Identification of the design variables of eLearning tools

The widespread availability of digital learning resources in a variety of media formats has promoted the proliferation of eLearning systems as an integral part of teaching across all sectors of education. However, these systems are rarely planned in advance taking into account its final usefulness. At most, they are validated through learner experience using the final implemented system. In this paper, a scientific technique called concept mapping is proposed to identify the external variables that should be kept in mind while designing an eLearning tool. As a result, improvements can be programmed to increase its utility in the teaching activities prior to its use. The method has been tested in the development of a eLearning system used for advanced microprocessor teaching. Results are shown through two-dimensional maps, in which variables can be seen as clusters or groups of ideas. These variables can be used as a guide for developing an eLearning tool. The reliability of the results is also analyzed to check the correct application of the proposed technique.     

Identifying multiple roles of ICT coordinators

This study reports on the development and validation of measurement scales to study the different roles fulfilled by ICT coordinators. Based on a review of the literature, a 24 item questionnaire was constructed and administered to a sample of 177 Flemish ICT coordinators working in primary education. Exploratory factor analysis revealed a four-factor solution: the ICT coordinator as a planner, a budgeter, a technician, and an educationalist. Qualitative data corroborated these roles. This study provides a quantitative measure of the different roles assumed by ICT coordinators in practice. The implications of our findings for schools, researchers and policy makers are discussed.     

A visualization model based on adjacency data

In this paper, we describe a model whose focus is on data visualization. We assume the data are provided in adjacency format, as is frequently the case in practice. As an example, individuals who buy item a are likely to buy or consider buying items b, c, and d, also. We present a simple technique for obtaining distance measures between data points. Armed with the resulting distance matrix, we show how Sammon maps can be used to visualize the data points. An application to the college selection process is discussed in detail.     

Accuracy and bias of ICT self-efficacy: An empirical study into students’ over- and underestimation of their ICT competences

Most studies on the assessment of ICT competences use measures of ICT self-efficacy. These studies are often accused that they suffer from self-reported bias, i.e. students can over- and/or underestimate their ICT competences. As such, taking bias and accuracy of ICT self-efficacy into account, would improve the validity of these studies and the predictive power of the ICT self-efficacy measures used. Consequently, the general aim of this study is twofold. First, to explore the degree to which primary school students are under- and/or overestimating their ability in digital information processing and communication. Second, to identify student characteristics that are possibly related to the accuracy of ICT self-efficacy. Information on accuracy and bias of ICT self-efficacy was gathered by comparing students’ results on an ICT self-efficacy scale and a performance based ICT competence test. Both instruments were administered to 378 sixth grade students from 58 primary schools in Flanders (the Dutch speaking part of Belgium). Information on the explanatory student characteristics was gathered through a questionnaire that was administered to the same students. The results indicate that primary school students make relatively accurate and positively biased judgments about their ability in digital information processing and communication. Further, the results indicate that primary school students’ actual ICT competences and previous ICT experience are related to their accuracy of ICT self-efficacy. As this study is one of the first to investigate primary school students’ accuracy and bias of ICT self-efficacy and to identify potential explanatory variables, it provides new insights into the nature of ICT self-efficacy.     

Extending metric multidimensional scaling with Bregman divergences

Sum of weighted square distance errors has been a popular way of defining stress function for metric multidimensional scaling (MMDS) like the Sammon mapping. In this paper we generalise this popular MMDS with Bregman divergences, as an example we show that the Sammon mapping can be thought of as a truncated Bregman MMDS (BMMDS) and we show that the full BMMDS improves upon the Sammon mapping on some standard data sets and investigate the reasons underlying this improvement. We then extend a well known family of MMDS, that deploy a strategy of focusing on small distances, with BMMDS and investigate limitations of the strategy empirically. Then an opposite strategy is introduced to create another family of BMMDS that gives increasing mapping quality. A data preprocessing method and a distance matrix preprocessing are introduced.     

基于MSD的图像感兴趣区域自动提取方法研究

将单幅图像数据进行分割,获得高维化后的数据集合,再依据图像数据的最优分解来提取不同图像块之间的数字关联,利用多维尺度分析(MDS)方法来获取单幅图像数据不同块之间的低维表示。通过对此低维表示的自动分析,便可获得图像感兴趣区域的精确位置。的实例验证了方法的可行性、有效性。     

无线传感器网络距离自调整的MDS定位算法

定位技术是无线传感器网络中的关键支撑技术之一。针对移动无线传感器网络的特点,在深入分析现有多维定标节点定位算法的基础上,提出一种改进机制,即距离自调整的多维定标节点定位算法(SA_MDS)。该算法运用3种方法估算节点的两跳距离,然后自动调整节点间的估算距离,从而提高定位精度。仿真结果表明,采用SA_MDS算法,节点的定位精度有较大提高。     

Partially observed distance mapping for cooperative multi-robot localization

This paper presents a distance mapping-based multi-robot localization method, which works with incomplete data. We make three contributions. First, we propose the use of multi dimensional scaling (MDS) for multi-robot localization. Second, we formulate the problem to accommodate partial observations common in multi-robot settings. We solve the resulting optimization problem using “scaling by majorizing a complicated function,” a popular algorithm for iterative MDS. Third, we take advantage of the motion information of robots to help the optimization procedure. Three policies are compared at each time step: random, previous, and prediction (constructed by combining the previous pose estimates with motion information). Using extensive empirical results, we show that the initialization by the prediction method results in better performance in terms of both accuracy and speed when compared to the other two initialization techniques.     

