Examining Temporal Regularity in Categorical Team Communication Using Sample Entropy

Abstract

Communication is inherent to team coordination and performance. Nonlinear time-series measures, such as Sample Entropy (SEn), provide the opportunity to examine the temporal structure of team communication. The aim for this experiment was to develop a method for applying SEn to a set of categorically coded and sequential team verbal communications recorded during a dyadic Air Battle Management (ABM) simulation. Results showed that deterministic temporal regularity was detected in team communication for three categorical coding schemes applied to the data -team role, semantic content, and combined. For data coded for semantic content, SEn was able to detect an increase in communication temporal regularity for teams exposed to high workload. Practical and theoretical implications are considered.

Problem‐Solving Phase Transitions During Team Collaboration

“…Note that adopting this approach may require either the use of speaker-only codes (i.e., codes that only represent speaker and not semantic content; cf. Strang et al, 2012;Parker et al, 2016, when exploring alternative coding systems) or the use of methods from computational linguistics that can semantically categorize single utterances in near real time (e.g., Angus et al, 2012). Alternatively, one could use more fundamental linguistic aspects such as the categorization of vocal frequency (Black et al, 2013) or speech/pause dynamics (Fusaroli & Tyl en, 2016).…”

An Investigation of Coding Schemes for Sample Entropy Analysis of Communications Data

“…Recently, nonlinear time series analysis techniques, which can be used to characterise the degrees of temporal variation (or complexity) in complex rhythmic signals, have been successfully applied to team communications data. These approaches provide new insights into team communication dynamics while complementing information derived from other more "established" analytical approaches (Gorman, Cooke, Amazeen & Fouse, 2012;Strang, et al, 2012). In general, results from these recent studies have described findings that align with a theory of optimal complexity (Stergiou, Harbourne & Cavanaugh, 2006;Stergiou & Decker, 2011), which posits complex rhythmic systems exhibit optimal and efficient performance when they exhibit a combination of both deterministic (predictable) and stochastic (unpredictable) behaviour, i.e., systems are optimal when they exhibit simultaneous stability and flexibility.…”

Temporal Complexity in Team Coordination Associated with Increased Performance in a Fast-Paced Puzzle Task

“…SEn parameters M and r were set at 2 and 0, respectively, for type time series following the recommendations and procedures described in Strang et al (2012) for examining nominal data.…”

“…In a recent experiment, Strang et al (2012) used Sample Entropy (SEn; Richman & Moorman, 2000) to examine temporal structure in categorically coded team communications made by teams performing a simulated air defense task. The main findings from that study were: a) confirmation that meaningful temporal structure existed in team communication (i.e., communication patterns were not random, but instead contained semideterministic temporal structure), and b) SEn values were influenced by experimental manipulationcommunication exhibited lower complexity (decreased SEn) in teams exposed to high task difficulty.…”