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

School-based interventions for socially including autistic pupils in mainstream schools were systematically reviewed. Included interventions targeted at least one level of the school environment: the autistic children, the peers, the staff, and/or the physical environment, and assessed autistic pupils’ quantity and/or quality of social participation as outcome measures. Findings from 56 studies showed increased accessibility of school activities to autistic pupils, but the reciprocity and friendship between the autistic pupils and the peers were not necessarily improved. Moreover, limited interventions were available for modifying the physical environment. A more holistic strategy that moves the focus from individual children’s social skills to the larger context surrounding children, should be considered for a better inclusion of autistic children in school routine.

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Many autistic youths experience restricted school participation. The present study investigated the influences of youth, family and school factors on autistic youths’ school participation. Parents of 200 Dutch autistic youths (age range: 4–16 years, M age = 12.23 years, SD age = 2.93 years) filled in questionnaires in a national survey for autistic individuals, reporting the school participation, age and autistic traits of their child, parents’ education level and self-efficacy for supporting their child’s schoolwork, and the impact of problems their child experienced with the physical and social environments of the school. Multivariate linear regression analysis using imputed data revealed that among the six predictor variables, only the impact of problems autistic youths experienced with the physical environment of school was negatively associated with their school participation. This study provided support for the essential role of the school environment in predicting autistic youths’ school participation, indicating that problematic aspects in the school environment could have a greater impact on autistic youths’ school participation than youth factors or family factors. This highlights the need to create a more accommodating environment at school, where autistic youths can participate easily and comfortably.@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 connectedness at school is crucial to children's development, yet very little is known about the way it has been affected by school closures during COVID-19 pandemic. We compared pre-post lockdown levels of social connectedness at a school playground in forty-three primary school-aged children, using wearable sensors, observations, peer nominations and self-reports. Upon school reopening, findings from sensors and peer nominations indicated increases in children's interaction time, network diversity and network centrality. Group observations indicated a decrease in no-play social interactions and an increase in children's involvement in social play. Explorative analyses did not reveal relations between changes in peer connectedness and pre-lockdown levels of peer connectedness or social contact during the lockdown period. Findings pointed at the role of recess in contributing to children's social well-being and the importance of attending to their social needs upon reopening.

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Background: Outdoor social participation in the school playground is crucial for children's socio-emotional and cognitive development. Yet, many children with disabilities in mainstream educational settings are not socially included within their peer group. We examined whether loose-parts-play (LPP), a common and cost-effective intervention that changes the playground play environment to enhance child-led free play, can promote social participation for children with and without disabilities. Method: Forty-two primary school children, out of whom three had hearing loss or autism, were assessed for two baseline and four intervention sessions. We applied a mixed-method design, combining advanced sensors methodology, observations, peer nominations, self-reports, qualitative field notes and an interview with the playground teachers. Results: Findings indicated for all children a decrease during the intervention in social interactions and social play and no change in network centrality. Children without disabilities displayed also an increase in solitude play and in the diversity of interacting partners. Enjoyment of LPP was high for all children, yet children with disabilities did not benefit socially from the intervention and became even more isolated compared with baseline level. Conclusions: Social participation in the schoolyard of children with and without disabilities did not improve during LPP in a mainstream setting. Findings emphasize the need to consider the social needs of children with disabilities when designing playground interventions and to re-think about LPP philosophy and practices to adapt them to inclusive settings and goals.

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Detecting and analyzing group behavior from spatio-temporal trajectories is an interesting topic in various domains, such as autonomous driving, urban computing, and social sciences. This paper revisits the group detection problem from spatio-temporal trajectories and proposes “WavenetNRI”, a graph neural network (GNN) based method. The proposed WavenetNRI extends the previously proposed neural relational inference (NRI) method (an unsupervised learning approach for inferring interactions from observational data) in two directions: (1) symmetric edge features and edge updating processes are applied to generate symmetric edge representations corresponding to the symmetric binary group relationships; (2) a gated dilated residual causal convolutional (GD-RCC) block is adopted to capture both short and long dependency of the edge feature sequences. We evaluated the performance of the proposed model on three simulation datasets and three real-world pedestrian datasets, using the Group Mitre metric to measure the quality of the predicted groups. We compared WavenetNRI with four baseline methods, including two clustering-based and two classification-based methods. In these experiments, NRI and WavenetNRI outperformed all other baselines on the group-interaction simulation datasets, while NRI performed slightly better than WavenetNRI. On the pedestrian datasets, the WavenetNRI outperformed other classification-based baselines. However, it did not compete against the clustering-based methods. Our ablation study showed that while both proposed changes cannot be effective at the same time, either of them can improve the performance of the original NRI on one dataset type.

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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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Video games frequently feature 'open world' environments, designed to motivate exploration. Level design patterns are implemented to invoke curiosity and to guide player behavior. However, evidence of the efficacy of such patterns has remained theoretical. This study presents an empirical study of how level design patterns impact curiosity-driven exploration in a 3D open-world video game. 254 participants played a game in an empirical study using a between-subjects factorial design, testing 4 variables: presence or absence of patterns, goal or open-ended, nature and alien aesthetic, and assured or unassured compensation. Data collection consisted of in-game metrics and emotion word prompts as well as post-game questionnaires. Results show that design patterns invoke heightened exploration, but this effect is influenced by the presence of an explicit goal or monetary compensation. There appear to be many motivations behind exploratory behavior in games, with patterns raising expectations in players. A disposition for curiosity (i.e. 'trait curiosity') was not found to influence exploration. We interpret and discuss the impact of the conditions, individual patterns, and player motivations. @en

Curiosity is a strong motivator for human action, but the circumstances under which one becomes curious are not clear. This paper builds on the assumption that video games can be used as a stimulus for the experimental study of curiosity, and forms a basis in examining the type of curiosity motivated by spatial exploration. A video game was created that incorporates five proposed ‘game design patterns’ that may induce curiosity in players. The game, Shinobi Valley, was tested in a pilot study with 24 participants. Participants responded positively to the game and exhibited exploratory behaviour while playing without specifically being prompted to do so. The presented results suggest which of the patterns are most promising in inducing curiosity, and show that the game is of sufficient quality to be used in larger studies.

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