留学生招生和奖学金政策调整提供关键支撑，所形成的来华留学生规模预测、质量预测机器模型经过反复调校将可直接用于来华留学生研究和实践工作。课题组前期研究成果、方法、数据资源、研究成员准备充分，将保障研究高质量推进。

China has encountered a serious problem that the qualification of international student coming to China is relatively limited. The key question is whether the dramatically increased input of governmental scholarship takes effect in enrolling high-qualification foreign student. Taking “the Belt and Road” countries as the research object, this project introduces the artificial intelligence machine learning method for the first time and uses big data to train the machine model to answer 4 questions scientifically: how the scholarships facilitate the growth of international student in China? Does scholarship improve or decline the quality of international students in China? Whether the scholarship is the fundamental reason for international student to study in China? And whether the scholarship is scientifically and accurately placed on the applicant? The application of the research method called artificial intelligence machine learning in this project is of innovative value. It is the first time to scientifically answer the relationship between governmental scholarship and the qualification of international students in China in the international academic community, the first time to make causal inference about the government scholarship and students’ behavior of studying abroad, and the first time to make causal inference about the relationship between the supply of government scholarship and the quality of applicants. This will provide fundamental support for the enrollment of international student coming to China and proper adjustment of the scholarship policies.