基于WC-C-R学习资源推荐的研究

基于资源的学习已成为远程教育的一种重要的学习方式，网络课件和资源库是远程教育环境下两种重要的学习资源。为提高基于资源的学习效率，在“网络课件-概念图-学习资源库”三层模型研究的基础上，提出基于知识的资源推荐，并通过多Agent系统实现了在WC-C-R模型上进行资源推荐。实验证明，通过资源推荐，有助于提高学生的学习效率。     

基于Bayesian Network的学习资源库推荐系统构建与实现

针对学习资源使用者的特点和当前网络学习模型的不足,提出运用贝叶斯网络建立一种个性化学习者模型。基于用户决策方案指导资源库的建设,提出了一种新的学习资源推荐算法,使学习资源的呈现符合学习者认知发展水平和个性特征,改善资源库的组织结构,实现智能化、个性化的学习资源库推荐系统。实践证明,对于本系统所推荐的学习资源,学习者非常满意。     

基于WEB的数学素材库的模型设计

远程教育的当务之急是建立一个合理有效的资源库,使得广大教师可以共享制作网络课件所需的基本微小课件、以及媒体、案例、试题等素材资源,可以简单方便地制作出适合个人需要的网络课件。文章就如何构建一个教学素材库系统展开讨论,并提出一个有较强可行性的模型。     

基于XML的网络课件模型研究及实现

基于网络的计算机辅助教学朝着分布化、结构化、协同化方向发展,网络课件的合理建模和构造成为需要迫切解决的问题。该文提出了一个网络课件分层结构信息模型,把网络课件组织成具有课件目录层-课件页面层-媒体资源层三个层次的分层结构模型,定义了两套标记语言M M L和PM L,其中M M L用于描述课件目录层,PM L用于描述课件页面层和媒体资源层,从而实现了对网络多媒体课件的建模和构造,该模型能有效地解决课件网络化中出现的一些问题。     

基于本体的教学资源库及课件开发系统设计

我国目前的教育事业出现了这样一种现象,就是在教学中各种类的学习资源很多,但是却只有占整体很小一部分的网络课件教学资源.为了解决这样的一种局面,通过对教学资源的虚拟化整合,制造出了网络教学资源库这样的设计成果,也总结出了很多的基于本体的教学资源库,然后进行设计造出新的更好课件的办法.通过长时间的使用后发现,将教学资源虚拟化整合,更加丰富了网络教育的内容,通过基于本体的各种教学资源库的利用,可以很容易地就设计创新出新的教学课件,这对教育资源的共享的发展具有极大的帮助作用.     

基于语义Web的网络学习资源库本体实现

将语义Web技术引入网络学习系统，构造了一个基于语义Web架构的网络学习资源库本体，实现对网络学习系统中学习资源的管理。在分析本体建模方式以及网络学习资源库基本功能的基础上，定义了由学习资源本体和用户本体组成的学习资源库顶层本体，并给出系统类图，在Protégé3.1中实现了本体建模，给出了基于OWL的本体描述，对定义的本体进行了评估，并用基于本体的推理实例验证了本体的有效性。     

LMOD：一种基于本体描述的电子学习资源库模型*

随着电子学习系统应用的深入,资源库已经成为影响电子学习系统可用性的一个重要因素。针对现有资源库在资源检索查全率、查准率上存在的不足,将语义特征引入到电子学习资源库模型的构建之中,提出了一种基于本体描述的电子学习资源库模型LMOD。LMOD通过构建电子学习资源库本体并生成相应的语义元数据规范地描述资源,将资源以机器可以理解的方式组织起来;并利用语义学视图规范用户查询语句。在此基础上实现基于语义的资源查询,以有效地解决搜索中含糊解释与同义识别的问题。该模型能够有效克服现有资源库建设方案的缺点,提升资源库的使用效率与可用性。     

个人资源库的构建

基于网络的资源型学习,是指如何有效组织和利用因特网资源进行学习。基于资源的学习也称资源型学习,这是一种利用多种媒体资源来实现教学目标的学习活动。在这种学习模式中,构建个人资源库是积累个人资源的必要手段。该文介绍了面向公众的个人资源库及私有资源库的的类型、特点并对个人资源库的构建方法进行了有意义的探索。     

