Network distance and centrality shape social learning in the classroom.

Abstract

Social learning can help individuals to efficiently acquire knowledge and skills. In the classroom, social learning often takes place in structured settings in which peers help, support, and tutor each other. Several protocols have been developed to make peer-assisted learning (PAL) more efficient. However, little attention has been devoted to how the transfer of knowledge is shaped by the social relationship between peers, and their relative positions in the social network. To address this gap, we combined social network analysis with an experimental social learning task, in which pupils (N = 135; aged 11-19) could use social information from their peers to improve their performance. We show that pupils' tendencies to use social information substantially decrease with the peer's distance in the social network. This effect is mediated by subjective closeness: pupils report feeling much closer to their friends than to their non-friends, and closeness strongly enhances social learning. Our results further show that, above and beyond these effects of network distance, social information use increases with the peer's social status (network centrality) and perceived smartness. Our results provide empirical evidence in a naturalistic setting for the role of specific network attributes in shaping pupils' willingness to learn from their peers. These findings illustrate the value of a social network approach for understanding knowledge transfer in the classroom and can be used to structure more effective peer learning. Impact and ImplicationsThis study shows how social network analyses can help teachers and practitioners boost learning outcomes. Social network data can inform matching of pupils for peer learning, and can help cultivating social cohesion in the classroom. Collecting social network data is a fast and cheap procedure, and may be easily incorporated in existing protocols aimed at promoting peer learning, knowledge transfer and positive school culture.

Social influence in adolescence as a double-edged sword

“…In real life, however, the social information that might influence individuals depends on their position in their social network, and individuals' social learning strategies (e.g. to preferentially heed familiar individuals, experts or prestigious sources [68][69][70][71][72]). This introduces asymmetries in the social environments that individuals observe, determining, for example, whether rule compliance and generosity are perceived to be common, and whether rule violations and selfishness are typically disapproved of [38,71,73].…”

YouTube vloggers set the stage: How public (non)compliance with COVID‐19 regulations affects adolescents

“…Vloggers are popular among adolescents, and adolescents are more likely to copy high‐status peers' behaviors compared with low‐status peers (Bandura, 1977; Choukas‐Bradley et al, 2015; Cohen & Prinstein, 2006; Gradassi et al, 2022). On YouTube, vloggers can receive supportive or dismissive evaluations from their viewers, in terms of (dis)likes and positive or negative comments, which communicates injunctive norms about how behavior is rewarded.…”

Social learning across adolescence: A Bayesian neurocognitive perspective

“…Information from an expert is likely to be more reliable than from a novice leading to more informational social influence exerted by the former, and copying normative behavior displayed by a high versus a low status peer might impact your own social status more, especially when you find yourself transitioning from one social group to another. A demonstrator’s performance or reliability, for example, indeed are important factors for social information use ( Morgan et al, 2012 , Olsen et al, 2019 , Gradassi et al, 2022 ). In addition to a demonstrator’s objective performance, conveyed performance or subjective confidence statements heavily influence copying behavior, such that more confident people, or people who state that they are more confident, exert more influence over both group and individual decisions ( Gradassi et al, 2022 , no date; Zarnoth and Sniezek, 1997 ; Morgan et al, 2012 ; Moussaïd et al, 2013 ), as do more extreme opinions ( Price and Stone, 2004 , da Silva Pinho et al, 2021 ).…”

“…Indeed, peer characteristics pertaining to social relations and group structure have been identified to influence to what extent these peers influence others’ behavior ( Kendal et al, 2018 ). For example, high school students are more strongly influenced in their perceptual decision making by classmates who are perceived as more popular or who are socially closer ( Gradassi et al, 2022 ). Additionally, decisions or judgements made by groups of people tend to be more influential when that group is larger and when there is higher consensus within that group ( Morgan et al, 2012 , Moussaïd et al, 2013 , Molleman et al, 2020 , da Silva Pinho et al, 2021 ).…”