摘要
当前我国的职业教育正面临大改革,国家把职业教育提升到与本科同等重要的地位,同时职业教育也将进行大幅度的扩招,不仅面向中职、高中生,还面向各类社会人员,在师资力量有限、知识技能更新迅速的职业教育现状下,要实现高质量的人才培养,需要借助机器学习算法来辅助教师开展教学,通过设计符合机器学习算法的题目,可以有效的减少教师出题的负担,实现分层的个性化教学效果。本文研究层次聚类算法在学生动态分组及推荐中的应用,以辅助教师实施补救性教学,并有效缓解学生学习需要及教师精力有限的矛盾。
At present,China’s vocational education is facing major reforms.The country has promoted vocational education to the same important status as undergraduates.At the same time,vocational education will also undergo a substantial expansion,not only for secondary vocational and high school students,but also for all kinds of social person.Under the current situation of vocational education with limited teachers and rapid updating of knowledge and skills,to achieve high-quality talent training,machine-learning algorithms need to be used to assist teachers in teaching.By designing topics that conform to machine learning algorithms,teachers can effectively reduce the number of questions and achieve hierarchical personalized teaching effects.This paper studies the application of hierarchical clustering algorithm in students’ dynamic grouping and recommendation to assist teachers in implementing remedial teaching,and effectively alleviate the contradiction between students’ needs and teachers’ limited energy.
作者
蒋海锋
JIANG Haifeng(Guangdong Polytechnic of Science and Technology,Zhuhai,Guangdong,519090)
出处
《科教导刊》
2021年第29期36-38,共3页
The Guide Of Science & Education
基金
广东科学技术职业学院校级科研项目“SOM聚类算法在智能教学系统中的研究与应用实施”(项目编号:XJJS202106)
广东科学技术职业学院校级教改项目“媒体融合视域下高职网络新闻与传播专业人才培养模式的研究与实践”(项目编号:JG202102)。
关键词
层次聚类算法
推荐系统
辅助教学
hierarchical clustering algorithm
recommended system
assisted teaching
