Sociograms

Context

In a recent news article, the Ministry of Education (MOE) announced that there will be more focus in mental wellness and peer support in schools soon, as the Character and Citizenship Education (CCE) curriculum is being refreshed for 2021.  Besides this interesting nugget of information; "As specialised skills may be needed to facilitate discussion of complex or sensitive topics,  every secondary school will have specialised CCE teachers by 2022.", I was reminded of something some colleagues and I explored in my previous school. SOCIOGRAMS. Sociograms are graphic representation of social links that a person has. It is a graph drawing that plots the structure of interpersonal relations in a group situation (Moreno,1934).

Sociograms are visual representations of social networks

Expert's take on Sociograms
Roger Banerjee, a Professor of Developmental Psychology at the University of Sussex, head of the CRESS (Children's Relationships, Emotions, and Social Skills) Lab there and co-editor of the book 'Infant and Child Development' says that sociograms help teachers understand more about their class’s peer relationships. It helps teachers understand the class dynamics and it provides a visual tool to determine spheres of influence (or lack of) in the classroom.

He explains:

” Sociograms are made on the basis of pupils’ nominations of classmates in response to questions. The exact wording of the questions can vary depending on the interests of the teacher. But a common scenario involves asking pupils to nominate three classmates with whom they most like to play or spend time with, and three classmates with whom they least like to play or spend free time with.”

The Sociogram Tools on his website are based on over three decades of work on sociometric procedures, and provide a simple implementation of very widely-used nomination procedures for capturing levels of acceptance and rejection within the peer group. The site includes a sample sociometric survey which could be used directly or digitalised to facilitate in the creation of the sociogram.

Visualisation of a network

My own experience applying sociograms
Some of the more experienced teachers in my previous school including the HOD of Student Management did a study on the use of sociograms in 2018 as part of their Professional Learning Team(PLT). I was intrigued by their sharing that simple data collation of 3 names from each student in a class, could generate a pretty powerful tool for teachers. I took the initiative to join the PLT on student development in 2019 as I could contribute with some data crunching and I believed in the power of sociograms to improve peer interactions, teacher-student relationship and build a positive as well as healthy classroom environment.

Sample sociogram

As part of our study on the implementation of a peer support structure, we had to find a discerning way to choose peer leaders from the secondary 1 intake. What better way than to use data to support teacher's instincts/judgements. So, I created a Google Form (I can share if you really want, just reach out to me) to collate the names from the classes involved and plugged them in an online program by by Timothy Pratley called Leaderboardx.

A video by Timothy on how to use his platform to build sociograms

Basically, what I was able to create allowed the Student Leadership Committee to spot the students who stand out in class. They include the influencers (informal/formal leaders of cliques) and the  isolates (silent sufferers/loners) based on the number of arrows pointing to them. The Leaderboard web app also ranks the students in order of their influence using a page rank algorithm (originally used by Google for their search engine). Ideally, those ranked higher could be potential leaders due to their influence over others but teachers should also consider if they were good role models (if that was important) and that they speak up for the quieter one in the class too. Eventually, the peer leaders that the teachers chose based on their own professional judgement mostly tallied with the top ranking students based on the sociogram. Then, we trained the peer leaders (2 from each class) on help seeking and help giving (CHEER) and rolled out our intervention strategies to the secondary 1 classes. We wanted to determine if the peer support structure was able to improve students' intrinsic motivation levels but that would be a potential topic of discussion for a future post.

Sociogram for my own form class

In my experience using sociograms for various purposes in my previous school, I realised that it was helpful for my sensing of the social-emotional state (to follow up with guidance and conversations) of specific students and peer dynamics of the different groups in school. I tried out with my form class and found surprising results. For example, a boy in class was often seen surrounded by classmates but he was never chosen as a students others would want to work with even in his closest circle of friends. Trying out with the student council, I realised that the higher ranked members who were eventually interviewed to join the executive committee (exco) make up a majority of the finalised exco list. I suppose a massive one could be done amongst students in a whole level to see if there are opportunities to improve social mixing at bigger level. My worry is if the data (PDPA and all) gets leaked  to the students who are being analysed or if they start asking questions as to why the survey or question is asked then it coud lead to a tricky situation. That is why the sociogram users of the data will need to be objective and professional about the process so that the potential benefit to students' development can be maximised.

Student Council group members selection

Conclusion

All in all, I must say that the sociogram is a good tool to have but it is not the end all be all. Rather, only users who truly know what to look out for in the sociograms and then follow-up accordingly will be able to fully maximise the potential of the visual representation of the class social networks.

Update: I found this excel macro that may be helpful in generating the sociogram directly on excel. 

Credits for this Excel program to Rhyd Lewis: LewisR9@cf.ac.uk, www.RhydLewis.eu. [seems like the macros do not work well]

Instructions for Use

The Excel program can be downloaded here. Once downloaded, all relevant information should be input into the Data worksheet as illustrated in the screenshot below. To collect this data, a survey should be conducted within the classroom. In this survey each child should first be asked to nominate up to three students that they most like (ML) and up to three students that they least like (LL). Further information on how to do this in a safe and valid way can be found here.

 

The collected information should then be typed into the spreadsheet. Specifically, each child should be allocated an ID number, and the ID numbers for their ML and LL nominations should be listed alongside.

 

Once the data has been typed in, the sociogram program is executed by clicking on the button at the top-right of the spreadsheet. This will produce (a) a matrix summarising the data, and (b) a visualisation of the sociogram:

Interpreting the Matrix and Sociogram

The matrix reported by this program gives a summary of the data. A table is included at the bottom of the sheet that lists, for each student, how often they have been named as “Most Liked” (ML) and “Least Liked” (LL) by the other students.

 

The Sociogram produced by the Excel program gives a visual representation of the data. The following text, quoted verbatim from this webpage of Robin Banjeree, describes how to interpret this network.

 

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Each node represents a pupil, and the arrows indicate ML nominations. Single-headed black arrows indicate unreciprocated ML nominations and double-headed blue arrows indicate reciprocated ML nominations. If you included ML and LL nominations, then some pupils may be allocated to one of the following colour-coded peer status categories on the basis of the numbers of ML and LL nominations received:

 

·         Popular (coloured green): received high numbers of ML nominations and low numbers of LL nominations. The majority of pupils with this classification tend to be prosocial, showing socially competent behaviour.

·         Rejected (coloured grey): received low numbers of ML nominations and high numbers of LL nominations. This is considered to be the most 'at-risk' peer status classification, as it is often associated with externalising and/or internalising problems. This also tends to be the most stable peer status classification, with some pupils experiencing multiple years of peer rejection. Further assessment of these pupils, measuring their feelings and their patterns of thinking, will be important for supporting these pupils' development in targeted work. In addition, the links in the sociogram will provide valuable information for supporting and managing these pupils in groupwork.

·         Controversial (coloured orange): received high numbers of ML nominations and high numbers of LL nominations. This classification tends to be less stable, but pupils falling into this category can be highly influential. They are often dominant characters who are perceived to be highly popular, yet they may be aggressive, disruptive, and even intimidating. Because of their influence, work with these pupils can have a substantial impact on the classroom ethos.

·         Neglected (coloured pink): received low numbers of ML nominations and low numbers of LL nominations. This classification is generally seen as less problematic than the Rejected category. Research often finds that these pupils -- despite having low social impact -- are well-adjusted, although they may have a reputation for shyness.

 

Bear in mind that the peer status allocations are based on statistical cutoffs. There may be other pupils in the class/group who fall just short of the threshold for one of these peer status categories. Please examine your Excel spreadsheet to see the exact numbers of ML and LL nominations received by each pupil.