摘要
全民学习和终身学习推动网络教育的迅猛发展,网络教学资源的合理建设和有效性研究已成为重要研究课题,本文基于远程教学理论和人工智能技术,在充分利用数据挖掘的基础上,分析、汇总、提炼了学生网络自主学习的资源行为数据,采用基于决策树的C4.5算法进行科学分类,形成资源类型应用决策树,获取网络资源利用规律,以预测和指导远程教学资源的科学建设和高效使用,对构建远程网络教学模式,提高教育机构、教师、学生网络教育实施和研究能力,进而提升教学质量给予理论导向和探索前景。
Universal and lifelong learning promote the rapid development of online education,the reasonable construction and effectiveness research of network teaching resources has become an important research subject. This paper on the basis of remote teaching theory and artificial intelligence,making full use of data mining,analysis、summary、refine the resource behavior data of students' autonomous learning. This paper make the scientific classification Using C4. 5 algorithm based on decision tree,form the decision tree about resource type of using,obtain use rules about network resources,in order to predict and guide the scientific construction and efficient using about distance teaching resources. The paper give the theoretical guide and exploration prospect about the construction of the remote network teaching mode,and improving the ability of online education implementation and research about the? educational institutions、teachers and students,and thus enhancing the quality of teaching.
出处
《内蒙古农业大学学报（自然科学版）》
CAS
2015年第2期172-176,共5页
Journal of Inner Mongolia Agricultural University(Natural Science Edition)
关键词
网络教学
C4.5算法
资源建设
Network teaching
C4.5 algorithm
resources construction
