We hypothesize that effective collaboration is facilitated when individuals and environmental components form a synergy where they work together and regulate one another to produce stable patterns of behavior, or regularity, as well as adaptively reorganize to form new behaviors, or irregularity. We tested this hypothesis in a study with 32 triads who collaboratively solved a challenging visual computer programming task for 20 min following an introductory warm‐up phase. Multidimensional recurrence quantification analysis was used to examine fine‐grained (i.e., every 10 (...) s) collective patterns of regularity across team members' speech rate, body movement, and team interaction with the shared user interface. We found that teams exhibited significant patterns of regularity as compared to shuffled baselines, but there were no systematic trends in regularity across time. We also found that periods of regularity were associated with a reduction in overall behavior. Notably, the production of irregular behavior predicted expert‐coded metrics of collaborative activity, such as teams' ability to construct shared knowledge and effectively negotiate and coordinate execution of solutions, net of overall behavioral production and behavioral self‐similarity. Our findings support the theory that groups can interact to form interpersonal synergies and indicate that information about system‐level dynamics is a viable way to understand and predict effective collaborative processes. (shrink)

A key emergent property of group social dynamic is synchrony–the coordination of actions, emotions, or physiological processes between group members. Despite this fact and the inherent nested structure of groups, little research has assessed physiological synchronization between group members from a multi-level perspective, thus limiting a full understanding of the dynamics between members. To address this gap of knowledge we re-analyzed a large dataset comprising physiological and psychological data that were collected in two laboratory studies that involved two different social (...) group tasks. In both studies, following the group task, members reported their experience of group cohesion via questionnaires. We utilized a non-linear analysis method-multidimensional recurrence quantification analysis that allowed us to represent physiological synchronization in cardiological interbeat intervals between group members at the individual-level and at the group-level. We found that across studies and their conditions, the change in physiological synchrony from baseline to group interaction predicted a psychological sense of group cohesion. This result was evident both at the individual and the group levels and was not modified by the context of the interaction. The individual- and group-level effects were highly correlated. These results indicate that the relationship between synchrony and cohesion is a multilayered construct. We re-affirm the role of physiological synchrony for cohesion in groups. Future studies are needed to crystallize our understanding of the differences and similarities between synchrony at the individual-level and synchrony at the group level to illuminate under which conditions one of these levels has primacy, or how they interact. (shrink)

An emerging perspective on human cognition and performance sees it as a kind of self-organizing phenomenon involving dynamic coordination across the body, brain and environment. Measuring this coordination faces a major challenge. Time series obtained from such cognitive, behavioral, and physiological coordination are often complicated in terms of non-stationarity and non-linearity, and in terms of continuous vs. categorical scales. Researchers have proposed several analytical tools and frameworks. One method designed to overcome these complexities is recurrence quantification analysis, developed in the (...) study of non-linear dynamics. It has been applied in various domains, including linguistic data or motion data. However, most previous studies have applied recurrence methods individually to categorical or continuous data. To understand how complex coordination works, an integration of these types of behavior is needed. We aimed to integrate these methods to investigate the relationship between language and motion directly. To do so, we added temporal information to categorical data, and applied joint recurrence analysis methods to visualize and quantify speech-motion coordination coupling during a rap performance. We illustrate how new dynamic methods may capture this coordination in a small case-study design on this expert rap performance. We describe a case study suggesting this kind of dynamic analysis holds promise, and end by discussing the theoretical implications of studying complex performances of this kind as a dynamic, coordinated phenomenon. (shrink)

Cognitive Science, Volume 45, Issue 11, November 2021.

