基于认知负荷及知识地图的适应性学习内容呈现机制研究
发布时间：2019-06-24 22:47
【摘要】： 通过因特网来学习成为近年来的热点，越来越多的课程通过网络来发布，网络成为支持远程教育、终生学习的重要手段。然而，有研究发现，学习者在超媒体信息空间学习的时候，存在信息超载的问题。网络可以提供大量的信息，然而对大量的信息进行处理时会加重学习者的认知负荷。同时，由于网络学习缺乏指导和监控，学习者往往不能找到适合自己学习程度的学习材料。这样，学习者在进行网络学习时会感到无所适从，或者事倍功半，甚至会影响学习者进行网络学习的信心。 目前网络化学习正在向着适应化方向发展，现有的网络学习系统或网络课程在给予学习者适当的引导方面还有很多值得改进的地方。近年来教育领域关于认知负荷的研究兴起，认知负荷的相关研究开始从基础研究走向应用研究。因此，本研究提出在超媒体学习系统内部建立一套“基于认知负荷和知识地图的适应性学习系统”，通过诊断性、过程性的评价策略，预测学习者对某个学习内容的学习能力，为学习者呈现适合他们知识水平的适应性学习内容，，以增强网络超媒体学习系统的适应性，更好的满足学习者的需要。 为了确定方法的可行性，该研究以java课程的第五章为例，设计了能够稳定实现所设计功能的原型系统——CKBALS：首先，通过认知负荷理论和知识地图的结构化知识表征，分解和建构了具有适应性的网络课程结构；其次，通过试题属性表的构建和概念累积计分算法，确定学生的概念掌握程度；然后，根据学习者的概念学习能力呈现适应性的学习材料，帮助学生更加高效地学习。 通过对研究问题的分析，实施双任务法测量认知负荷实验以及原型系统的设计和开发，我们得出本研究的主要结论：内在认知负荷随着任务难度的变化而发生有规律的变化，这种规律可以应用在适应性学习系统中，是系统适应行为的依据；根据领域模型及概念层级关系建构的学生模型能够有效描述个别学生的学习情况，是系统适应行为的基础；精心设计的单元测验能够确定学生当前的知识水平，预测学习者接下来的学习行为；根据学习者的概念学习能力向学习者呈现适应性的学习内容，帮助学生高效的完成学习，减少发生认知超载的可能性。
[Abstract]:Learning through the Internet has become a hot spot in recent years, more and more courses are released through the network, the network has become an important means to support distance education and lifelong learning. However, some studies have found that learners in hypermedia information space learning, there is a problem of information overload. The network can provide a large amount of information, however, the cognitive load of learners will be increased when a large amount of information is processed. At the same time, due to the lack of guidance and monitoring of online learning, learners are often unable to find learning materials suitable for their own learning level. In this way, learners will feel at a loss as to what to do, or get half the result with half the effort, and even affect the confidence of learners in online learning. At present, network learning is developing in the direction of adaptation. there are still many areas worthy of improvement in the existing online learning system or online courses in giving learners appropriate guidance. In recent years, the research on cognitive load has risen in the field of education, and the related research of cognitive load has begun to move from basic research to applied research. Therefore, this study proposes to establish an adaptive learning system based on cognitive load and knowledge map within the hypermedia learning system. Through diagnostic and process evaluation strategies, the learners' learning ability to a certain learning content can be predicted, and the adaptive learning content suitable for their knowledge level can be presented to the learners in order to enhance the adaptability of the online hypermedia learning system and better meet the needs of learners. In order to determine the feasibility of the method, taking the fifth chapter of java curriculum as an example, the prototype system CKBALS:, which can stably realize the designed function, is designed. Firstly, through the cognitive load theory and the structured knowledge representation of knowledge map, the adaptive network course structure is decomposed and constructed. Secondly, through the construction of test questions attribute table and the concept cumulative scoring method, the students' concept mastery degree is determined. Then, according to the learners' conceptual learning ability, adaptive learning materials are presented to help students learn more efficiently. Through the analysis of the research problems, the implementation of the cognitive load measurement experiment by the two-task method and the design and development of the prototype system, we draw the main conclusions of this study: the internal cognitive load changes regularly with the change of task difficulty, which can be applied to the adaptive learning system and is the basis of the adaptive behavior of the system; The student model constructed according to the domain model and conceptual hierarchical relationship can effectively describe the learning situation of individual students, which is the basis of systematic adaptive behavior, and the carefully designed unit test can determine the current knowledge level of students and predict the next learning behavior of learners. According to the learners' conceptual learning ability, they present adaptive learning content to the learners, help students to complete the learning efficiently, and reduce the possibility of cognitive overload.
