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作 者:李春霞 LI Chun-xia(School of Digital Media,Lanzhou University of Arts and Science,Lanzhou 730000,China)
机构地区:[1]兰州文理学院数字媒体学院,甘肃兰州730000
出 处:《兰州文理学院学报(自然科学版)》2024年第6期51-54,共4页Journal of Lanzhou University of Arts and Science(Natural Sciences)
摘 要:针对教育领域中学生能力评估的难题,即传统方法难以全面、客观地反映学生综合能力的现状,引入K-means算法作为核心方法,通过数据挖掘手段实现了对学生能力进行多维度、精细化的分类评估.首先,详细探讨了K-means算法在学生能力评估中的具体应用;然后,通过科学的数据处理流程,揭示了学生能力的内在结构和特点.本文方法不仅有助于识别学生的优势与短板,还为教育政策的制定及教学策略的调整提供了有力支持,促进了教育教学的个性化和精准化.In response to the difficulty of evaluating students’abilities in the field of education,that is,traditional methods are difficult to comprehensively and objectively reflect the current situation of students’comprehensive abilities,the K-means algorithm is introduced as the core method to achieve multi-dimensional and refined classification evaluation of students’abilities through data mining methods.This article explores in detail the specific application of K-means algorithm in student ability assessment.Through a scientific data processing process,it reveals the inherent structure and characteristics of students’abilities,which not only helps identify their strengths and weaknesses,but also provides strong support for the formulation of educational policies and the adjustment of teaching strategies,promoting the personalization and precision of education and teaching.
关 键 词:K-MEANS算法 学生能力评估 数据处理 精准评估
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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