The dynamical hypothesis claims that cognitive systems, such as teams, are dynamical systems (i.e., an interdependent collection of individuals and their technology that change together over time). Following this hypothesis, team researchers have adopted dynamical approaches to better understand the team cognitive processes and states that form team cognition, as well as how they emerge over time. One approach focuses on team coordination dynamics, which examines the coupling of signals between interacting individuals in various modalities, and has been shown to (...) reflect aspects of team functioning including team cognition. However, how changes in team coordination relate to high-level team cognitive processes and states, as well as important events, are not yet fully understood. To this end, we advance a methodological framework for researching team cognition under the dynamical hypothesis. Subsequently, we provided an empirical case-study application of this framework. Thereby, this work contributes methodologically and empirically to a deeper understanding of team cognition, the dynamical hypothesis, and the synergy between them. (shrink)

Despite the challenges associated with virtually mediated communication, remote collaboration is a defining characteristic of online multiplayer gaming communities. Inspired by the teamwork exhibited by players in first-person shooter games, this study investigated the verbal and behavioral coordination of four-player teams playing a cooperative online video game. The game, Desert Herding, involved teams consisting of three ground players and one drone operator tasked to locate, corral, and contain evasive robot agents scattered across a large desert environment. Ground players could move (...) throughout the environment, while the drone operator’s role was akin to that of a “spectator” with a bird’s-eye view, with access to veridical information of the locations of teammates and the to-be-corralled agents. Categorical recurrence quantification analysis was used to measure the communication dynamics of teams as they completed the task. Demands on coordination were manipulated by varying the ground players’ ability to observe the environment with the use of game “fog.” Results show that catRQA was sensitive to changes to task visibility, with reductions in task visibility reorganizing how participants conversed during the game to maintain team situation awareness. The results are discussed in the context of future work that can address how team coordination can be augmented with the inclusion of artificial agents, as synthetic teammates. (shrink)

Over the past several decades, research in the cognitive sciences has foregrounded the importance of active bodies and their continuous dependence on the changing environment, strengthening the relevance of dynamical models. These models have been steadily developed within the ecological psychology approach to cognition, which arguably contributes to the “ecological turn” we are witnessing today. The embodied and situated nature of cognition, regarded by some as a passing trend, is presently becoming a largely accepted assumption. In this paper, I claim (...) that in light of these developments, ecological psychology, in alliance with related approaches, such as enactivism and interactivism, has the potential to deeply transform our perspectives on cognition and action, restoring their pertinence to humans as persons. However, an important challenge to the realization of this potential has to be noted: neither the mainstream information-processing approach nor the dynamics-oriented perspective on cognition provides an account of how the capacity of humans to use language and think “symbolically” can be derived from the continuous flow of agent−environment interaction. I will attempt to show that posing the “dynamical” and “computational” hypotheses about the nature of cognition as mutually exclusive approaches to cognition results in undesirable reductionism, which makes it difficult to meet this challenge. There are good reasons, advanced over half a century ago by, for example, Michael Polanyi or Howard Pattee, to think that we need complementary descriptions to understand cognizing systems, in order to grasp the fact that they are governed both by physical laws and by emergent historical constraints. Details of such a complementarity-based approach still await elucidation, but some proposed solutions have the potential to ease the tension between the information-processing and dynamical approaches to cognition and to lead to a better understanding of their interrelation. (shrink)

Emotional regularity is the degree to which a person maintains and returns to a set of emotional states over time. The present investigation examined associations between emotional regularity and extant emotion measures as well as psychologically relevant dimensions of personality, health, and real-world occupational outcomes. Participants included 598 U.S. adults who provided daily experience sampling reports on their emotional states for approximately two months. Results suggest that emotional regularity was related to, but distinct from, well-established measures of emotion including emotional (...) intensity, variability, covariation, inertia, granularity, and emodiversity. Furthermore, emotional regularity significantly predicted measures of personality, psychological health, and occupational outcomes even when accounting for extant emotion measures and sociodemographic covariates. Finally, it explained modest (7.5%) improvement (in terms of cross-validated RSq.) over baseline models containing emotional intensity, variability, and sociodemographic covariates. These findings suggest that emotional regularity may provide an important indicator of healthy emotional functioning and may be a promising area for further scientific discovery. (shrink)