Groups of individuals need to coordinate in many real world
domains. However, coordination failure is common and not
well understood. There are few coordination measurements,
analyses focus on averaged data, and models lack coordination
strategies and clear correspondence to cognitive mechanisms.
Here, we present a thorough analysis of human data from a
difficult coordination scenario and a cognitive model implemented
within the ACT-R cognitive architecture to fit and explain
the data. Data were explored to better understand coordination
strategies and group dynamics. The cognitive model included
pre-game preferences, coordination strategies like signaling,
and other player choice predictions. This work highlights
the need for deeper data explorations and presents challenges
for modeling related to coordination dynamics, strategies,
and how players form beliefs about others.