The aim of this explorative research study was to identify the relationship between the positions of individual students in their peer social networks and their classroom seating arrangement through sociometry and social network analysis. We examined the social networks of 17 classrooms comprising 363 students (183 boys, 180 girls) attending lower secondary schools (ISCED 2A). We found that positions in social networks could not be connected with single specific seating positions. Nonetheless, certain tendencies can be observed. Students who are perceived as more likeable sit in the middle column of the classroom and are seated close to each other. Locations inhabited by dominant students are positioned further from teachers and further apart from each other. The increase of the values of degree centrality, closeness centrality, and eigenvector centrality is noticeable in desks positioned further away from the teacher. By comparing these results with studies examining seating arrangements as a means of distributing learning opportunities through student participation, specific zones can be observed in the classroom that could benefit the children seated there in their roles as students and at the same time in their roles as classmates.
The paper presents to Czech social scientists an introductory review of the concept of equivalence and the method of blockmodeling in social network analysis (SNA). After introducing the central concepts of SNA such as node and tie, along with their basic metrics such as centrality and cohesion, I present the concepts of role and position. These are treated by SNA as clusters of nodes with similar ties, something I juxtapose to algorithms to identify cohesive subgroups of nodes. Subsequently, I define and compare the two most frequently applied types of equivalence - structural, which is strict but broadly applicable, and regular, which is more liberal but has limited uses. Structural equivalence builds on a strict definition of similarity of ties, treating as equivalent only such nodes that have the same ties to the same other nodes. Regular equivalence works with looser criteria and better corresponds with both the theoretical and the intuitive notions of role; this, however, is outweighed by the absence of a unique regular-equivalent solution within a network and by the difficulty to process networks with undirected ties. Regular-equivalent nodes are such that have ties to other mutually equivalent nodes. I present examples to demonstrate the differences between both definitions. In the following section, I discuss measurement of similarity between the different nodes’ profiles of ties (e.g., correlation and Euclidean distance) and possible uses of the standard statistical methods of cluster analysis and multidimensional scaling to detect equivalent classes of nodes within networks. After pointing to the weaknesses of these techniques in network data analysis, I present blockmodeling as a method designed specifically to identify roles and positions within networks. Ischematize the blockmodeling procedure and present its basic terms before comparing classic inductive blockmodeling, which is primarily fit for the purposes of exploration and network reduction, with deductive generalized blockmodeling, which is applicable in testing hypotheses about basic structural characteristics of a network. I bring attention to the strengths and weaknesses of both approaches. Relatedly, I present an application of blockmodeling especially for the purposes of simplified network representation, comparing structural patterns across networks, and testing structural theories. In the following section, I demonstrate specific blockmodeling algorithms based on both structural equivalence (CONCOR and Tabu Search optimization) and regular equivalence (REGE and Tabu Search optimization). Then I verify the adequacy of their resulting assignment of positions to nodes using eta coefficient, Q modularity and correlation of the ideal blocked and the empirical adjacency matrices. In the concluding section, I demonstrate the entire blockmodeling procedure on an empirical case of a small network with undirected ties using the UCINET software tool, including interpretation of results. Finally, I reflect the contemporary position of blockmodeling among leading research approaches in SNA, referring to other empirically oriented studies that demonstrate the broad applicability and utility of position analysis., Tomáš Diviák., and Obsahuje použitou literaturu a poznámky
