Autistic children are often reported less socially connected, while recent studies show autistic children experiencing more loneliness in school than allistic (i.e. non-autistic) children, contradicting the traditional view that autistic children lack social motivation. This study aimed to understand individual differences in how social connectedness is construed, between and within groups of autistic and allistic pupils, using a multimethod approach. Forty-seven autistic and 52 neurodiverse-allistic classmates from two special primary schools participated (8–13 years). Proximity sensors worn by pupils on playgrounds during recess measured (1) total time in face-to-face contacts, (2) number of contact partners, and (3) centrality in playground networks. Peer reports measured (4) reciprocal friendships and (5) centrality in classmate networks. To evaluate their feelings of connectedness, pupils rated the level of loneliness in school. Compared with allistic pupils, autistic pupils had fewer reciprocal friendships, but similar total time in social contacts, number of partners, classmate/playground centrality, and levels of loneliness. Lower levels of loneliness related to higher classmate centrality in autistic children, but longer time in social contacts in allistic children. For these autistic children, being liked as part of a peer group seems essential. Understanding relevant differences in children’s needs could lead to a more welcoming school climate.@en

The present study aims to infer individuals’ social networks from their spatio-temporal behavior acquired via wearable sensors. Previously proposed static network metrics (e.g., centrality measures) cannot capture the complex temporal patterns in dynamic settings (e.g., children’s play in a schoolyard). Moreover, existing temporal metrics overlook the spatial context of interactions. This study aims first to introduce a novel metric on social networks in which both temporal and spatial aspects of the network are considered to unravel the spatio-temporal dynamics of human behavior. This metric can be used to understand how individuals utilize space to access their network, and how individuals are accessible by their network. We evaluate the proposed method on real data to show how the proposed metric impacts performance of a clustering task. Second, this metric is used to interpret interactions in a real-world dataset collected from children playing in a playground. Moreover, by considering spatial features, this metric provides unique knowledge of the spatio-temporal accessibility of individuals in a community, and more clearly captures pairwise accessibility compared with existing temporal metrics. Thus, it can facilitate domain scientists interested in understanding social behavior in the spatio-temporal context. Furthermore, We make our collected dataset publicly available for further research.

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Social participation at schoolyards is crucial for children’s development. Yet, schoolyard environments contain features that can hinder children’s social participation. In this paper, we empirically examine schoolyards to identify existing obstacles. Traditionally, this type of study requires huge amounts of detailed information about children in a given environment. Collecting such data is exceedingly difficult and expensive. In this study, we present a novel sensor data-driven approach for gathering this information and examining the effect of schoolyard environments on children's behaviours in light of schoolyard affordances and individual effectivities. Sensor data is collected from 150 children at two primary schools, using location trackers, proximity tags, and Multi-Motion receivers to measure locations, face-to-face contacts, and activities. Results show strong potential for this data-driven approach, as it allows collecting data from individuals and their interactions with schoolyard environments, examining the triad of physical, social, and cultural affordances in schoolyards, and identifying factors that significantly impact children's behaviours. Based on this approach, we further obtain better knowledge on the impact of these factors and identify limitations in schoolyard designs, which can inform schools, designers, and policymakers about current problems and practical solutions.

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