Search Results (4)

In the last decade there has been significant growth in the interest and application of using EEG (electroencephalography) outside of laboratory as well as in medical and clinical settings, for more ecological and mobile applications. However, for now such applications have mainly included military, educational, cognitive enhancement, and consumer-based games. Given the monetary and ecological advantages, consumer-grade EEG devices such as the Emotiv EPOC have emerged, however consumer-grade devices make certain compromises of data quality in order to become affordable and easy to use. The goal of this study was to investigate the reliability and accuracy of EPOC as compared to a research-grade device, Brainvision. To this end, we collected data from participants using both devices during three distinct cognitive tasks designed to elicit changes in arousal, valence, and cognitive load: namely, Affective Norms for English Words, International Affective Picture System, and the n-Back task. Our design and analytical strategies followed an ideographic person-level approach (electrode-wise analysis of vincentized repeated measures). We aimed to assess how well the Emotiv could differentiate between mental states using an Event-Related Band Power approach and EEG features such as amplitude and power, as compared to Brainvision. The Emotiv device was able to differentiate mental states during these tasks to some degree, however it was generally poorer than Brainvision, with smaller effect sizes. The Emotiv may be used with reasonable reliability and accuracy in ecological settings and in some clinical contexts (for example, for training professionals), however Brainvision or other, equivalent research-grade devices are still recommended for laboratory or medical based applications. Full article

The literature on the role of gestures in children with language delay (LD) is partial and controversial. The present study explores gestural production and modality of expression in children with LD and semantic and temporal relationships between gestures and words in gesture + word combinations. Thirty-three children participated (mean age, 26 months), who were recruited through a screening programme for LD. Cognitive skills, lexical abilities, and the use of spontaneous gestures in a naming task were evaluated when the children were 32 months old. When the children were 78 months old, their parents were interviewed to collect information about an eventual diagnosis of developmental language disorder (DLD). According to these data, the children fell into three groups: children with typical development (n = 13), children with LD who did not show DLD (transient LD; n = 9), and children with LD who showed DLD (n = 11). No significant differences emerged between the three groups for cognitive and lexical skills (comprehension and production), for number of gestures spontaneously produced, and for the sematic relationships between gestures and words. Differences emerged in the modality of expression, where children with transient LD produced more unimodal gestural utterances than typical-development children, and in the temporal relationships between gestures and words, where the children who would show DLD provided more frequent representational gestures before the spoken answer than typical-development children. We suggest a different function for gestures in children with T-LD, who used representational gestures to replace the spoken word they were not yet able to produce, and in children with LD-DLD, who used representational gestures to access spoken words. Full article

The proliferation of mobile devices in everyday life since the end of the 20th century has led to mobile applications for educational purposes and the creation of the research field of mobile learning. Despite the extended research interest on the effectiveness of this field, there is limited research on mobile learning for various social groups, such as refugees, students with learning difficulties and disabilities. Due to the unprecedented number (over one hundred million) of refugees during the second decade of the 21st century worldwide, many NGOs (Non-Governmental Organizations) and UN (United Nations) initiatives have proposed leveraging mobile learning for refugee educational needs. This research article focuses on mobile learning for refugee education. Namely, the present systematic literature review results from 2015 to 2020 will give a concrete picture of the recently existing mobile learning apps for refugees and their characteristics. According to the research findings, 15 characteristics were collected out of 14 applications. According to prior literature, areas of agreement or discrepancies in the field were found. Two new -to previous literature- characteristics were revealed: interwoven psychological and educational features and refugees’ cultural features in the apps. The summarization and categorization of the app’s characteristics aim to contribute to mobile learning research and impact game developers, educators, and NGOs according to refugee needs. The limitations of this study and issues for further exploration will also be discussed in the last sections. Full article

In this paper we formally define the hierarchical clustering network problem (HCNP) as the problem to find a good hierarchical partition of a network. This new problem focuses on the dynamic process of the clustering rather than on the final picture of the clustering process. To address it, we introduce a new hierarchical clustering algorithm in networks, based on a new shortest path betweenness measure. To calculate it, the communication between each pair of nodes is weighed by the importance of the nodes that establish this communication. The weights or importance associated to each pair of nodes are calculated as the Shapley value of a game, named as the linear modularity game. This new measure, (the node-game shortest path betweenness measure), is used to obtain a hierarchical partition of the network by eliminating the link with the highest value. To evaluate the performance of our algorithm, we introduce several criteria that allow us to compare different dendrograms of a network from two point of view: modularity and homogeneity. Finally, we propose a faster algorithm based on a simplification of the node-game shortest path betweenness measure, whose order is quadratic on sparse networks. This fast version is competitive from a computational point of view with other hierarchical fast algorithms, and, in general, it provides better results. Full article