GenAI技术在教育评价中的算法偏见:表现、成因与对策
The Algorithmic Bias of GenAI Technology in Educational Assessment:Manifestations,Causes,and Strategies
谢琦 1余日季 1蔡苏2
作者信息
- 1. 湖北大学 艺术与设计学院,湖北 武汉 430062
- 2. 北京师范大学 教育学部,北京 100875
- 折叠
摘要
在全球创新驱动发展战略不断深化的背景下,生成式人工智能(Generative AI,GenAI)技术正逐步成为推动教育评价体系转型升级的重要力量.然而,当前教育领域对智能技术的应用仍处于初级阶段,尤其在大语言模型的可解释性方面面临严峻挑战.数据偏差、算法设计缺陷和测试验证不足导致的"算法偏见"问题,已成为制约技术公平应用的关键难题.对此,文章结合GenAI技术在教育评价中的实际应用,首先系统梳理了算法偏见的具体表现,涵盖个体差异、地域差异、社会地位差异等维度;之后深入剖析了偏见产生的成因,主要从数据质量、模型设计、应用场景三个方面展开;最后提出完善算法设计、统筹治理主体、促进技术普惠等对策,以期为构建公正、透明、包容的教育评价体系提供参考.
Abstract
Under the context of deepening global innovation-driven development strategy,Generative Artificial Intelligence(GenAI)technology is increasingly becoming an important force to promote the transformation and upgrading of educational evaluation system.However,the application of intelligent technologies in the education field remains nascent,particularly facing significant challenges in the interpretability of large language model.The problem of"algorithmic bias"stemming from data bias,algorithm design defect,and inadequate testing verification has become a key problem restricting the fair application of technology.Therefore,combined with the practical application of GenAI technology in education evaluation,this paper first systematically combed the specific manifestations of algorithm bias,including individual differences,regional differences,social status differences,and other dimensions.After that,the root causes of bias were deeply analyzed from the perspectives of data quality,model design,and application scenarios.Finally,the strategies such as refining algorithm design,coordinating governance subject,and promoting technology inclusion to provide reference for the construction of a fair,transparent,and inclusive educational evaluation system.
关键词
GenAI技术/算法偏见/教育评价/数据伦理/人工智能Key words
GenAI technology/algorithmic bias/educational assessment/data ethics/artificial intelligence引用本文复制引用
出版年
2025
NETL
NSTL
万方数据