【作者】 丁荣涛；

【导师】 赵燕伟；

【作者基本信息】 浙江工业大学 ， 计算机应用技术， 2008， 硕士

【摘要】 智能授导系统是借助人工智能的方法与技术,适应性地组织学习资源、实施教学策略、提供教学服务、进行教学评价的一种数字化学习支持系统。目前的智能授导系统中往往“智能化”体现不够,资源无法被有效利用,不能根据学习者个性提供相应的指导,实现个性化教学。我们希望开发一种智能的自适应授导系统,根据学习者的认知水平和学习行为,分配学习资源,制定个性化的学习路径,改变传统教育的“一视同仁”,实施个性化教育。本文的研究工作是一项计算机应用、人工智能、教育技术学多学科交叉的研究工作。本文在教育心理学、数据挖掘和本体等方面做了较深入的研究,开展了以下主要研究工作,并取得一定的研究成果。1、通过基于个性化教学原理的网络学习行为智能分析系统的构建和实施,积累和沉淀有分析价值的实验数据,掌握每个学习者的认知水平和学习风格等,选择ID3算法,并进行改进,分析学习者的学习者模型信息,形成学习者特征,建立个性化学习行为的决策树分类模型。2、引入领域本体,构建智能授导系统中的学习者和学习资源相关本体模型,同时对学习资源进行语义描述,建立学习资源分配知识库,根据学习者个体特征生成个性学习导航路径,支持个性化学习。3、实现了基于本体和数据挖掘技术的智能授导原型系统开发,包括学习行为分析及管理子系统、学习资源管理子系统、学习资源分配子系统等三个子系统。通过该系统,为每一个学习者提供了适应其需求特点的学习资源,使学习者的学习潜能在特定设计的环境下得到充分发挥。4、论文的最后总结了本文的研究工作,并讨论了一些未解决的问题以及进一步研究工作的前景。更多还原

【Abstract】 The Intelligent Tutoring System is a kind of digitized study support system in virtue of the artificial intelligence, it can compatibly organizes the teaching resources, implements teaching strategy, provides the teaching service, and carries on the teaching appraisal. The intellectualized degree of the present Intelligent Tutoring System is insufficient, the resources is unable to be used effectively, and it cannot provide the corresponding instruction according to the learners’ individuality to realize the individual teaching. We hoped developing an auto-adapted tutoring system to assign study resources, establish individual study path, and change the " impartial treatment " of traditional education according to the cognition level and the style of learners, and then implement the individual education.The research of this article is a crossed study of computer application, artificial intelligence, and educational technique. We have done more thorough research on the educational psychology, data mining and ontology. The main research work as follows, and obtains the certain research results.1. Because of the constructing and implementation of the network study behavior intelligence analysis system based on individual teaching principle, we have accumulated the empirical data that have analysis value, have grasped the cognition level and the study style of each learner. We choose the ID3 algorithm, and make the improvement, then analyze the study model information, form learner study characteristic, and establish the tree classification model of individual study behavior.2. We introduced domain ontology, and constructed the related ontology model of the learners and the study resources in the intelligent tutoring system, simultaneously carried on the semantic description to the study resources, established the study resource distribution library, and then produced individual study navigation way according to the learner’s individual characteristic to support the individual study.3. The prototype intelligent tutoring system based on the ontology and the data mining technology has been realized, including the study style analysis and management subsystem, teaching resource management subsystem, teaching resource distribution subsystem. This system provides study resources that adapted to the demands of each learner and enables the full display of study potential in the specific designed environment.The paper finally summarized the research work of this article, and discussed some solution of question as well as the further research work prospect.更多还原