Exploring quantitative indicators for monitoring resilient team cognition

Abstract

Many human factors researchers have explored the cognitive and behavioral factors that affect team performance through behavioral and verbal protocol analyses. These studies primarily used qualitative analyses of observable behaviors and utterances, which makes it difficult to capture the dynamic and resilient team cooperation process directly. Therefore, it is necessary to develop quantitative indicators or measures to assess dynamic processes in team behavior and communication. Once such appropriate indicators or measures are developed, we can compare the performance of different teams quantitatively and find the features of team cognition that support good performance. In the study of complex problem solving, several studies calculated the entropies of utterances from the results of a qualitative analysis of team communication to detect phase changes in complex problem solving (Wiltshire and Butner, 2017). In addition to entropy, this study calculates the Kullback–Leibler divergence (KL) of utterances in segments for the entire team process to identify dynamic features and irregular segments in team communication. We applied the information theory to quantify the features of utterances in segments for the entire team process to find dynamic features and irregular segments in team communication. We analyzed the utterance data of a three-person team working on a task that required dynamic role assignment and collaboration. We first analyzed the turn-taking and communication contents and then visualized them using recurrence plots to visually find sequential patterns. We then calculated the Kullback–Leibler divergence (KL) and plotted it with sliding windows to analyze the dynamic features in team communication. The results showed that the bias of the content increased with disturbances, which suggests that the proposed indices can be used to capture speech distortions caused by external disturbances.