基于Web的适应性学习支持系统研究
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摘要
目前的网络教学系统大多通过网页发布和一些交流工具来开展教学活动，基本上是Internet技术在教学上的一些简单应用。它们主要提供一些学习资源，学习的动态过程无从体现，没有发挥教师的即时指导、监控、调节等作用，缺乏对适应学生特征的个性化学习支持手段。
适应个体特征的学习支持环境是网络教学中的一个重要研究课题，九十年代中期以来，关于该领域的研究论文与报告日趋增多，其中尤其以适应性超媒体(AH，Adaptive Hypermedia)的研究最为活跃。适应性学习支持系统是适应性超媒体在教学领域中的应用，它是智能教学系统与超媒体系统的交叉、集成与融合，既能体现出用户在学习过程中，具有高度的自主性，能够自由选择学习路径和自定学习步调；又能根据用户的特点对学习内容和学习方向提供合适的指导和帮助。
本文的研究立足于开展网络教学的实际需要，通过借鉴国内外关于适应性超媒体、智能教学系统和网络教学系统的研究成果，提出了一套教学领域知识的组织和表示方案，用户建模方法和体现智能适应性特征的学习支持系统结构模型，并基于这些研究成果开发了适应性远程学习支持系统--A-Tutor(Adaptive Tutor)。
本文的内容组织如下：
第一章介绍课题的来源，界定了本文的研究范围。
第二章阐述课题研究的理论基础，通过对学习理论、教学理论的研究，将学习系统的支持因素进行了提炼和抽象，并对其在不同教学系统中的表现形式进行比较。
第三章对学习系统的形式化建模进行了分析与研究。
第四章对教学软件的几种主要形式进行评述，重点分析适应性教育超媒体系统和教学支撑平台的研究进展情况，并对A-Tutor系统与目前的适应性学习支持系统进行了分析和比较。
第五章阐述了适应性学习支持系统A-Tutor的总体结构模型。
第六章研究领域建模的思想与方法，重点论述A-Tutor系统中领域知识组织的层次模型和信息模型。
第七章对用户模型与用户建模的基本思想和方法进行了分析，重点论述A-Tutor系统中的用户模型和建模方法。
第八章对A-Tutor系统中适应性发布引擎的实现技术和关键算法进行了研究。
第九章介绍A-Tutor系统的开发技术，同时还介绍了利用A-Tutor系统进行网络课程创作和学习的过程。
第十章对本文的研究进行了总结，并指出了本文研究的不足和今后的研究方向。
本文的贡献和创新在于：
(1)较全面地总结了适应性超媒体系统／适应性学习支持系统的研究成果，并提出了适应性学习支持系统的系统模型与结构。
(2)提出了网络教学中的领域知识层次模型和以学习单元为核心的领域知识信息模型。并采用确定性因子和模糊技术表示不确定性的领域知识。
(3)提出了多层次的用户模型结构和用户建模的方法，采用了基于教学策略的动态练习创作和发布方法。
(4)在适应性学习系统所营造的学习环境方面，采取以学习单元为核心，局部学习环境满足梅瑞尔提出的教学设计基本原则(以问题为中心，激发、演示、应用、集成)，在全局上，根据用户的知识掌握程度，采用链标记、直接导航和动态学习区实现智能导航。
华南师范大学博士学位论文:基于Web的适应性学习支持系统研究
(5)基于上述的理念和设计，开发了适应性网络课程发布系统原型，并提出了适应性
网络课程创作的过程和方法，为今后进一步的实验研究奠定了基础。
Most of the current distance learning systems, which are implemented by combining web-based learning material and some corresponding tools, are simple applications of Internet technology in distance education. These systems, which are short of individual learning support to the student, are hard to offer such functions as real time guidance, monitoring, adjusting, etc.
Adaptive learning environment is an important subject in distance education. Since 1996, research papers in this area, especially on adaptive hypermedia (AH), have increased fastly. Adaptive learning system is application of adaptive hypermedia in education, which is the cross of intelligent tutoring system (ITS) and hypermedia. Not only they ensure the freedom to the user in his learning procedure, but also provide guidance and help which are adaptive to user's traits.
