Who students interact with? A social network analysis perspective on the use of Twitter in language learning

This paper reports student interaction patterns and self-reported results of using Twitter microblogging environment. The study employs longitudinal probabilistic social network analysis (SNA) to identify the patterns and trends of network dynamics. It is building on earlier works that explore associations of student achievement records with the observed network measures. It integrates gender as an additional variable and reports some relation with interaction patterns. Additionally, the paper reports the results of a questionnaire that enables further discussion on the communication patterns

Institutional factors influencing innovation adoption by dairy farmers in Ireland

Location-based resources are important factors in the entrepreneurial creation of wealth. This is as true in agriculture as it is in other industrial contexts. In this study, we are interested in how formal and informal institutions such as knowledge networks and localized ‘webs’ of influence act to facilitate or block innovation in the dairy farming industry. Our study of dairy farmers in Munster, Republic of Ireland (an intensive location for dairy farming), is located in a context in which there are policy-based interventions intended to improve the local economic environment. We are interested to know if these are effective, or if other factors within the institutional field are too strong and act to impede the take up of new ideas promoted within such initiatives. Our study uses neo institutional theory as the methodological lens through which we assess the interplay of structural factors within the field. Using interview accounts, we are looking for evidence of embedded institutional logics, interpretive schemas, knowledge blockages, and the role of formal institutions on the development of innovation within the field. Through undertaking a deep study of innovativeness in one locale, Munster, with the proviso that we use this as an illuminatory context and not one that is necessarily representative of a wider field, we contribute to an understanding of the influences on resistance to innovation in farming contexts, and to the wider theoretical field of agricultural economics

Stochastic Blockmodeling for the Analysis of Big Data

The aim of this paper is to consider the stochastic blockmodel to obtain clusters of units as regards patterns of similar relations; moreover we want to analyze the relations between clusters. Blockmodeling is a technique usually applied in social network analysis focusing on the relations between \u201cactors\u201d i.e. units. In our time people and devices constantly generate data. The network is generating location and other data that keeps services running and ready to use in every moment. This rapid development in the availability and access to data has induced the need for better analysis techniques to understand the various phenomena. Blockmodeling techniques and Clustering algorithms, can be used for this aim. In this paper application regards the Web

Enhancing young students' high-level talk by using cooperative learning within Success for All lessons

This study examined whether students achieved high-level talk during group work because of involvement in cooperative learning within the Success for All (SfA) program. SfA is a comprehensive school program in which cooperative learning plays a key role, in addition to several other components such as parental involvement and tutoring. A quasi-experimental design with a treatment and a control group was used. At the end of the school year, grade-1 students (6- and 7-years-old children) executed a group task in small groups of four students. At that moment, SfA students had experienced cooperative learning within SfA lessons for a whole school year. In total, 160 students participated in this study. Using a coding scheme the quality of student's talk during group work was compared between treatment and control group. Compared to the control group, SfA students showed more high-level talk. SfA students expressed more extended elaborations of propositions and asked more open elaboration questions. Hence, the results of this study suggest that cooperative learning activities within SfA-lessons contributed to students' high-level talk.</p

Critical phenomena in exponential random graphs

The exponential family of random graphs is one of the most promising class of network models. Dependence between the random edges is defined through certain finite subgraphs, analogous to the use of potential energy to provide dependence between particle states in a grand canonical ensemble of statistical physics. By adjusting the specific values of these subgraph densities, one can analyze the influence of various local features on the global structure of the network. Loosely put, a phase transition occurs when a singularity arises in the limiting free energy density, as it is the generating function for the limiting expectations of all thermodynamic observables. We derive the full phase diagram for a large family of 3-parameter exponential random graph models with attraction and show that they all consist of a first order surface phase transition bordered by a second order critical curve.Comment: 14 pages, 8 figure