Using process-oriented, sequencing educational technologies: Some important pedagogical issues

In recent times, sequencing technologies are becoming increasingly used, both by the university and the industry sectors. In essence, these complex systems support sequencing of, and navigation through units of content. They come in two different types: SCORM-based and workflow-based systems. Current research efforts related to sequencing technologies concentrate mostly on technical issues, while the associated pedagogical issues remain unexplored.The main objective of this paper is to describe the most important pedagogical issues that need to be taken into account when implementing any type of sequencing educational technologies (either SCORM- or workflow-based). These issues were identified during an action-learning project related to the practical implementation of a workflow-based educational system. During the reflection phase of this project, these issues were then genarised, so they could be applied to any type of sequencing technology and in any application domain (teaching discipline). The paper describes how sequencing technology can be used to enable a more flexible learning experience (especially in terms of time and flexible learning pathways) and then proceeds with the detailed analysis of the associated pedagogical issues.     

Nanoindentation mapping of mechanical properties of cement paste and natural rocks

This paper reports a study to assess nanoindentation mapping of mechanical properties of cement paste and natural rocks. Initial work seems to show that mechanical property mapping by nanoindentation is feasible and can be related to microscopic information. Further work is however required on the effect of indent size and spacing. Such a testing technique can be very useful for materials with different phases to study the intrinsic properties of each component, and also the interaction and properties of the interfacial regions of different phases. The values of Young's modulus and hardness of the individual mineral phases were also determined by statistically analysing a large number of experimental data.     

Support vector regression methodology for prediction of input displacement of adaptive compliant robotic gripper

The prerequisite for new versatile grippers is the capability to locate and perceive protests in their surroundings. It is realized that automated controllers are profoundly nonlinear frameworks, and a faultless numerical model is hard to get, in this way making it troublesome to control utilizing tried and true procedure. Here, a design of an adaptive compliant gripper is presented. This design of the gripper has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize specific shapes of the grasping objects. Since the conventional control strategy is a very challenging task, soft computing based controllers are considered as potential candidates for such an application. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) to estimate and predict optimal inputs displacement of the gripper according to experimental tests and shapes of grasping objects. Instead of minimizing the observed training error, SVR _poly and SVR _rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR approach compared to other soft computing methodology.     

Developing a model to assess the success of e-learning systems: evidence from a manufacturing company in transitional economy

This paper examines the success of an e-learning system in a company from the perspective of employees by using a multimethod approach. For this purpose Moodle learning management system was used. The success of e-learning as an information system was evaluated using four constructs of the updated DeLone and McLean IS success model—system quality, use, user satisfaction and net benefits, and adding one more construct—user performance. In this research a combination of observation and survey as two different research methods was used, which allowed the new measure to be incorporated into the model. Empirical assessment was carried out by exploratory factor analysis, confirmatory factor analysis and structural equation modeling. The research model was found to be valid and reliable. The results provide an expanded understanding of the constructs that measure the success of an e-learning system, helping to more deeply understand the key success dimensions and their interrelationships. The implications of our work were discussed. The DeLone and McLean IS success model applied equally well. However, the use of observation as a method of data collection revealed the weaknesses of the original model.     

Relatedness between numerically small Dutch Red dairy cattle populations and possibilities for multibreed genomic prediction

Red dairy breeds are a valuable cultural and historical asset, and often a source of unique genetic diversity. However, they have difficulties competing with other, more productive, dairy breeds. Improving competitiveness of Red dairy breeds, by accelerating their genetic improvement using genomic selection, may be a promising strategy to secure their long-term future. For many Red dairy breeds, establishing a sufficiently large breed-specific reference population for genomic prediction is often not possible, but may be overcome by adding individuals from another breed. Relatedness between breeds strongly decides the benefit of adding another breed to the reference population. To prioritize among available breeds, the effective number of chromosome segments (M_e) can be used as an indicator of relatedness between individuals from different breeds. The M_e is also an important parameter in determining the accuracy of genomic prediction. The M_e can be estimated both within a population and between 2 populations or breeds, as the reciprocal of the variance of genomic relationships. We investigated relatedness between 6 Dutch Red cattle breeds, Groningen White Headed (GWH), Dutch Friesian (DF), Meuse-Rhine-Yssel (MRY), Dutch Belted (DB), Deep Red (DR), and Improved Red (IR), focusing primarily on the M_e, to predict which of those breeds may benefit from including reference animals of the other breeds. All of these breeds, except MRY, are under high risk of extinction. Our results indicated high variability of M_e, especially between M_e ranging from ～3,500 to ～17,400, indicating different levels of relatedness between the breeds. Two clusters are especially important, one formed by MRY, DR, and IR, and the other comprising DF and DB. Although relatedness between breeds within each of these 2 clusters is high, across-breed genomic prediction is still limited by the current number of genotyped individuals, which for many breeds is low. However, adding MRY individuals would increase the reference population of DR substantially. We estimated that between 11 and 133 individuals from other breeds are needed to achieve accuracy of genomic prediction equivalent to using one additional individual from the same breed. Given the variation in size of the breeds in this study, the benefit of a multibreed reference population is expected to be lower for larger breeds than for the smaller ones.     

Exploring the tension between transparency and datification effects of open government IS through the lens of Complex Adaptive Systems

Government agencies worldwide continue their commitment to providing open data in order to increase transparency of education, healthcare and other public services. Focusing on open government information systems (IS) that provide performance-related data, this paper explores the ongoing tension between government’s goal of transparency and the resulting largely opaque datification effects. Our research insights are derived from an empirical longitudinal study of a controversial open government IS called My School, currently providing performance data on almost 10,000 schools in Australia. We investigate the tension between transparency intended with schools’ open performance data and datification effects they create within the education system and a broader society, through the theoretical lens of Complex Adaptive Systems (CAS). Our study reveals how the tension emerges due to unpredictable use, propagation and reinterpretation of open data by more and more users. Consequently, the original meaning of data gets distorted, as these users continue to reconstruct and reinterpret ‘data’ in their own contexts and adapt their behavior in pursuit of their strategic goals. We also identify and theorize seven datification patterns underlying the tension and the ways they produce various social consequences. Based on these research contributions we discuss important strategic implications for government decision makers and identify new opportunities for future research on open government IS.     

Variable neighbourhood simulated annealing algorithm for capacitated vehicle routing problems

This article presents the variable neighbourhood simulated annealing (VNSA) algorithm, a variant of the variable neighbourhood search (VNS) combined with simulated annealing (SA), for efficiently solving capacitated vehicle routing problems (CVRPs). In the new algorithm, the deterministic ‘Move or not’ criterion of the original VNS algorithm regarding the incumbent replacement is replaced by an SA probability, and the neighbourhood shifting of the original VNS (from near to far by k← k+1) is replaced by a neighbourhood shaking procedure following a specified rule. The geographical neighbourhood structure is introduced in constructing the neighbourhood structures for the CVRP of the string model. The proposed algorithm is tested against 39 well-known benchmark CVRP instances of different scales (small/middle, large, very large). The results show that the VNSA algorithm outperforms most existing algorithms in terms of computational effectiveness and efficiency, showing good performance in solving large and very large CVRPs.     

Semantic Mediation for Standard-Based B2B Interoperability

The authors discuss a semantic-mediation architecture to advance traditional approaches for standards-based business-to-business (B2B) interoperability. The architecture is supported by the Athena Knowledge Representation and Semantics Mediation tool suite. Initial experimentations with the architecture and the toolset offer discussions of key architectural and functional aspects and suggest directions for future tools enhancements.