基于邮戳的网络教育资源安全机制

基于互联网的信息资源库是网络教育、电子政务、电子商务的基础设施。资源库中的不可信任资源将会给用户和系统带来不可估计的损失和危害。本文利用内容邮戳技术，以防止资源被非法篡改和病毒感染；通过定义访问控制域，对网络课件等可运行资源需要的系统资源的访问进行授权，这样可以有效地保证系统的安全。     

面向智慧校园的标准化学习资源管理体系研究

立足于高校数字校园网建设的现状,以网络学习资源为研究对象,探索我国网络教育资源建设存在的问题,并从元数据、学习对象数据、学习资源库和资源导航库四个方面标准化建设深入研究.给出分布式、统一网络学习资源库管理体系设计方案,以期为实现多方网络教育资源的整合提供借鉴与参考.     

学习资源库知识服务模型研究

学习资源库是基于Web学习环境中的重要组成部分,针对现有学习资源库服务的不足,文章提出了学习资源库知识服务模型,系统的论述了学习资源库知识服务的类型、服务提供方式、构成要素、工作机制以及服务过程等,提出了以Agent为主要实现技术的学习资源库知识服务系统框架,为验证此模型与框架的有效性与可行性,构建了实验系统。实验结果表明知识服务的提供能够有效的提高学习资源库的利用率、教与学效果以及学习资源管理效率。     

A nonlinear regulator design in the presence of systemuncertainties using multilayered neural network

The authors present a novel nonlinear regulator design method that integrates linear optimal control techniques and nonlinear neural network learning methods. Multilayered neural networks are used to add nonlinear effects to the linear optimal regulator (LOR). The regulator can compensate for nonlinear system uncertainties that are not considered in the LOR design and can tolerate a wider range of uncertainties than the LOR alone. The salient feature of the regulator is that the control performance is much improved by using a priori knowledge of the plant dynamics as the system equation and the corresponding LOR. Computer simulations are performed to show the applicability and the limitations of the regulator.     

Social models in open learning object repositories: A simulation approach for sustainable collections

Learning object repositories (LOR) are digital collections of educational resources and/or metadata aimed at facilitating reuse of materials worldwide. In open repositories, resources are made available at no cost, representing a case of information sharing with an implicit and diffuse social context. In such settings, quality control is in many cases based in some form of community filtering that provides a reliable basis for ranking resources when repositories reach a critical mass of users. However, there have been numerous repository initiatives and projects and many of them did not reached a significant degree of actual usage and growth that made them sustainable in the long term. In consequence, finding models for sustainable collections is a key issue in repository research, and the main problem behind that is understanding the evolution of successful repositories. This in turn requires analyzing experimental models of the behavior of their users that are coherent with the available evidence on their structure and growth patters. This paper provides a partial model for such behavior based on existing reported evidence and on the examination of patterns in a large and mature repository. Agent-based simulation was chosen to allow for contrasting configurations with different parameters. Simulations were devised with the RePast framework and the resulting model implementation constitutes an initial baseline for future studies aimed at contrasting empirical data on repository usage with their community setting. The model described accounts for known user contribution patterns and it is coherent with the implicit social network structure found in an existing large LOR.     

Repositories and communities at cross-purposes: issues in sharing and reuse of digital learning resources

Abstract   Globally, institutions are setting up digital repositories to support the sharing of resources for teaching and learning. The educational rationale is that a single set of resources can be restructured to support different pedagogical approaches and to achieve economies of scale. A key problem is that these learning object repositories (LORs), like many other learning technology innovations, are often designed to exploit the capabilities of technology rather than to meet learners' needs. The premise of this study is that the nature and organization of a community is likely to impact the way an LOR is used. Key dimensions of repositories and communities are discussed. Three repository systems are analysed to identify how communities use repositories. Guided by Activity Theory, the LORs and user communities are analysed as activity systems. These activity systems are compared and contradictions between them are identified. From the analysis, barriers and enablers for the use of LORs to support learning are discussed and a framework for addressing the key issues in the repository development stage is proposed.     