【学位授予单位】：西南大学
【学位级别】：硕士
【学位授予年份】：2007
【分类号】：G434
本文编号：2505427
[Abstract]:Learning through the Internet has become a hot spot in recent years, more and more courses are released through the network, the network has become an important means to support distance education and lifelong learning. However, some studies have found that learners in hypermedia information space learning, there is a problem of information overload. The network can provide a large amount of information, however, the cognitive load of learners will be increased when a large amount of information is processed. At the same time, due to the lack of guidance and monitoring of online learning, learners are often unable to find learning materials suitable for their own learning level. In this way, learners will feel at a loss as to what to do, or get half the result with half the effort, and even affect the confidence of learners in online learning. At present, network learning is developing in the direction of adaptation. there are still many areas worthy of improvement in the existing online learning system or online courses in giving learners appropriate guidance. In recent years, the research on cognitive load has risen in the field of education, and the related research of cognitive load has begun to move from basic research to applied research. Therefore, this study proposes to establish an adaptive learning system based on cognitive load and knowledge map within the hypermedia learning system. Through diagnostic and process evaluation strategies, the learners' learning ability to a certain learning content can be predicted, and the adaptive learning content suitable for their knowledge level can be presented to the learners in order to enhance the adaptability of the online hypermedia learning system and better meet the needs of learners. In order to determine the feasibility of the method, taking the fifth chapter of java curriculum as an example, the prototype system CKBALS:, which can stably realize the designed function, is designed. Firstly, through the cognitive load theory and the structured knowledge representation of knowledge map, the adaptive network course structure is decomposed and constructed. Secondly, through the construction of test questions attribute table and the concept cumulative scoring method, the students' concept mastery degree is determined. Then, according to the learners' conceptual learning ability, adaptive learning materials are presented to help students learn more efficiently. Through the analysis of the research problems, the implementation of the cognitive load measurement experiment by the two-task method and the design and development of the prototype system, we draw the main conclusions of this study: the internal cognitive load changes regularly with the change of task difficulty, which can be applied to the adaptive learning system and is the basis of the adaptive behavior of the system; The student model constructed according to the domain model and conceptual hierarchical relationship can effectively describe the learning situation of individual students, which is the basis of systematic adaptive behavior, and the carefully designed unit test can determine the current knowledge level of students and predict the next learning behavior of learners. According to the learners' conceptual learning ability, they present adaptive learning content to the learners, help students to complete the learning efficiently, and reduce the possibility of cognitive overload.
【学位授予单位】：西南大学
【学位级别】：硕士
【学位授予年份】：2007
【分类号】：G434
【引证文献】
相关期刊论文 前3条
1 曹娟;潘来齐;;基于认知负荷理论的虚拟学习环境设计[J];电化教育研究;2010年04期
2 肖浩宇;;国内外“适合的教育”研究述评[J];基础教育研究;2012年20期
3 曹娟;;基于认知负荷理论的虚拟学习环境结构分析[J];软件导刊(教育技术);2012年02期
相关硕士学位论文 前3条
1 曹娟;基于认知负荷理论的虚拟学习环境设计[D];山东师范大学;2011年
2 季春兰;高中生认知负荷量表的编制及其相关研究[D];南京师范大学;2011年
3 周丽;基于图形化编程的高中算法教学研究[D];上海师范大学;2008年
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