网络学习者的学习软环境探析

今天计算机和网络在人们的学习交流中发挥着重要的作用,构建一个有效的学习软环境对学习者的学习非常重要,本文对学习软环境进行了分析,对其构建方法以及社会性软件的应用进行了相关探讨。     

泛在学习及其关键技术

泛在学习为教育改革提供了新的视角.依据对泛在学习主要特征的分析,提出了泛在学习环境模型,并讨论了支持泛在学习的关键技术.     

浅析泛在学习环境下的学习服务管理系统

本文从泛在学习出发,简单地介绍了泛在学习环境,提出泛在学习环境下的学习服务管理系统的概念,并对其主要功能模块和总体架构进行了阐述。     

新时代下的学习新模式——泛在学习

泛在学习作为一种新型的学习模式,它基于高速移动通信网路技术,通过无线便携设备获取教育信息,学习资源和教育服务。本文介绍了泛在学习的基本概念,讨论了其实现条件和方式以及优势和局限,在此基础上展望泛在学习的未来。     

RESTful风格的泛在学习平台的设计和实现

通过研究Rails框架实现RESTfulWebService的原理,本文从资源规划和URI设计,路由建立,控制器设计以及实现模板等方面综合阐述了泛在学习平台的设计思路,利用MVC架构和Ruby语言实现了具有良好交互性和可伸缩性的泛在学习平台,使用户可以轻松地使用平台进行学习和交流。     

智能适应服务导向的泛在学习模式在英语教学中的应用研究

本文分析了智能适应服务导向的泛在学习模式特性和英语教学模式,给出了传统的英语课程与泛在学习的英语课程的区别,提出了一种英语泛在学习平台体系结构,望对泛在学习理论在英语教学中的研究起一定的借鉴作用。     

自由版权——创意时代的知识规则

自由版权是以知识开放共享为核心激励创新过程的知识规则体系。 当前，随着创意经济的兴起、博客的发展，知识经济正在进入一个新的发展阶段。这一新阶段的特点是，知识经济正从物化的、大规模生产的传统方向，向创意的、个性化生产的方向转变。原有的知识产权体系，已不能充分满足Web2．0时代创新的要求。在软件源代码、左版和公共版权基础上，发展出完整的自由版权体系，是知识经济发展的内在要求。通过自由版权体系，平衡知识垄断体系之偏，成为全面建设创新型国家的当务之急。     

泛在学习在C语言教学改革实践中的探索

随着计算机技术、无线通信技术以及网络技术的飞速发展,一种新型的学习方式-泛在学习正逐渐成为可能.本文探讨如何将泛在学习应用于C语言教学,结合实际情况,研究探索出一个趋于泛在学习的C语言教学环境.     

基于Wi－Fi的高校泛在学习环境研究

从目前来看,Wi-Fi网络在无线局域网组网中扮演者重要角色,受到越来越多用户的亲睐,俨然已成为是无线局域网中的佼佼者。由此组建的高校校园Wi-Fi网络为泛在学习环境的发展带来了新的视角,为高校教育改革提供了新的思路。通过对Wi-Fi网络的分析,在讨论泛在学习环境的特点和构成的基础上,尝试性的提出基于Wi-Fi的高校泛在学习环境模型,并就高校如何构建此模型进行了剖析。     

Toward Third Generation Threaded Discussions for Mobile Learning: Opportunities and Challenges for Ubiquitous Collaborative Environments

The mobile communication revolution has led to pervasive connectedness—as evidenced by the explosive growth of instant messaging in the home, and more recently, the enterprise–and, together with the convergence of mobile computing, provides a basis for extending collaborative environments toward truly ubiquitous immersion. Leveraging the true anytime/anywhere access afforded by mobile computing, it becomes possible to develop applications that not only are capable of responding to users whenever/wherever, on demand, but that also may actively seek out and engage users when the need arises. Thus, immersive environments need no longer be thought of strictly in terms of physical immersion with clearly discernable enter and exit events, but rather they may be extended, through mobile-enabled computing, toward ubiquity in terms of both time and space. Based on Media Synchronicity Theory, potential benefits are envisioned, particularly in the case of collaborative learning environments, from shortened response cycles and increased real time interaction opportunities. At the same time, a number of challenging issues must be addressed in designing such an environment to ensure user acceptance and to maximize realization of the potential. Third Generation (3G) Threaded Discussion has been conceptualized as an environment, well suited to mobile learning (m-learning) that could leverage mobile-enabled ubiquity to achieve a degree of extended immersion and thereby accrue the associated collaboration benefits. Exploring this conceptualization serves to help surface both the opportunities and the challenges associated with such environments and to identify promising design approaches, such as the use of intelligent agents.This revised version was published online in March 2005 with corrections to the cover date     

构建数字化学习社区的一种新技术

通过课题研究,开展用Blog技术构建数字化学习社区的实践,文章对其可行性进行了分析,强调了构建的原则,阐明了构建的优势,并对系统的开发及试运行进行了说明。三年的实证研究认为Blog技术是建设数字化学习社区非常适用的一种新技术。     

构建数字化学习社区的一种新技术

通过课题研究，开展用Blog技术构建数字化学习社区的实践，文章对其可行性进行了分析，强调了构建的原则，阐明了构建的优势，并对系统的开发及试运行进行了说明。三年的实证研究认为Blog技术是建设数字化学习社区非常适用的一种新技术。     

