The Structure of Cluster Knowledge Networks Uneven, not Pervasive and Collective

This study focuses on the relationship between industrial clustering and innovation. It contributes to this literature by showing two empirical properties of the cluster learning process: first, that the structure of the knowledge network in a cluster is related with the heterogeneous distribution of firm knowledge bases and, second, that business interactions and inter-firm knowledge flows are not highly co-occurring phenomena. In particular, this paper highlights how the heterogeneity of firms’ knowledge bases generates uneven distribution of knowledge and selective inter-firm learning. This study has been based on empirical evidence collected at firm level in three wine clusters in Italy and Chile. Methods of social network analysis have been applied to process the data.Industrial clusters, knowledge flows, business interactions, networks.

Forum participation plugin for Moodle: development and discussion

At present, a large amount of software has been created to analyze social networks, such as libraries to access online social networking APIs, software to draw graphs and tools to use and analyze networks. In fact, and because of the use of Moodle as standard Learning Management System at the University of Las Palmas de Gran Canaria, in 2009 was born the idea of creating a plugin for Moodle capable of analyzing forums in which students participate and of identifying the major players within the student network. This work is about the present state of such plugin, which provides useful information to teachers so that, through the use of social network analysis, allows them to make decisions to improve and promote participatory education. Here, we show the application of the plugin to three case studies, in two different universities, which allowed to evaluate its usefulness and to compare the information according to the variables that influenced each case study

Building relationships on social networking sites from a social work approach

Our current age of connectedness has facilitated a boom in interactive dynamics within social networking sites. It is, therefore, possible for the field of Social Work to draw on these advantages in order to connect with the unconnected by strengthening online mutual support networks among users. The aim of this article is to examine whether ‘connectedness’ in social networking sites improves online social capital and resilience of social service users. Through our analysis of social networks carried out on an experimental model, we observed the patterns of connectedness on Facebook of 50 social service end-users from Málaga, Spain. The detection of online communities through the modularity algorithm has allowed us to ascertain whether individuals’ offline realities mirror their online realities. At the same time, we examined the influence certain interactions (likes, comments, etc.) have on leadership through online ethnography. Finally, online social capital, understood as the combination of connectedness and online interaction, has been correlated with users’ resilience. The results reveal that both connectedness and interaction feed themselves and have correlations with resilience

Research on E-Learning in the Workplace 2000-2012: A Bibliometric Analysis of the Literature

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Gamifying massive online courses: effects on the social networks and course completion rates

This paper analyzes the e ects of gamification in the social network of a massive online course. An educational social-networking platform gathered information about the contributions of participants and about the social networks that were formed during the course. A gamification layer with three game elements (points, badges, and leaderboard) was then implemented in the online learning platform. Social network analysis (SNA) and principal component analysis (PCA) were used to analyze the di erences between a treatment and a comparison group (N = 591 and N = 427), using a set of 20 variables for each participant which quantified contributions to the learning platform as well as position and influence in the social network. The results of SNA show that gamification influences the structure of the social network of the course. The results also suggest that the variables cluster similarly for each group and that the linear combination of variables called the first component (F1) is a good descriptor of students’ work and position in the network. F1 can be used to build predictive models of course completion. The models show that the probability of passing the course increases more rapidly in the treatment (gamified) group.Spanish Ministry of Economic A airs and Digital Transformation (Grant TIN2014-54874-R) and Government of Comunidad de Madrid (Grant CM/JIN/2019-037).info:eu-repo/semantics/publishedVersio

A study on the influence of Korean middle school students' relationship through science class applying STAD cooperative learning

In order to find out the influence of Korean Middle School Students’ relationship by science class applying STAD cooperative learning, this study conducted a social network analysis and sought to analyze the communication networks within the group and identified the change process of the type. The subject of this study was 30 students of the second grade at the girls’ middle school located in Korea’s Metropolitan City. For five weeks, science class applying STAD Cooperative Learning was implemented in the ‘reproduction and generation’ chapter. First, the class social network analysis showed that all the prices of density, degree centrality, closeness centrality, and betweenness centrality have risen after science class applying STAD Cooperative Learning. Also, the classroom’s relationship index has improved. In other words, STAD Cooperative Learning encouraged interaction among students. Second, in order to research popularity, students’ centrality analysis through the class social network analysis showed that top-ranked students’ values of density, degree centrality, closeness centrality, and betweenness centrality appeared commonly high after science class applying STAD Cooperative Learning. Third, the analysis of the communication network change within six groups showed that all channel type appeared most often and circle type also appeared anew after science class applying STAD Cooperative Learning. In other words, it was possible to exchange information freely and communicate with all members of the group through STAD Cooperative LearningPeer Reviewe

Do birds of a feather flock together? Proximities and inter-clusters network

The present contribution develops on the analysis of clusters in terms of proximities by exploring the issue of distant inter-cluster collaborations. We mobilize different forms of proximity (geographic, cognitive, social) discussed in the literature in order to identify their respective influence on intercluster collaboration by taking the example of French Pôles de Compétitivité. Our results echo previous results applied to intra-cluster collaborations since inter-cluster collaboration mostly relies on a form of social capital due to the key roles played by relational and cognitive proximity. Finally, our results exhibit a negative influence of geographic distance on collaboration. JEL: C45, R12, R58 Keywords: clusters, network analysis, proximities, intercluster collaboration