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Social presence is an important construct in online group learning. It influences the way how social interaction unfolds online and affects learning and social outcomes. However, what precisely social presence is has been under debate, as presently a plethora of different definitions and measures exist preventing the development of a coherent research field regarding social presence and its defining role in online group learning. To solve the issue, we went back to the original social presence theory as devised by the communication researchers Short et al. (1976) to show that although they had a clear idea of social presence—namely “realness” of other persons in the interaction—their definition is ambiguous, not operationalizable, and the measurement of it questionable. We, therefore, disentangled their social presence theory and (1) reformulated the social presence definition to enable an operationalization in line with the previous conceptualization of social presence; (2) departed from the technological determinism of social presence; and (3) identified two other constructs closely linked to social presence, namely, sociability (as a medium attribute) and social space (as a group attribute). By reformulating the definition of social presence and by linking it to social space and sociability, we hope to contribute to a more coherent line of social presence research and to better understand interpersonal communication, group learning, and group dynamics when learning and working together in an online setting.

Although a large proportion of our lives are spent participating in social interactions, the investigation of the neural mechanisms supporting these interactions has largely been restricted to situations of social observation — that is, situations in which an individual observes a social stimulus without opportunity for interaction. In recent years, efforts have been made to develop a truly social, or ‘second-person’, neuroscientific approach to these investigations in which neural processes are examined within the context of a real-time reciprocal social interaction. These developments have helped to elucidate the behavioural and neural mechanisms of social interactions; however, further theoretical and methodological innovations are still needed. Findings to date suggest that the neural mechanisms supporting social interaction differ from those involved in social observation and highlight a role of the so-called ‘mentalizing network’ as important in this distinction. Taking social interaction seriously may also be particularly important for the advancement of the neuroscientific study of different psychiatric conditions.Studies that examine brain activity during real-time social interactions may advance our understanding of human social behaviour. Redcay and Schilbach describe progress in ‘second-person’ neuroscience and discuss the insights into the brain mechanisms of social behaviour that have been gained.

Social influence is the process by which individuals adapt their opinion, revise their beliefs, or change their behavior as a result of social interactions with other people. In our strongly interconnected society, social influence plays a prominent role in many self-organized phenomena such as herding in cultural markets, the spread of ideas and innovations, and the amplification of fears during epidemics. Yet, the mechanisms of opinion formation remain poorly understood, and existing physics-based models lack systematic empirical validation. Here, we report two controlled experiments showing how participants answering factual questions revise their initial judgments after being exposed to the opinion and confidence level of others. Based on the observation of 59 experimental subjects exposed to peer-opinion for 15 different items, we draw an influence map that describes the strength of peer influence during interactions. A simple process model derived from our observations demonstrates how opinions in a group of interacting people can converge or split over repeated interactions. In particular, we identify two major attractors of opinion: (i) the expert effect, induced by the presence of a highly confident individual in the group, and (ii) the majority effect, caused by the presence of a critical mass of laypeople sharing similar opinions. Additional simulations reveal the existence of a tipping point at which one attractor will dominate over the other, driving collective opinion in a given direction. These findings have implications for understanding the mechanisms of public opinion formation and managing conflicting situations in which self-confident and better informed minorities challenge the views of a large uninformed majority.

This paper estimates peer effects in a university context where students are randomly assigned to sections. While students benefit from better peers on average, low-achieving students are harmed by high-achieving peers. Analyzing students’ course evaluations suggests that peer effects are driven by improved group interaction rather than adjustments in teachers’ behavior or students’ effort. Building on Angrist’s research, we further show that classical measurement error in a setting where group assignment is systematic can lead to a substantial overestimation of peer effects. However, when group assignment is random—like in our setting—peer effect estimates are biased toward zero.

The purpose of this article is to provide a scoping review of the current literature on group flow. Based on the PRISMA-guidelines for systematic reviews, 26 publications were identified that met the inclusion criteria. Publication analyses comprised an individual consideration of each publication and a systematic, integrative synthesis of all publications. Analyses identified heterogeneous group flow definitions across publications, supporting the need for an integrative definition. Further heterogeneity existed in the theoretical approaches and measures used, highlighting the need for a comprehensive theory and a measurement standard. Components (e.g., synchronization), antecedents (e.g., trust), and outcomes (e.g., well-being) of group flow were identified in publications that presented empirical studies, some of which that showed similarities between characteristics of group flow and individual flow and others that showed aspects unique to group flow. Overall, this scoping review reveals the need for a systematic research program on group flow.