Analýza sociálnych sietí si svojim širokým využitím nachádza miesto v množstve vedeckých odborov. V pedagogickom výskume má potenciál odhaliť a preskúmať doteraz neznáme usporiadania vzťahov medzi aktérmi vo vzdelávaní. Tento článok poskytuje úvod do problematiky, techník a využitia analýz y sociálnych sietí v pedagogickom výskume. V prvom rade predstavuje základnú terminológiu a koncepty analýz y sociálnych sietí. Na príklade malej siete ilustruje základné sieťové výpočty tak na úrovni jednotlivých aktérov, ako na úrovni celej siete. Článok ďalej poskytuje stručný prehľad štúdií z pedagogického výskumu, v ktorých bola analýza sociálnych sietí využitá. Hlavná časť článku na príklade fiktívnej triedy a piatich výskumných otázok ukazuje možnosti analýz y sociálnych sietí v pedagogickom výskume od základnej prierezovej analýz y po dynamickú inferenčnú analýzu. Krok za krokom sú predstavené rôzne metódy s následnou interpretáciou ich výsledkov. Okrem výpočtov centralít, klastrovacieho koeficientu a prepojenosti siete sú v príkladoch predstavené aj permutačné testy pri testovaní významnosti za využitia sieťových dát, ERGM (exponential random graph models) a STERGM (separable temporal exponential graph models). V neposlednom rade sú prediskutované problémy spojené s využitím analýz y sociálnych sietí. and With its wide range of applications, social network analysis has found its place in a number of scientific fields. In educational research, social network analysis has the potential to uncover and investigate yet unknown configurations of relationships among actors in education. This paper provides an introduction to the issues, techniques, and applications of social network analysis in educational research. It first surveys the basic terminolog y and concepts in social network analysis. Using the example of a small network, it demonstrates basic network calculations at the level of both the individual actors and the network as a whole. Furthermore, the paper provides a brief overview of studies in the field of educational research that have employed social network analysis. Using the example of a fictional classroom and five research questions, the main part of the paper demonstrates the application of social network analysis in educational research ranging from crosssectional descriptive analysis to dynamic inferential analysis. Step by step, it introduces a range of methods and interprets their results. In addition to centrality, clustering, and connectedness measures, the example contains permutation tests used for significance testing with network data, exponential random graph models (ERGM), and separable temporal exponential graph models (STERGM). Finally, the paper discusses challenges related to the application of social network analysis.
Cílem exploratorně orientované studie je zmapovat sociální sítě autorů a publikačních zdrojů v pedagogických vědách v letech 2009–2013. Studie je založena na metodologii analýzy sociální sítě (social network analysis – SNA), která začíná získávat stále větší pozornost i v kontextu českého pedagogického výzkumu. V rámci studie jsou využita data z hodnocení výsledků výzkumných organizací, která jsou v ČR pravidelně shromažďována za účelem národního hodnocení výzkumných institucí. Článek předkládá hlavní z jištění exploratorní analýzy a dává k dispozici doplňující interaktivní nástroje pro další průzkum dat. and The aim of this exploratory study is to analyze the social networks of authors and publication resources in educational sciences between 2009 and 2013. The study is based on the methodology of social network analysis which has been gaining increasing attention even within educational sciences in the Czech Republic. The study makes use of data about research and development results that are regularly collected for the purposes of national evaluations of research institutions. The paper presents the main findings of the exploratory analysis and makes available additional interactive tools for further exploration of the data.
The present article deals with the diffusion of the predominantly female Roman cult of Bona Dea. In order to contextualize and preliminarily assess Attilio Mastrocinque's (2011, 2014) hypothesis of a top-down imperial organization of the cult, supervised by empress Livia herself, both gendered constraints to mobility and the Augustan marriage ban are taken into account and evaluated. Epistemological and methodological limitations of social network analysis in the field of ancient history are carefully appraised before tackling the relationships between hypothetical imperial support and quantitative diffusion of the cult. As an alternative methodological approach, Donald W. Meinig's model of dynamic cultural regions is adopted, and adapted, to suggest a possible spatial and diachronic pattern of diffusion.
Engaging in positive relationships with peers is highly important for children's learning and development. In the present study, social network analyses were used to investigate how children's language competence affects their peer relationships in the context of early childhood classrooms. A total of 13 classrooms (N = 248 children) participated. Children's language competence was measured using tests for oral communicative competence and receptive vocabulary knowledge. Furthermore, a sociometric method was used to obtain network data. Outcomes of social network analyses showed that children are more likely to form relationships with children with high and similar levels of receptive vocabulary knowledge. In addition, weak support was found for the hypothesis that children form relationships with children with high levels of oral communicative competence.