基于k -均值算法的在线课程学习者智能分层模型研究

Ying Zhu, Xiaonuan Wang
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引用次数: 0

摘要

由于学习者群体的个性缺陷,一般的教学方法已经不能满足学习者整体素质的需要。分级课程关注的是中小学生不同的人性化和学业需求,需要可行的方案和总体目标,以提高学校的整体效果。针对教育中的分层模型,基于计算机技术和网络课程教学中的K-means算法设计了分层模型,对学习者的学业状况进行划分。仿真实验表明,该分层模型比基于专业排名和学习者总分排名的分层模型更加科学合理。研究结果可为其他学科提供参考。
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Research on Intelligent Hierarchical Model of Online Course Learners Based on K-Means Algorithm
Due to personal defects in the learner population, the general teaching method can no longer meet the needs of learners' overall talent. The graded curriculum focuses on the different humanization and academic needs of primary and secondary school students, which requires feasible plans and overall objectives for the improvement of the overall effect of the school. Focusing on the hierarchical model in education, a hierarchical model is designed based on the K-means algorithm in teaching computer technology and network courses to divide learners' academic situations. The simulation test shows that the hierarchical model is more scientific and reasonable than the hierarchical model based on professional ranking and learners' total score ranking. The study result provides a reference for other disciplines.
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