摘要
通过大数据分析、机器学习、自然语言处理等技术,人工智能能够高效处理大量教育数据,精准识别学生的学习模式和发展趋势,为学生提供个性化的学习建议。然而,人工智能赋能研究生增值评价在实际应用中也面临诸多挑战,如评价主体多元性缺失、数据质量不高、评价结果复杂等,制约了人工智能技术的应用效果,也对教育管理和政策制定提出了新的要求。旨在探讨人工智能赋能研究生增值评价的内在逻辑,分析其现实困境,并提出相应的实践路径。
Through technologies such as big data analysis,machine learning,and natural language processing,artificial intelligence can efficiently process large amounts of educational data,accurately identify students learning patterns and development trends,and provide personalized learning recommendations for students.However,the practical application of AI empowering the value-added evaluation of graduate students faces numerous challenges,such as the lack of diversity in evaluation subjects,low data quality,and complex evaluation results,which have restricted the application effect of AI technology and also put forward new requirements for educational management and policy formulation.This article aims to explore the inherent logic of artificial intelligence empowering the value-added evaluation of graduate students,analyze its practical challenges,and propose corresponding practical paths.
作者
池芳
CHI Fang(Development Planning and Evaluation Office,Wuyi University,Wuyishan 354300,China)
出处
《成都工业学院学报》
2025年第6期65-70,共6页
Journal of Chengdu Technological University
关键词
人工智能
研究生教育
增值评价
动态追踪
过程性评价
Artificial Intelligence
graduate education
value-added evaluation
dynamic tracking
Process Evaluation
