Concept mapping as a follow-up strategy to learning from texts: what characterizes good and poor mappers?

Concept maps consist of nodes that represent concepts and links that represent relationships between concepts. Various studies have shown that concept mapping fosters meaningful learning. However, little is known about the specific cognitive processes that are responsible for such mapping effects. In a thinking-aloud study, we analyzed the relations between cognitive processes during concept mapping as well as the characteristics of the concept maps that the learners produced and learning outcomes (38 university students). To test whether differences in learning outcome are due to differences in general abilities, verbal and spatial abilities were also assessed. In a cluster-analysis two types of ineffective learners were identified: ‘non-labeling mappers’ and ‘non-planning mappers’. Effective learners, in contrast, showed much effort in planning their mapping process and constructing a coherent concept map. These strategies were more evident in students with prior concept-mapping experience (‘advanced beginners’) than in those who had not used this learning strategy before (‘successful beginners’). Based on the present findings, suggestions for a direct training approach (i.e., strategy training with worked-out examples) and an indirect training approach (i.e., supporting the learners with strategy prompts) were developed.     

Towards mapping library and information science

In an earlier study by the authors, full-text analysis and traditional bibliometric methods were combined to map research papers published in the journal Scientometrics. The main objective was to develop appropriate techniques of full-text analysis and to improve the efficiency of the individual methods in the mapping of science. The number of papers was, however, rather limited. In the present study, we extend the quantitative linguistic part of the previous studies to a set of five journals representing the field of Library and Information Science (LIS). Almost 1000 articles and notes published in the period 2002–2004 have been selected for this exercise. The optimum solution for clustering LIS is found for six clusters. The combination of different mapping techniques, applied to the full text of scientific publications, results in a characteristic tripod pattern. Besides two clusters in bibliometrics, one cluster in information retrieval and one containing general issues, webometrics and patent studies are identified as small but emerging clusters within LIS. The study is concluded with the analysis of cluster representations by the selected journals.     

多异构数据库环境下的数据共享方案研究

XML是一种具有通用格式的文档结构，其自描述性的特点使得其非常适合于作为数据交换中传输的中间格式；Java对象（JO）具有更活的数据操纵能力。在其上进行数据操作具有简单、方便的优点。文章提出了一种基于数据库记录、Java对象、XML三者相互转换实现多并构数据库环境下数据共享问题的解决方案，该方案能在较大程度上减少代码的编写并提高数据共享的效率。     

我国教育技术学者合著网络知识图谱构建研究

知识图谱可以以可视化的形式展现学科的知识体系,借助教育技术期刊载文中的作者合著信息,可以构建出我国教育技术学者合著网络知识图谱;通过社会网络分析方法,可以对合著网络进行整体属性、社群结构、中心性、小团体、核心—边缘结构分析,从而得出合著网络的各项特征。结果显示,我国教育技术学者合著网络的密度较小,网络聚集度不大,虽具有小世界效应特征,但连通性较差,合著局限在小圈子内,同时具有核心—边缘结构。可划分为15个合著群体,有较多的高产合著组合和合著小团体,内部派系比较复杂,不过规模都较小,他们信息分享和科研合作机会的差别较大,黄荣怀、何克抗、李克东等学者是合著网络的核心学者。     

集值映射Henig有效解的最优性条件

在锥偏序Banach空间中利用集值映射的上图导数引进了Henig有效意义下的广义梯度,在一定条件下,利用凸集分离定理证明了该广义梯度的存在性。作为应用,给出了用广义梯度刻画集值优化问题Henig有效解的充分条件。     

DDC与《中图法》组合类目映射探讨

国内分类法映射研究多关注于间接映射方法的实现,对词表类目复杂语义关系研究较少。当前分类法采用大量的组合类目形式表达一些复杂的概念,由于不同类表之间组合类目的特点及作用不同,导致组合类目之间映射存在一定难度。针对DDC和《中图法》除生物科学以外的理学领域类目,分析了组合类目的分布特点,从语义层将组合类目划分为并列关系、属分关系、限制关系、交叉关系四种类型,总结组合类目的两种基本功能,从等同、包含和交叉三种关系类型研究组合类目直接映射的匹配规则,为进一步构建《中图法》和DDC的自动映射系统提供参考依据。表10。参考文献11。     

也谈机房的快速维护

本对机房快速有效的维护管理提出了新的思路并给出了具体实现方法，并在实际应用中取得了良好的效果。     

CMP JDO Hibernate的比较

文章是对java领域中影响较大的三种O/RMapping技术进行了比较,并通过实际的性能测试,通过直观,有说服力的数据来对三者进行比较。     

弹跳球运动的研究

建立了弹跳球运动的二维映射关系式，利用非线性动力学的原理和方法，在不同控制参数条件下，研究了系统二维映射式不动点的稳定性．     

从变量函数概念到RMI原则

代数函数概念经过几个世纪的演变过程，由函数概念向映射迈步是质的变化，是在原有概念基础的深化和推广，映射本质就是两个集合之间的元素对应，它与函数本质相同。函数的关系演变推导，可以用关系、映射、反演方法解决，这种方法就叫做“RMI”原则方法．