Author: Dr Marc Sarazin
Studying networks means much more than going through Instagram accounts, or looking at how ambitious teachers try to get ahead of their peers.
Most people, when they hear the word “networks”, think of social media—of computers connected in the ether, somehow allowing us to send each other messages or like each other’s posts. The word “networking”, meanwhile, often connotes a mercenary attitude: it reminds us of an ambitious professional trying to get ahead, sometimes unfairly, through charm or persuasion.
But the concept of “social networks” has a far richer meaning. The field of study most closely associated with it, Social Network Analysis (“SNA”), has a long and distinguished history in the social sciences (Freeman, 2004
). This is especially true in education – where the earliest recorded attempt to map a classroom social network can arguably be traced back to 1880s Germany (Heidler et al, 2014
). Far from the idea of inanimate objects connected through technology, or of the calculating ‘networker’ acting with a disregard for others, “social networks” remind us of our fundamental interdependence
with other people. Studying social networks, in other words, means getting at the interconnectedness that defines our lives.
Core ideas in social network research
Fundamentally, social network research tells us that people don’t exist in a vacuum: We are all influenced by the people around us. However, it teaches us that how
we are influenced by them depends not only on the relationships that we
have, but also the relationships that they
have. This idea has been powerfully brought home during the COVID-19 pandemic. Our chances of being infected by the coronavirus depend not only on whom we interact with, but on the interactions of our social contacts. I can be at risk even if I only meet up with one person—if that person also regularly meets up with dozens of other people. Alternatively, and on a more positive note, whether I hear about the latest teaching innovations depends not only on how much I turn to my colleagues for information or advice—it also depends on how well-connected my colleagues, in turn, are (Moolenaar et al, 2011
From this fundamental idea comes the notion that, if you want to understand a complex working environment like a school, you need to study the collaborative relationships of every staff member—from the head teacher to part-time school employees, including janitors, psychologists or counselors—relationships which, together, make up the school’s collaboration networks. Whether teachers can make a difference in their jobs depends on the structure of these networks. For example, networks that are dense—that feature many relationships, often cutting across professional specialisms—have been found to promote a climate of collaboration and collective efficacy among teachers (Daly et al, 2010
, Ortega et al, 2019
). They could therefore help teachers support students from migrant backgrounds, as we hypothesise in the TEAMS project
At the same time, the resources that individual teachers have at their disposal can depend on teachers’ positions in their school’s networks (Penuel et al, 2009
)—not only how many collaborative relationships they have, but also whether they are connected to influential others. Teachers who are connected to specialist support services, or who bridge between these services and their teacher colleagues, could be very well placed to support students from diverse backgrounds. As such, they could play an important role in schools’ efforts to integrate migrant students.
Once again, these trends remain invisible unless we study every person working in a school, and each person’s interactions with their colleagues. Studying entire school networks, then, becomes pivotal, both for appraising the social resources at the disposal of schools and for developing schools’ capacities to include migrant students. It also, of course, allows scholars to produce network visualisations, which have long been used to provide rich feedback to research participants (e.g. Tubaro, 2019
). For example, the visualisations below come from a project that was a prelude to the TEAMS project (Pantic et al, 2021
). They show how, in the “Disa” school, a greater range of teachers were involved in intense collaboration around student support than in the “Vega” school (Disa and Vega are pseudonyms).
Measuring school collaboration networks is not without its challenges. It requires significant buy-in: If fewer than 70% – 80% of staff members respond to a social network survey, then the data may not accurately represent a school’s networks. Staff who do respond might not recall all their interactions, or even all the other people that work in their school, particularly if they haven’t seen them for a while due to school closures. To alleviate this, network researchers often use “rosters”, or lists of all staff members working in a school. However, this information, just like participants’ responses, needs to be managed sensitively. In particular, participant identities need to remain confidential, including in network visualisations. Finally, network methods call for a deep dialogue between researchers and participants, one where both parties build mutual understandings of what’s going on in the network (D’Angelo & Ryan, 2019
). These challenges notwithstanding, social network concepts and tools are invaluable for understanding the opportunities and constraints that schools face in integrating students from diverse backgrounds—not least of which, migrant students.
Image Copyright © 2021, Nataša Pantić et al, CC BY.
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Pantić, N., Galey, S., Florian, L., Joksimović, S., Viry, G., Gašević, D., Knutes Nyqvist, H., & Kyritsi, K. (2021). Making sense of teacher agency for change with social and epistemic network analysis. Journal of Educational Change. https://doi.org/10.1007/s10833-021-09413-7
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Tubaro, P. (2019). Whose results are these anyway? Reciprocity and the ethics of “giving back” after social network research. Social Networks, S037887331930070X. https://doi.org/10.1016/j.socnet.2019.10.003
Published 1 April 2021
Edited 6 April 2021