个性化概念图在网络自主学习中的应用研究

发布时间：2018-05-30 16:37

本文选题：个性化学习 + 认知结构　；参考：《武汉大学》2010年博士论文

【摘要】：个性化学习是当代教育领域积极倡导的学习理念和模式,它强调以学习者为主体,针对学习者个性特点、知识经验和能力等具体学习情境而采用恰当的学习方法、学习内容和学习进度。在影响学习的诸多因素中,学习者的认知结构是其中最重要的。现有的网络教学系统很少考虑到不同学习者因认知结构的不同而引起的对课程材料的不同需求,更没有考虑到学习者的学习情况会随着学习者的学习进展而发生变化,一般是所有的学习者面对同一份静态的超媒体文档。如何形式化与量化表示学习者的认知结构,为网络自主学习者提供高质量的学习建议和指导,是网络学习系统的关键问题。本文在研究大量中外文献的基础上,针对当前网络学习系统存在的问题,在以下几个方面做了深入的研究： (1)学习者认知结构的形式化表示和量化。作为影响学习最重要的因素,学习者认知结构的形式化与量化是网络学习系统为学习者提出合理的学习建议和指导的基础。本文在定义学科知识点之间有序学习关系的基础上,提出个性化概念图的构建方法,以此表示学习者的认知结构。 (2)学习目标的预测分析。当完成某个阶段的学习,而进入下一阶段的学习时,网络自主学习者通常会面临多个学习目标的选择。本文结合个性化概念图的结构信息和语义信息,提出了计算知识点之间关联度的新方法,并在此基础上对新学习目标进行量化分析和计算,并将目标概念加以区分,帮助学习者选择最合适的下一步学习目标。 (3)学习资料的获取。以概念扩展的方式在Web或者网络学习系统内搜索学习资源,提出计算文本资源的难易度的方法,并根据学习者的认知水平和文本资源之间的适合程度进行排名,以便将最适合学习者当前认知水平的学习资源推荐给学习者。 (4)个性化概念图的可视化。研究概念图的自动布局方法,除了遵循传统的可视化美观准则,还特别强调节点之间内在的语义联系。对于具有复杂结构的个性化概念图,本文提出一种基于学习者兴趣的可视化简化方法,在某一时刻只呈现与学习者当前兴趣和关注点相关的概念,从而减轻学习者的认知负担,提高认知效率。在文章的最后介绍了个性化概念图原型系统,该系统可以进行概念图的编辑,自动布局,以及个性化概念图的构建、学习目标预测与概念划分、基于学习者兴趣的可视化。该系统为网络学习者提供了图形化的学习进程管理功能,智能化地指导和帮助学习者选择合适的学习目标,而且在面对复杂的概念图时,可以根据学习者当前的兴趣和关注点将其简化的表示出来。
[Abstract]:Individualized learning is an active learning concept and model advocated in the field of contemporary education. It emphasizes on taking learners as the main body and adopting appropriate learning methods according to specific learning situations such as individual characteristics, knowledge, experience and ability of learners. Learning content and progress. Among the many factors affecting learning, learners' cognitive structure is the most important. The existing web-based teaching system rarely takes into account the different needs of curriculum materials caused by different learners' cognitive structure, and does not take into account that learners' learning situation will change with the learners' learning progress. Generally all learners face the same static hypermedia document. How to formalize and quantify learners' cognitive structure and provide high quality learning advice and guidance for autonomous learners is a key issue in web-based learning systems. Based on the study of a large number of Chinese and foreign literature, this paper makes a deep study in the following aspects, aiming at the problems existing in the current network learning system: 1) formal representation and quantification of learners' cognitive structure. As the most important factor affecting learning, the formalization and quantification of learners' cognitive structure is the basis of the e-learning system to provide reasonable learning advice and guidance for learners. Based on the definition of the orderly learning relationship between the knowledge points of the subject, this paper proposes a method to construct the individualized concept map to represent the cognitive structure of the learners. 2) Prediction and analysis of learning objectives. When a certain stage of learning is completed and the next stage of learning is reached, the learner of network autonomy usually faces the choice of multiple learning goals. Based on the structural information and semantic information of the personalized concept map, a new method of calculating the correlation degree between knowledge points is proposed in this paper. On this basis, the quantitative analysis and calculation of the new learning object are carried out, and the concept of the goal is distinguished. Help learners to choose the most appropriate learning goals for the next step. 3) access to learning materials. Search for learning resources in Web or web-based learning system in the way of concept expansion, propose a method to calculate the difficulty of text resources, and rank them according to the learners' cognitive level and the suitability of text resources. In order to recommend the most suitable learning resources for the learners' current cognitive level. 4) Visualization of personalization concept map. In this paper, the automatic layout method of concept map is studied, which not only follows the traditional visual aesthetic criterion, but also emphasizes the intrinsic semantic relation between nodes. For the personalized concept map with complex structure, this paper proposes a visual simplification method based on learners' interest, which presents only the concepts related to the learners' current interests and concerns at any given time, thus reducing the cognitive burden of learners. Improve cognitive efficiency. At the end of the paper, the prototype system of individualized concept map is introduced. The system can edit the concept map, automate the layout, construct the personalized concept map, predict the learning goal and divide the concept, and visualize the concept based on the learner's interest. The system provides network learners with graphical learning process management functions, intelligently instructs and helps learners to choose appropriate learning goals, and in the face of complex concept diagrams, It can be simplified according to the learner's current interests and concerns.
【学位授予单位】：武汉大学
【学位级别】：博士
【学位授予年份】：2010
【分类号】：G434

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