现代教育技术2026，Vol.36Issue(4)：5-14,10.DOI:10.3969/j.issn.1009-8097.2026.04.001
生成式人工智能之于教育的过量肯定风险及其规避
The Excessive Affirmation Risk of Generative Artificial Intelligence in Education and Its Avoidance
摘要
Abstract
The output logic of Generative artificial intelligence,which seems to be creative but actually predictive,often requires an excessive reliance on the contextual situation to produce results that satisfy users,thereby generating excessive affirmation.In education,such excessive affirmation is mainly manifested as excessive identification in the process of question-solving and answering,performance orientation in resource recommendation,and standard-centrism in performance evaluation.Improper use of generative artificial intelligence will further intensify the degree of excessive affirmation,thereby exposing students to risk of self-boundary crisis,individual self-exploitation,and performance subject burnout.By tracing the generation reasons of excessive affirmation,it can be found that the output of excessive affirmation stemmed from the purposeless,non-reflexive,and value-free algorithmic limitations of generative artificial intelligence.Negation was an instinct of human beings and a unique intelligence that distinguished humans from machines,which ought to be continuously advocated in the educational process.To reasonably and appropriately avoid the excessive affirmation risk of generative artificial intelligence in education,the value of negation should be acknowledged,the authentic self of students should be explored;the myth of performance growth should be dispelled,and the essence of human beings should be returned to;the reward crisis should be broken,and learning to observe should be emphasized.关键词
生成式人工智能/教育/过量肯定/优绩主义/奖赏危机Key words
generative artificial intelligence/education/excessive affirmation/meritcracy/reward crisis分类
社会科学引用本文复制引用
孙立会,许丰年..生成式人工智能之于教育的过量肯定风险及其规避[J].现代教育技术,2026,36(4):5-14,10.基金项目
本文为2025年教育部教育管理信息中心委托研究课题"高等教育中生成式人工智能伦理治理的国际比较研究及数据库建设"(项目编号:MOE-CIEM-2025026)、中央民族大学校级研究生自主科研项目"人工智能时代教育数字化转型的逻辑与机理研究"(项目编号:SZKY-Y2025199)的阶段性研究成果. （项目编号:MOE-CIEM-2025026）