Rooted in the need of distance instruction and by referencing fruits of adaptive hypermedia, ITS, and network instruction system, the author presented an instruction domain model, user model and modeling method, system structure of adaptive learning system in the thesis. In addition, some algorithms on curial components are discussed and a prototype named A-Tutor (Adaptive Tutor) has been developed.
The content in the thesis is as following:
In Chapter 1, the origin of problem in the paper was introduced and the research framework was defined.
In Chapter 2, the instruction theory was surveyed. Supporting factors in learning process were put forward, and their traits were compared in different instruction systems.
In Chapter 3, the formal modeling of learning system was investigated.
In Chapter 4, a few types of instruction software were reviewed. Especially, the author focused on state of art of adaptive education hypermedia and instruction supporting platform, and then compared the current adaptive learning system with A-Tutor system.
In Chapter 5, overall structure model of A-Tutor was analyzed.
In Chapter 6, ideas and methods of domain model were introduced firstly, and then layered model and information model in A-Tutor were presented in detail.
In Chapter 7, user model and modeling method were introduced firstly, and then user mode! in A-Tutor was focused on.
In Chapter 8, crucial algorisms of adaptive engine in A-Tutor were investigated.
In Chapter 9, development technology was introduced firstly, and then the procedure of authoring and learning with A-Tutor were presented.
In Chapter 10, the author made a conclusion on this thesis and then indicated some: shortcomings and the next research goal.
The creative and contributions in this thesis can be summed up as following:
(1) make an overall review on fruits of adaptive hypermedia and adaptive learning system., and put forward a new system model of adaptive learning system.
(2) design an instruction knowledge layered model and information model, and use certainty factor and fuzzy technology to represent uncertain knowledge.
(3 ) bring forward a multi-tier user model and methods of user modeling.
(4) use learning unit as core, offering tree-like directory navigation and task-based learning
style. In local appearance, the system satisfied what Merrill said basic infraction principles , which combining problem, activation, demonstration, application and integration. And in global appearance, the system use link annotation as guidance. Besides, dynamic learning area was used as navigation in task-based learning style.
(5) based on the above technology, the author have developed an adaptive learning prototype system, and put forward a process and method on how to produce an adaptive on-line course, which is the base of the experiment research.
适应个体特征的学习支持环境是网络教学中的一个重要研究课题，九十年代中期以来，关于该领域的研究论文与报告日趋增多，其中尤其以适应性超媒体(AH，Adaptive Hypermedia)的研究最为活跃。适应性学习支持系统是适应性超媒体在教学领域中的应用，它是智能教学系统与超媒体系统的交叉、集成与融合，既能体现出用户在学习过程中，具有高度的自主性，能够自由选择学习路径和自定学习步调；又能根据用户的特点对学习内容和学习方向提供合适的指导和帮助。
本文的研究立足于开展网络教学的实际需要，通过借鉴国内外关于适应性超媒体、智能教学系统和网络教学系统的研究成果，提出了一套教学领域知识的组织和表示方案，用户建模方法和体现智能适应性特征的学习支持系统结构模型，并基于这些研究成果开发了适应性远程学习支持系统--A-Tutor(Adaptive Tutor)。
本文的内容组织如下：
第一章介绍课题的来源，界定了本文的研究范围。
第二章阐述课题研究的理论基础，通过对学习理论、教学理论的研究，将学习系统的支持因素进行了提炼和抽象，并对其在不同教学系统中的表现形式进行比较。
第三章对学习系统的形式化建模进行了分析与研究。
第四章对教学软件的几种主要形式进行评述，重点分析适应性教育超媒体系统和教学支撑平台的研究进展情况，并对A-Tutor系统与目前的适应性学习支持系统进行了分析和比较。
第五章阐述了适应性学习支持系统A-Tutor的总体结构模型。
第六章研究领域建模的思想与方法，重点论述A-Tutor系统中领域知识组织的层次模型和信息模型。
第七章对用户模型与用户建模的基本思想和方法进行了分析，重点论述A-Tutor系统中的用户模型和建模方法。
第八章对A-Tutor系统中适应性发布引擎的实现技术和关键算法进行了研究。
第九章介绍A-Tutor系统的开发技术，同时还介绍了利用A-Tutor系统进行网络课程创作和学习的过程。
第十章对本文的研究进行了总结，并指出了本文研究的不足和今后的研究方向。
本文的贡献和创新在于：
(1)较全面地总结了适应性超媒体系统／适应性学习支持系统的研究成果，并提出了适应性学习支持系统的系统模型与结构。
(2)提出了网络教学中的领域知识层次模型和以学习单元为核心的领域知识信息模型。并采用确定性因子和模糊技术表示不确定性的领域知识。
(3)提出了多层次的用户模型结构和用户建模的方法，采用了基于教学策略的动态练习创作和发布方法。