Ad hoc网络的局部最优路由选择策略

在Ad hoc网络中,由于节点的移动性及拓扑结构的易变性,路由成为最受关注的问题。提出了一种局部最优路由策略(LOR)。在该策略中,有两个节点需要通信时,根据节点存储的路由信息选择路径,如果有节点移动/删除,则就近选择合适的路径。仿真结果表明,LOR策略在工作过程中能使用较少的信息量和较小的时延来建立路径,明显提高了网络的性能。     

A personalized learning content adaptation mechanism to meet diverse user needs in mobile learning environments

With the heterogeneous proliferation of mobile devices, the delivery of learning materials on such devices becomes subject to more and more requirements. Personalized learning content adaptation, therefore, becomes increasingly important to meet the diverse needs imposed by devices, users, usage contexts, and infrastructure. Historical server logs offer a wealth of information on hardware capabilities, learners?? preferences, and network conditions, which can be utilized to respond to a new user request with the personalized learning content created from a previous similar request. In this paper, we propose a Personalized Learning Content Adaptation Mechanism (PLCAM), which applies data mining techniques, including clustering and decision tree approaches, to efficiently manage a large number of historical learners?? requests. The proposed method will intelligently and directly deliver proper personalized learning content with higher fidelity from the Sharable Content Object Reference Model (SCORM)-compliant Learning Object Repository (LOR) by means of the proposed adaptation decision and content synthesis processes. Furthermore, the experimental results indicate that it is efficient and is expected to prove beneficial to learners.     

Mobile Robot Learning by Self-Observation

The aim of the project described in this paper was to investigate robot learning at a most fundamental level. The project focused on the transition between organisms with innate behaviors and organisms that have the most rudimentary capability of learning through their personal interaction with their environment. It was assumed that the innate behaviors gave basic survival competence but no learning ability. By observing the interaction between their innate behaviors and the organism's environment it was reasoned that the organism should be able to learn how to modify its actions in a way that improves its performance. If a learning system is given more information than it requires then, when it is successful, it is difficult to say which pieces of information contribute to the success. For this reason the information available to the learning system was kept to an absolute minimum. In order to provide a practical test of the learning scheme developed in this project, the robot environment EDEN was constructed. Within EDEN a robot's actions influence its internal energy reserves. The environment incorporates sources of energy, and it also involves situations that use additional energy or reduce energy consumption. A successful learning scheme was developed purely based on the recorded history of the robot's interactions with its environment and the knowledge that the robot's innate behavior was reactive. This learning scheme allowed the robot to improve its energy management by exhibiting classical conditioning and a restricted form of operant conditioning.     

三维分子结构的制作、显示和格式转换

本文总结了各种三维分子结构在计算机和网络上显示与制作的方法,包括三维动画如3D Studio MAX、VRML、化学结构插件如MDL Chime Plugin、CS ChemOffice Plugin和HyperChem Plugin等、CML、Flash 3D动画、JAVA动画等,比较了他们制作和显示三维分子的优缺点,同时总结了各种三维分子结构格式的相互关系及转换方法,认为以通用的“mol”格式可以作中介可以较好地实现格式转换。     

Interoperability of Learning Objects Copyright in the LUISA Semantic Learning Management System

Abstract

Semantic Web technology is able to provide the required computational semantics for interoperability of learning resources across different Learning Management Systems (LMS) and Learning Object Repositories (LOR). The EU research project LUISA (Learning Content Management System Using Innovative Semantic Web Services Architecture) addresses the development of a reference semantic architecture for the major challenges in the search, interchange, and delivery of learning objects in a service-oriented context. One of the key issues, highlighted in this paper, is Digital Rights Management (DRM) interoperability. A Semantic Web approach to copyright management has been followed, which places a Copyright Ontology as the key component for interoperability among existing DRM systems and other licensing schemes like Creative Commons. Moreover, Semantic Web tools like reasoners, rule engines and semantic queries facilitate the implementation of an interoperable copyright management component in the LUISA architecture.