On the information and representation of non-Euclidean pairwise data

Two common data representations are mostly used in intelligent data analysis, namely the vectorial and the pairwise representation. Pairwise data which satisfy the restrictive conditions of Euclidean spaces can be faithfully translated into a Euclidean vectorial representation by embedding. Non-metric pairwise data with violations of symmetry, reflexivity or triangle inequality pose a substantial conceptual problem for pattern recognition since the amount of predictive structural information beyond what can be measured by embeddings is unclear. We show by systematic modeling of non-Euclidean pairwise data that there exists metric violations which can carry valuable problem specific information. Furthermore, Euclidean and non-metric data can be unified on the level of structural information contained in the data. Stable component analysis selects linear subspaces which are particularly insensitive to data fluctuations. Experimental results from different domains support our pattern recognition strategy.     

I-Scal: Multidimensional scaling of interval dissimilarities

Multidimensional scaling aims at reconstructing dissimilarities between pairs of objects by distances in a low-dimensional space. However, in some cases the dissimilarity itself is unknown, but the range of the dissimilarity is given. Such fuzzy data give rise to a data matrix in which each dissimilarity is an interval of values. These interval dissimilarities are modelled by the ranges of the distances defined as the minimum and maximum distance between two rectangles representing the objects. Previously, two approaches for such data have been proposed and one of them is investigated. A new algorithm called I-Scal is developed. Because I-Scal is based on iterative majorization it has the advantage that each iteration is guaranteed to improve the solution until no improvement is possible. In addition, a rational start configuration is proposed that is helpful in locating a good quality local minima. In a simulation study, the quality of this algorithm is investigated and I-Scal is compared with one previously proposed algorithm. Finally, I-Scal is applied on an empirical example of dissimilarity intervals of sounds.     

Multidimensional scaling as a method for assessing internal conceptual models of inspection tasks

Modelling the decision making component of inspection is hampered by an incomplete understanding of the way in which humans internally represent information about inspection tasks. This paper describes the use of multidimensional scaling (MDS) as a method for assessing the internal conceptual models used by inspectors. In this research six subjects were trained to inspect and classify a visually presented simulated product into one of four quality control categories. A methodology using a pairwise similarity procedure and a MDS analysis of the obtained ratings was used to track the evolution of an inspector's conceptual model and to relate the internal structure of that model to the inspector's performance. The results demonstrated the ability of the method to track the development of the decision maker's model during learning and revealed the relation between a well structured model and performance.     

专业技术考核自动出卷系统的数据库开发

阐述了专业技术考核自动出卷系统的数据库结构、设计思想和技术难点；并简述了PowerBuilder语言、VBA编程、嵌入式SQL语句的特点和应用，以及该软件的通用性和发展前景。     

基于多维尺度分析的自适应室内群终端定位方法

室内定位是普适计算领域的热点研究问题。当前,室内定位方法主要分为基于信号传播模型的定位方法和基于无线信号指纹的定位方法。其中,基于指纹的方法由于不需要知道无线信号接入点(Access Point,AP)的位置而得到更加广泛的应用, 其需要通过离线阶段采集大量数据来构建丰富的指纹库,满足这一条件需要大量的人工标定工作。对此,文中提出了一种基于指纹空间关系的定位方法,相比于传统的指纹定位方法,该方法无需建立指纹库,只需要通过获取多终端的 Wi-Fi 信号强度,计算所有终端的不相似度并构建不相似矩阵;通过多维尺度分析(Multidimensional Scaling,MDS)算法,构建出所有终端的位置分布图,进而通过确定其中 3 个以上终端的位置来定位所有的终端。采用支持向量回归机(Support Vector Regression,SVR)计算任意终端间的距离,并将距离矩阵作为不相似矩阵。文中在商场场景下选择了约2500m²的区域进行实验,所提方法的平均定位误差约为7m。     

Ethical judgments and behaviors: Applying a multidimensional ethics scale to measuring ICT ethics of college students

Assuming that ICT ethics are influenced by both moral and circumstantial factors, the study investigates Japanese college students’ ethical judgments and behavioral intentions in three scenarios involving ICT-related ethical problems and explores why they make such decisions, relying on five moral philosophies: moral equity, relativism, contractualism, egoism, and utilitarianism. The findings reveal that except for egoism, four moral dimensions affect ethical decisions of Japanese college students, each having different effects according to the particular ethical situation presented. Overall, the concepts of justice, fairness and moral rightness were found to influence these students’ ethical judgments in all ICT-related ethical dilemmas; legal obligations and benefits to society were found to have a weaker impact. It was also found that the students may behave unethically in ICT-related matters if these behaviors are perceived as culturally or traditionally acceptable or not perceived to be morally wrong. In conclusion, further research is suggested to analyze various scenario effects on students’ ICT-related ethical decisions and to investigate how cultural, professional and other environmental factors affect ethical decision-making. The establishment of a coherent ICT ethics policy in colleges is also proposed.