(4)在适应性学习系统所营造的学习环境方面，采取以学习单元为核心，局部学习环境满足梅瑞尔提出的教学设计基本原则(以问题为中心，激发、演示、应用、集成)，在全局上，根据用户的知识掌握程度，采用链标记、直接导航和动态学习区实现智能导航。
华南师范大学博士学位论文:基于Web的适应性学习支持系统研究
(5)基于上述的理念和设计，开发了适应性网络课程发布系统原型，并提出了适应性
网络课程创作的过程和方法，为今后进一步的实验研究奠定了基础。
Most of the current distance learning systems, which are implemented by combining web-based learning material and some corresponding tools, are simple applications of Internet technology in distance education. These systems, which are short of individual learning support to the student, are hard to offer such functions as real time guidance, monitoring, adjusting, etc.
Adaptive learning environment is an important subject in distance education. Since 1996, research papers in this area, especially on adaptive hypermedia (AH), have increased fastly. Adaptive learning system is application of adaptive hypermedia in education, which is the cross of intelligent tutoring system (ITS) and hypermedia. Not only they ensure the freedom to the user in his learning procedure, but also provide guidance and help which are adaptive to user's traits.
Rooted in the need of distance instruction and by referencing fruits of adaptive hypermedia, ITS, and network instruction system, the author presented an instruction domain model, user model and modeling method, system structure of adaptive learning system in the thesis. In addition, some algorithms on curial components are discussed and a prototype named A-Tutor (Adaptive Tutor) has been developed.
The content in the thesis is as following:
In Chapter 1, the origin of problem in the paper was introduced and the research framework was defined.
In Chapter 2, the instruction theory was surveyed. Supporting factors in learning process were put forward, and their traits were compared in different instruction systems.
In Chapter 3, the formal modeling of learning system was investigated.
In Chapter 4, a few types of instruction software were reviewed. Especially, the author focused on state of art of adaptive education hypermedia and instruction supporting platform, and then compared the current adaptive learning system with A-Tutor system.
In Chapter 5, overall structure model of A-Tutor was analyzed.
In Chapter 6, ideas and methods of domain model were introduced firstly, and then layered model and information model in A-Tutor were presented in detail.
In Chapter 7, user model and modeling method were introduced firstly, and then user mode! in A-Tutor was focused on.
In Chapter 8, crucial algorisms of adaptive engine in A-Tutor were investigated.
In Chapter 9, development technology was introduced firstly, and then the procedure of authoring and learning with A-Tutor were presented.
In Chapter 10, the author made a conclusion on this thesis and then indicated some: shortcomings and the next research goal.
The creative and contributions in this thesis can be summed up as following:
(1) make an overall review on fruits of adaptive hypermedia and adaptive learning system., and put forward a new system model of adaptive learning system.
(2) design an instruction knowledge layered model and information model, and use certainty factor and fuzzy technology to represent uncertain knowledge.
(3 ) bring forward a multi-tier user model and methods of user modeling.
(4) use learning unit as core, offering tree-like directory navigation and task-based learning
style. In local appearance, the system satisfied what Merrill said basic infraction principles , which combining problem, activation, demonstration, application and integration. And in global appearance, the system use link annotation as guidance. Besides, dynamic learning area was used as navigation in task-based learning style.
(5) based on the above technology, the author have developed an adaptive learning prototype system, and put forward a process and method on how to produce an adaptive on-line course, which is the base of the experiment research.
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