This article describes a representation-based framework of distributed cognition. This framework considers distributed cognition as a cognitive system whose structures and processes are distributed between internal and external representations, across a group of individuals, and across space and time. The major issue for distributed research, under this framework, are the distribution, transformation, and propagation of information across the components of the distributed cognitive system and how they affect the performance of the system as a whole. To demonstrate the value of (...) this representation-based approach, the framework was used to describe and explain an important, challenging, and controversial issue — the concept of affordance. (shrink)

This article describes a representation-based framework of distributed cognition. This framework considers distributed cognition as a cognitive system whose structures and processes are distributed between internal and external representations, across a group of individuals, and across space and time. The major issue for distributed research, under this framework, are the distribution, transformation, and propagation of information across the components of the distributed cognitive system and how they affect the performance of the system as a whole. To demonstrate the value of (...) this representation-based approach, the framework was used to describe and explain an important, challenging, and controversial issue — the concept of affordance. (shrink)

Multiple theories of problem-solving hypothesize that there are distinct qualitative phases exhibited during effective problem-solving. However, limited research has attempted to identify when transitions between phases occur. We integrate theory on collaborative problem-solving with dynamical systems theory suggesting that when a system is undergoing a phase transition it should exhibit a peak in entropy and that entropy levels should also relate to team performance. Communications from 40 teams that collaborated on a complex problem were coded for occurrence of problem-solving processes. (...) We applied a sliding window entropy technique to each team's communications and specified criteria for identifying data points that qualify as peaks and determining which peaks were robust. We used multilevel modeling, and provide a qualitative example, to evaluate whether phases exhibit distinct distributions of communication processes. We also tested whether there was a relationship between entropy values at transition points and CPS performance. We found that a proportion of entropy peaks was robust and that the relative occurrence of communication codes varied significantly across phases. Peaks in entropy thus corresponded to qualitative shifts in teams’ CPS communications, providing empirical evidence that teams exhibit phase transitions during CPS. Also, lower average levels of entropy at the phase transition points predicted better CPS performance. We specify future directions to improve understanding of phase transitions during CPS, and collaborative cognition, more broadly. (shrink)

We investigated the coupling between a speaker's and a listener's eye movements. Some participants talked extemporaneously about a television show whose cast members they were viewing on a screen in front of them. Later, other participants listened to these monologues while viewing the same screen. Eye movements were recorded for all speakers and listeners. According to cross-recurrence analysis, a listener's eye movements most closely matched a speaker's eye movements at a delay of 2 sec. Indeed, the more closely a listener's (...) eye movements were coupled with a speaker's, the better the listener did on a comprehension test. In a second experiment, low-level visual cues were used to manipulate the listeners' eye movements, and these, in turn, influenced their latencies to comprehension questions. Just as eye movements reflect the mental state of an individual, the coupling between a speaker's and a listener's eye movements reflects the success of their communication. (shrink)

Cognitive science normally takes the individual agent as its unit of analysis. In many human endeavors, however, the outcomes of interest are not determined entirely by the information processing properties of individuals. Nor can they be inferred from the properties of the individual agents, alone, no matter how detailed the knowledge of the properties of those individuals may be. In commercial aviation, for example, the successful completion of a flight is produced by a system that typically includes two or more (...) pilots interacting with each other and with a suite of technological devices. This article presents a theoretical framework that takes a distributed, socio‐technical system rather than an individual mind as its primary unit of analysis. This framework is explicitly cognitive in that it is concerned with how information is represented and how representations are transformed and propagated in the performance of tasks. An analysis of a memory task in the cockpit of a commercial airliner shows how the cognitive properties of such distributed systems can differ radically from the cognitive properties of the individuals who inhabit them. (shrink)

Body movements, autonomic arousal, and electroencephalograms of group members are often coordinated or synchronized with those of other group members. Linear and nonlinear measures of synchronization have been developed for pairs of individuals, but little work has been done on measures of synchronization for groups. We define a new synchronization coefficient, SE, for a group based on pairwise correlations in time series data and employing the notions of a group driver, who most drives the group’s responses, and empath, who is (...) most driven by the group. SE is developed here in the context of emotional synchronization based on galvanic skin response time series. A simulation study explores its properties, the balance between strong versus weak autocorrelational effects, transfer, group size, and direct versus oscillatory functions. Distributions of SE are not affected by group size up to 16 members. Norms for interpreting the coefficient are presented along with directions for new research. (shrink)

This study investigates interpersonal processes underlying dialog by comparing two approaches, interactive alignment and interpersonal synergy, and assesses how they predict collective performance in a joint task. While the interactive alignment approach highlights imitative patterns between interlocutors, the synergy approach points to structural organization at the level of the interaction—such as complementary patterns straddling speech turns and interlocutors. We develop a general, quantitative method to assess lexical, prosodic, and speech/pause patterns related to the two approaches and their impact on collective (...) performance in a corpus of task-oriented conversations. The results show statistical presence of patterns relevant for both approaches. However, synergetic aspects of dialog provide the best statistical predictors of collective performance and adding aspects of the alignment approach does not improve the model. This suggests that structural organization at the level of the interaction plays a crucial role in task-oriented conversations, possibly constraining and integrating processes related to alignment. (shrink)