A social network analysis of teaching and research collaboration in a teachers' virtual learning community

Abstract

Analysing the structure of a social network can help us understand the key factors influencing interaction and collaboration in a virtual learning community (VLC). Here, we describe the mechanisms used in social network analysis (SNA) to analyse the social network structure of a VLC for teachers and discuss the relationship between face‐to‐face and online collaborations. In contrast to previous research applying SNA to analyse measuring indexes alone, we emphasise the mechanisms combining SNA, questionnaires, content analysis and focus group interviews—the key methodology to analyse complex interaction in a VLC. On this basis, we present an analysis model for teachers' VLC and apply it to a teachers' VLC known as ‘IRIS’. The study participants comprised 172 K12 teachers aged between 25 and 55 years. This study collected collaboration data from 2006 to 2012 and analysed the social network structure using sociograms, centrality, cohesive subgroups, clique phenomenon, and matrix correlation of SNA. These findings suggest that face‐to‐face and online collaborations are both indispensable in teaching and in research and continuously supplement and remedy each other in professional development. Moreover, the model succeeded in accessing, describing and analysing the social network structure of a VLC.

Chinese undergraduate students' perceptions of mobile learning: Conceptions, learning profiles, and approaches

“…More learner‐centred learning activities could be conducted to underscore the importance of improved learner‐centred authority as assisted by mobile technology. Substantial work should focus on the surface‐supportive profile, which includes applying deep‐motive strategies to engage in m‐learning activities and the use of social network services to facilitate collaboration (Lin, Hu, Hu, & Liu, ).…”

“…More learner-centred learning activities could be conducted to underscore the importance of improved learner-centred authority as assisted by mobile technology. Substantial work should focus on the surface-supportive profile, which includes applying deep-motive strategies to engage in m-learning activities and the use of social network services to facilitate collaboration (Lin, Hu, Hu, & Liu, 2016 and WhatsApp rather than sharing ideas with their peers. However, for the mixed profile, a multidirectional communication as occur through among social network applications can facilitate collective efforts to produce creative works.…”

The moderating role of self-regulated learning in job characteristics and attitudes towards web-based continuing learning in the airlines workplace

“…This result might be better explained from the perspectives of both social support and self-regulated learning. On the one hand, Lin, Hu, Hu, and Liu (2016) demonstrated the benefits of web-based learning because learners could seek online support, while tutors could provide guidance online (via communicative platforms such as emails, instant messaging applications, blogs). On the other hand, Za et al (2014) demonstrated that employees who are inclined to learn through the processes of reflecting, sharing, receiving support and making adjustments (i.e., self-regulation) could effectively offer different contexts to foster transfer of their knowledge gained from oversimplified cases to conceptually complex situations.…”

Analysis of Learners’ Interactive Behaviours in Online Forum

“…The individual influence scope and socialized relationships among individuals in the network can be described by "cohesion" [5]. The importance of one individual to other individuals in the network is described by "centrality" [6]- [8]. The individuals in the social network consist of core members and peripheral members [9].…”

“…Hence the core members are more efficient for spreading information. Scholars constructed a three-dimensional analytical model to study the structural characteristics of cooperative networks [6]. Scholars also used SNA method to analyze the individuals' interactive behaviours and discuss the causes of some phenomenon [10].…”