Collective dynamics emerge from countless individual decisions. Yet, we poorly understand the processes governing dynamically-interacting individuals in human collectives under realistic conditions. We present a naturalistic immersive-reality experiment where groups of participants searched for rewards in different environments, studying how individuals weigh personal and social information and how this shapes individual and collective outcomes. Capturing high-resolution visual-spatial data, behavioral analyses revealed individual-level gains—but group-level losses—of high social information use and spatial proximity in environments with concentrated (vs. distributed) resources. Incentivizing participants at the group (vs. individual) level facilitated adaptation to concentrated environments, buffering apparently excessive scrounging. To infer discrete choices from unconstrained interactions and uncover the underlying decision mechanisms, we developed an unsupervised Social Hidden Markov Decision model. Computational results showed that participants were more sensitive to social information in concentrated environments frequently switching to a social relocation state where they approach successful group members. Group-level incentives reduced participants’ overall responsiveness to social information and promoted higher selectivity over time. Finally, mapping group-level spatio-temporal dynamics through time-lagged regressions revealed a collective exploration-exploitation trade-off across different timescales. Our study unravels the processes linking individual-level strategies to emerging collective dynamics, and provides tools to investigate decision-making in freely-interacting collectives. Individual decisions drive the dynamics of collective systems. Here, the authors use an immersive-reality experiment to show that group incentives reduce social information use and improve performance in naturalistic collectives.

This article is on collective phenomena in pedestrian dynamics during the assembling and dispersal of gatherings. To date pedestrian dynamics have been primarily studied in the natural and engineering sciences. Pedestrians are analyzed and modeled as driven particles revealing self-organizing phenomena and complex transport characteristics. However, pedestrians in crowds also behave as living beings according to stimulus-response mechanisms or act as human subjects on the basis of social norms, social identities or strategies. To show where pedestrian dynamics need social psychology in addition to the natural sciences we propose the application of three categories-phenomena, behavior and action. They permit a clear discrimination between situations in which minimal models from the natural sciences are appropriate and those in which sociological and psychological concepts are needed. To demonstrate the necessity of this framework, an experiment in which a large group of people (n = 270) enters a concert hall through two different spatial barrier structures is analyzed. These two structures correspond to everyday situations such as boarding trains and access to immigration desks. Methods from the natural and social sciences are applied. Firstly, physical measurements show the influence of the spatial structure on the dynamics of the entrance procedure. Density, waiting time and speed of progress show large variations. Secondly, a questionnaire study (n = 60) reveals how people perceive and evaluate these entrance situations. Markedly different expectations, social norms and strategies are associated with the two spatial structures. The results from the questionnaire study do not always conform to objective physical measures, indicating the limitations of models which are based on objective physical measures alone and which neglect subjective perspectives.

Sociomotor theory – an extension of ideomotor theory – suggests that actions can also be represented in terms of the effects they elicit from others. But what if those others violate one’s action effect anticipations? Here, we introduce a novel joint goal-setting paradigm to investigate effects of co-actors’ occasional and overall unreliability on an individual’s goal selection. In a first step, the participant moved a target halfway from the bottom center to the top left or right corner of the computer screen. In the second step, the co-actor moved the target to its final left or right position. In a learning block, the co-actor always continued the participant’s target movements. In the test block(s), the co-actor produced congruent action effects in 50% (unreliable) vs. 80% (reliable co-actor) of the trials. Experiment 1 consisted of one (between-participants), Experiment 2 and 3 of two (within-participants) test blocks; in Experiment 3, the co-actor changed between blocks. Results of Experiments 1 and 3 reveal that participants repeated their corner choice more often after incongruent trials, but only when the co-actor was generally reliable. Implications in terms of sociomotor action control and joint action are discussed.

In social interactions, own actions often trigger a particular response from another person. The sociomotor framework proposes that this consistent behavior of others can become incorporated into own action control. In line with this idea, recent studies have shown that own motor actions are facilitated if they are predictably being imitated rather than counterimitated by a social interaction partner. In the present study, we investigated whether this finding is influenced by the relationship between the interacting persons. To that end, we manipulated whether a participant was being imitated and counterimitated by an ingroup or by an outgroup member. In two experiments, we found a beneficial influence of being imitated irrespective of group membership. The results suggest that, while people incorporated their partner's behavior into own action control, this was not further qualified by group membership as a higher-order social variable. This finding points to a universal account of action control for actions with social action effects and actions with inanimate action effects alike.

Group awareness is of critical relevance for collaborative learning and interaction and is thus often referred to in CSCL research. However, the concept is only vaguely defined as some kind of understanding or perception of characteristics of learning partners or the collaborating group. Most CSCL research activities concerned with group awareness aim at modifying learners' awareness using so-called group awareness tools. However, there are much less attempts to measure group awareness and to conceptualize its formation. Thus, building on existing group awareness research, this article derives a conceptualization with six defining aspects of group awareness: (1) group awareness is cognitive, (2) group awareness is conscious, (3) group awareness is current, (4) group awareness is individual, (5) group awareness is social, and (6) group awareness is perceived as valid. Additionally, while it is often assumed that group awareness builds on self-regulatory skills, its role in regulating behavior and cognition within a social context is seldom explored. Thus, this article aims at defining and analyzing the concept of group awareness, specifying its relation to regulatory processes, and sketching possible research paths whilst building on, complementing, and informing tool-driven research.