基于泛在电力物联网的普适性智能电表状态实时评估方法

针对当前智能电表状态评估存在精确度低、泛化性差和实时困难等问题,本文采用泛在电力物联网构建状态实时评估方法解决该问题。首先,采用决策树算法实现智能电表的分类,整体增强方法的匹配度和适应性;随后针对不同类别的智能电表,采用Apriori算法对样本集数据的特征集进行识别和提取,从而降低特征维度并增强关联性;接着,基于决策引擎实现对智能电表状态实时评估,并以度量学习实现新增物联网采集数据的有效性评估,反馈优化传感设备部署,从而根据评估结果实现对新增部署传感器及其位置的调整,进而根据应用场景不断优化智能电表状态实时评估应用模式。实验结果表明,本方法可实现智能电表运行状况的实时、普适、精准运维评估,进一步解决泛在电力物联网设备现场部署经验不足、校验无目标等问题。     

一种新的神经网络学习算法

通过对人类学习机理和机制的研究,以及对现有ＢＰ神经网络学习算法及其改进的深入分析,本文提出了一种新的学习算法。该学习算法使神经网络学习由纯数学推导向智能化（启发式）学习发展,获取解决问题的最佳结构中神经元数及神经元间的联接数随问题的变化而动态变化,克服了目前神经网络学习算法普遍存在的学习时间长、局部极小小等问题。     

教育游戏:一种寓教于乐的新方式

教育游戏作为教育信息化的一个新元素,越来越受到人们的关注。该文对教育游戏产生的背景及教育游戏的基本概念(定义、特点、类型等)进行了阐述,还探讨了教育游戏的作用、定位及其应用方式。     

关联学习:关联关系挖掘新视角

关联关系挖掘与发现是大数据挖掘与分析的重要基础,现有的关联关系挖掘方法多是对数据进行统计分析,对未知数据缺少关联判别作用.尝试从学习的角度进行关联关系挖掘,给出了关联学习的形式化定义和相关概念,并根据关联学习定义构建学习数据集.具体地构建了2类关联图像数据集(two class associated image data sets, TAID),利用卷积神经网络提取关联特征,然后分别用softmax函数和K近邻算法判别关联关系,基于此提出3种关联关系判别器:关联图像卷积神经网络判别器(associated image convolutional neural network discriminator, AICNN)、关联图像LeNet判别器(associated image LeNet discriminator, AILeNet)和关联图像K近邻判别器(associated image K-nearest neighbor discriminator, AIKNN).3种关联判别器在TAID数据集上进行测试,AICNN在64×64像素90 000个训练样本上的判别精度达0.821 7,AILeNet在256×256像素22 500个训练样本上的判别精度达0.845 6,AIKNN在256×256像素22 500个训练样本上的判别精度达到0.866 4.这3种关联判别器有效地证明了学习角度挖掘关联关系的可行性.     

Performance,cognitive load,and behaviour of technology‐assisted English listening learning: From CALL to MALL

This study examines differences in English listening comprehension, cognitive load, and learning behaviour between outdoor ubiquitous learning and indoor computer‐assisted learning. An experimental design, employing a pretest‐posttest control group is employed. Randomly assigned foreign language university majors joined either the experimental group (outdoor ubiquitous learning), with 80 participants (26 males and 54 females), or a control group (indoor computer‐assisted learning), with 80 participants (27 males and 53 females). The experiment lasted 3 weeks. Both groups were administered a test of English listening proficiency before and after the experiment along with a questionnaire of cognitive load postexperiment. Prior English listening proficiency forms a covariate for the multivariate analysis of covariance. Results show (a) students in the experimental group exhibit significantly better English listening comprehension after the experiment compared to the control group; (b) students in the experimental group reported significantly lower cognitive load than the control group; (c) English listening comprehension and cognitive load exhibited a statistically significant negative relationship; and (d) outdoor ubiquitous learning enhanced self‐reported learning interests and interactions more than indoor computer‐assisted learning. Contributions and significances of this study are presented based on these results. Finally, implications for teaching practices are proposed.     

启发式知识获取方法研究

归纳学习是解决知识自动获取的有效方法，针对ID3算法、基于粗集的归纳学习以及其它一些归纳学习方法存在的问题，提出了一种新的归纳学习算法ITIL。此算法用信息增益为启发式，选择尽量少的重要属性或组合，以可分辨性为依据提取规则，许多实例表明，这些规则不仅简单，而且冗余小，作为知识获取模块的一部分，ITIL已被集成到一个“基于知识发现的医疗诊断辅助系统”动态知识库子系统中。     

A New Model of Computation for Learning Vision Modules from Examples

This paper addresses an important class of mimicry problems, where the goal is to construct a computer program which is functionally equivalent to an observed behaviour. Computer vision research can be considered such a challenge, where a researcher attempts to impart human visual abilities to a computer. Unfortunately this has proved a difficult task, not least because our vision processes occur mostly at a subconscious level. It is therefore useful to study the general mimicry problem in order to develop tools which may assist computer vision research.This paper formalises a mimicry problem as one in which a computer learning system (L) constructs a solution from a given program structure (i.e. template or outline) by posing questions to an Oracle. The latter is an entity which, when given an input value, produces the corresponding output of the function which is to be mimicked.In order to define a program's structure, particularly one which can be extracted from any computer program automatically, a new model of computation is developed. Based on this a fast algorithm which determines the best questions to pose to the Oracle is then described. Thus L relieves the human programmer of the difficulties faced in choosing the examples from which to learn. This is important because a human programmer might inadvertently choose biased, redundant or otherwise unhelpful examples. Results are shown which demonstrate the utility of a complete learning system (L) based on this work.This paper represents background theory and initial algorithms which further work will extend into powerful automatic learning systems, examples of which are found in [36] and [38].