摘要
随着Internet在我国的逐步普及和终身学习的学习型社会的到来,网络教育蓬勃发展。目前,网络教育的重心从初始的教学资源提供转向教学活动组织。在组织教学活动时,大多数网校往往把注意力集中在知识内容组织、网络课程设计、学习资源提供等方面,而忽视了对注册学生的学习监控,这是造成目前网络学习质量不够高的一个重要原因。
本文首先对网络学习行为、网络学习行为监控两方面的国内外研究状况进行文献研究;接着系统阐述了网络学习行为的内涵和网络学习行为监控的意义,提出了网络学习行为监控框架、基于电大在线学习平台的数据采集方法等;之后本文研究了web数据挖掘技术,提出了应用Web日志挖掘技术进行学习行为智能反馈的方法。本文通过对系统关键技术的研究,提出了学习行为智能监控模型、数据库架构等,最后进行系统设计和应用效果分析。本文给出了若干解决网络学习行为监控问题的新思路和新方法,比如学习行为数据采集采用服务器日志结合电大在线学习平台后台数据库技术,避免了学习行为数据的不准确;提出了采用web数据挖掘技术进行学习行为反馈等等。
本文设计并实现了一个具有一定综合性、智能性的网络学习行为监控系统,该系统能对学生网络学习行为、电大教学平台运行情况进行监控和数据收集,并支持将数据进行挖掘得出相似群体、相关问题等实现智能反馈。本文的研究将有力促进网络教育的教学过程管理,并为网络教育的教学质量提供了重要的保证。
Along with popularization of Internet in China and the coming of a learning-oriented society, network education is flourishing. Now the focus of network education is transferring from providing teaching resources to organizing teaching activities. When organizing teaching activities, most of network schools always focus on the knowledge content organization, the designing of the network curriculum, the providing of the learning resources, but neglect the monitoring of the registered students, which is an important reason for low quality of network learning.
The paper first has a literature review of the features of E-learning behavior, learning monitoring, and the monitoring of E-learning behavior published at home and abroad; and then puts forward a framework of E-learning monitoring and data collection methods based on online learning platforms of Radio and TV Universities after systematically presenting the meaning of E-learning behavior and significance of the monitoring of E-learning behavior. At the end of this paper, with a study on webdata mining, the author, with web log mining technology, gets the intelligent feedback of learning behavior. After a study on the key technology of the system, the paper presents a system model and database schema of the monitoring system of learning behavior, and then analyzes system design and effects of application of this system. The paper proposes several new ways of solving the problems of monitoring E-learning behavior, such as combining server log with database technology of online learning platforms of TV and Radio Universities when data collection of learning behavior so as to avoid inaccurate data about learning behavior; and getting the intelligent feedback of learning behavior by means of webdata mining technology.
The paper designs and realizes a comprehensive and intelligent monitoring system of E-learning behavior, which can monitor learners' E-learning behavior and teaching platforms of TV and Radio Universities, can collect these data, and can get intelligent feedback from similar groups and related problems after mining these data.
引文
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