Leveraging on Social Network Analysis (SNA) in Education

The world is facing a mental health crisis today

According to a study done by the Journal of the American Academy of Child and Adolescent Psychiatry¹, researchers found that at both the primary and secondary school level – children who were socially isolated experienced greater mental health difficulties and those who had exhibited problematic behaviours faced greater difficulty in coping with the social challenges that accompany their progression throughout their early school years.

This raises an important question for educators today – How can teachers better monitor and track the social dynamics amongst students? And what are some of the strategies they can employ to create an inclusive classroom environment while improving student outcomes? 

Introduction to Social Network Analysis (SNA)

As the future of education and edtech continues to evolve, one area of research that has rapidly gained traction is the concept of leveraging social network analysis (SNA) and its related tools. Historically, social network analysis has been used primarily in studying relationships and interactions between individuals or groups. SNA has also been widely used in a range of fields, mainly in the business, health and public sectors. 

So what is social network analysis and how does it work? From R.M. Kankaanranta, M. Hynninen & A. Lipponen’s literature review², social network analysis (SNA) is defined as a collection of methods and tools that could be used to study the relationships, interactions and communications between individuals or groups. It involves collecting data on the different connections between individuals and using that data to create visual representations of the network or networks, such as sociograms, graphs and matrices. From these visual representations, one can then identify patterns and trends.

SNA in the classroom

Within the classroom context, SNA is able to provide valuable insights into different classroom dynamics and showcase how students interact with one another. Through analysing the relationships and interactions between students, teachers can identify what are the social barriers to learning and comprehend how different classroom structures can impact student engagement and outcomes.

Two of the most important key concepts being used in social network analysis are centrality and triads. An individual or group’s relevance within the network is gauged by their centrality. It can be quantified in several ways, such as degree centrality, which counts the connections a person has, and betweenness centrality, which counts the instances in which a person is located on the shortest path between two other people in the network.

On the other hand, triads are sets of three individuals that have a relationship with one another. Triads can be examined to find clustering tendencies, or the propensity for specific people to be related to one another. This can be applied to find cliques or subgroups within a larger network.

Here at Dive Analytics, schools have also employed our social network analysis module within our Student Hub to examine their classroom dynamics across different grades and levels. They were able to determine patterns of clique development and how these cliques related to academic achievement by studying the data on students’ friendships and correlating them to other student attributes including grades, conduct, gender and more. 

Why should your school adopt Social Network Analysis (SNA)? 

For typical classroom sizes of 30 to 40 students, it can be quite challenging for form class teachers to understand each and every students’ friendship dynamics within the class. Often it is easy to know who are the more outspoken and popular student(s), but the challenge lies in identifying those who are more introverted and may be a potential outcast within the class.

There are many advantages to employing social network analysis in comprehending classroom dynamics³. Here are four strategies that we have seen educators use to remove social barriers and design more inclusive classrooms:

1. Targeted tutoring: 
   • Students who are not well-connected to their teachers or peers can be found via social network analysis. These students may be in danger of academic lagging behind and could benefit from specialised tutoring or mentoring. Additionally educators may make better decisions regarding how to set up their classrooms including changing seating layouts if they are aware of how various classroom arrangements affect their students’ engagement and learning. 
2. Bullying prevention: 
   • Social network analysis can be used to spot students who might be bullied. Designing interventions to deal with these problems and supporting the impacted students can be done using these insights.
3. Collaborative learning: 
   • Social network analysis can support more successful collaborative learning by detecting the patterns of interactions between students. This can be accomplished by pairing up students with similar study habits and learning styles so that they can collaborate more effectively.
4. Dissemination of information: 
   • Social network analysis can be used to comprehend information flow patterns, which is helpful for understanding how information is transferred among students. Teachers can also leverage on these important actors or nodes to disseminate information. 

Conclusion

In summary, social network analysis is a useful tool that can empower educators to better uncover social interactions amongst students in a classroom setting and beyond.   School leaders and form teachers are able to get a more complete view of their student dynamics instead of relying on instinct and guesswork. These insights allows them to introduce classroom interventions  more timely and achieve better student outcomes.

Connect with us and discover how our SNA tool can benefit your school today! 

References:

1. Matthews, T. et al. (2015) “Social isolation and mental health at primary and secondary school entry: A longitudinal cohort study,” Journal of the American Academy of Child & Adolescent Psychiatry, 54(3), pp. 225–232. Available at: https://doi.org/10.1016/j.jaac.2014.12.008.
2.  “Social network analysis in education: A review of the literature” by R.M. Kankaanranta, M. Hynninen & A. Lipponen, published in the Journal of Computer Assisted Learning. This paper provides an overview of the use of social network analysis in education research, and includes a summary of the key findings from relevant studies.
3. Saqr, M., Alamro, A. The role of social network analysis as a learning analytics tool in online problem based learning. BMC Med Educ 19, 160 (2019). https://doi.org/10.1186/s12909-019-1599-6