Making social learning capital visible: Peer networks of academically at-risk students

In this paper, we foreground a somewhat lesser known but increasingly prominent 21st century learning resource—social learning capital, broadly defined here as the ability to forge and tap into productive learning networks with peers and significant others. On the one hand, there are compelling theoretical reasons to suggest that social capital can serve as valuable learning resources for students, and bear great potential for buffering the detrimental effects of risk factors in the lives of academically at-risk learners. Specifically, an expanding body of literature upholds the positive role that peer relationships may play in the lives of adolescents. At the same time, however, given the double-edged nature of peer networks, it is hardly surprising to find indications of peer interactions posing negative effects on students’ behaviour and performance. It is important therefore, to have ways of assessing and understanding patterns and effects of students’ social learning networks in classrooms and schools, so that appropriate pedagogical strategies can be adopted where necessary to establish/strengthen productive networks and disrupt unproductive ones. This study explores the friendship networks that exist within 10 classes of Grade 7 students (N=200) from a Singapore school that has a strong educational programme for academically at-risk students. The participants were identified as academically at risk based on their performance in a national test that was given at the end of primary school. The authors will demonstrate how sociograms showing students’ friendship networks within each class were constructed, and how these social learning networks were analyzed qualitatively and quantitatively. Using regression analysis, the students’ network-based attributes were used to predict their academic motivation and engagement. The academic motivation and engagement of the students were also linked with those of their friends. Suggestions on how social network analysis can be utilized in teaching and developing intervention programmes for academically at-risk students will be discussed.