Group awareness tools: It’s what you do with it that matters

This study examined the effect of using a group awareness tool on online collaboration. Furthermore, we examined whether the effect of using a group awareness tool on online collaboration is mediated by group awareness (i.e., students’ awareness of their group members’ levels of participation). To answer these questions, we determined how often and how long 107 secondary education students used the Participation-tool (PT), a group awareness tool designed to visualize group members’ relative contribution to the online collaborative process. Our analyses show that duration of PT use (how long students displayed the tool on their screens) significantly predicted group members’ participation in the online dialogue, their participation when writing collaborative texts, equality of participation within the group, and coordination and regulation of activities in the relational space (i.e., discussing the collaboration process with group members). No effect of using the PT on group performance was found. Mediation analyses showed that the effect of using the PT is only partially mediated by group awareness: an indirect effect of using the PT, via enhanced awareness of participation, on student participation during chat discussions and the collaborative writing process was found.     

Psychosocial causes and consequences of pathological gaming

Pathological use of computer and video games has been associated with indicators of psychosocial well-being, such as loneliness, low self-esteem, low social competence, and low life satisfaction. However, few studies have decisively demonstrated whether these indicators of psychosocial well-being are causes or consequences of pathological gaming. To address this gap in the literature, we conducted a two-wave panel study among 851 Dutch adolescents (543 gamers). Causal relations were analyzed using autoregressive structural equation models. These analyses indicated that social competence, self-esteem, and loneliness were significant predictors of pathological gaming six months later. Thus, lower psychosocial well-being can be considered an antecedent of pathological gaming among adolescent gamers. Our analyses further indicated that loneliness was also a consequence of pathological gaming. This suggests that displacement of real-world social interaction resulting from pathological use of video games may deteriorate existing relationships, which could explain the increase in adolescent gamers’ feelings of loneliness.     

An expertise reversal effect of segmentation in learning from animated worked-out examples

Many animations impose a high cognitive load due to the transience of information, which often hampers learning. Segmentation, that is presenting animations in pieces (i.e., segments), has been proposed as a means to reduce this high cognitive load. The expertise reversal effect shows, however, that design measures that have a positive effect on cognitive load and learning for students with lower levels of prior knowledge, might not be effective, or might even have a negative effect on cognitive load and learning for students with higher levels of prior knowledge. This experiment with animated worked-out examples showed an expertise reversal effect of segmentation: segmented animations were more efficient than continuous animations (i.e., equal test performance with lower investment of mental effort during learning) for students with lower levels of prior knowledge, but not for students with higher levels of prior knowledge.     

Adding semantics to image-region annotations with the Name-It-Game

In this paper we present the Name-It-Game, an interactive multimedia game fostering the swift creation of a large data set of region-based image annotations. Compared to existing annotation games, we consider an added semantic structure, by means of the WordNet ontology, the main innovation of the Name-It-Game. Using an ontology-powered game, instead of the more traditional annotation tools, potentially makes region-based image labeling more fun and accessible for every type of user. However, the current games often present the players with hard-to-guess objects. To prevent this from happening in the Name-It-Game, we successfully identify WordNet categories which filter out hard-to-guess objects. To verify the speed of the annotation process, we compare the online Name-It-Game with a desktop tool with similar features. Results show that the Name-It-Game outperforms this tool for semantic region-based image labeling. Lastly, we measure the accuracy of the produced segmentations and compare them with carefully created LabelMe segmentations. Judging from the quantitative and qualitative results, we believe the segmentations are competitive to those of LabelMe, especially when averaged over multiple games. By adding semantics to region-based image annotations, using the Name-It-Game, we have opened up an efficient means to provide precious labels in a playful manner.     

Iterative Learning Control for uncertain systems: Robust monotonic convergence analysis

In this paper, we present a novel Robust Monotonic Convergence (RMC) analysis approach for finite time interval Iterative Learning Control (ILC) for uncertain systems. For that purpose, a finite time interval model for uncertain systems is introduced. This model is subsequently used in an RMC analysis based on μ analysis. As a result, we can handle additive and multiplicative uncertainty models in the RMC problem formulation, analyze RMC of linear time invariant MIMO systems controlled by any linear trial invariant ILC controller, and formulate additional straightforward RMC conditions for ILC controlled systems. To illustrate the derived results, we analyze the RMC properties of linear quadratic (LQ) norm optimal ILC.     

Suppressing intersample behavior in iterative learning control

Iterative Learning Control (ILC) is a control strategy to improve the performance of digital batch repetitive processes. Due to its digital implementation, discrete time ILC approaches do not guarantee good intersample behavior. In fact, common discrete time ILC approaches may deteriorate the intersample behavior, thereby reducing the performance of the sampled-data system. In this paper, a generally applicable multirate ILC approach is presented that enables to balance the at-sample performance and the intersample behavior. Furthermore, key theoretical issues regarding multirate systems are addressed, including the time-varying nature of the multirate ILC setup. The proposed multirate ILC approach is shown to outperform discrete time ILC in realistic simulation examples.     

Local and Global Interactions in an Evolutionary Resource Game

Conditions for the emergence of cooperation in a spatial common-pool resource game are studied. This combines in a unique way local and global interactions. A fixed number of harvesters are located on a spatial grid. Harvesters choose among three strategies: defection, cooperation, and enforcement. Individual payoffs are affected by both global factors, namely, aggregate harvest and resource stock level, and local factors, such as the imposition of sanctions on neighbors by enforcers. The evolution of strategies in the population is driven by social learning through imitation, based on local interaction or locally available information. Numerous types of equilibria exist in these settings. An important new finding is that clusters of cooperators and enforcers can survive among large groups of defectors. We discuss how the results contrast with the non-spatial, but otherwise similar, game of Sethi and Somanathan (American Economic Review 86(4):766–789, 1996).      

Taxonomy for the Network and Service Management Research Field

Network and service management has established itself as a research field in the general area of computer networks. However, up to now, no appropriate organization of the field has been carried out in terms of a comprehensive list of terms and topics. In this paper, we introduce a taxonomy for network and service management. With such a taxonomy, it is possible to better understand the landscape of research as well as to reason about possible future challenges and opportunities. As such, in addition to the taxonomy itself, we also present an initial analysis of the field’s past, present, and future, based on the records of papers submitted and accepted in major conferences in the area, as well as a site survey performed through a questionnaire answered by experts from both industry and academia.