Research on human cognition in complex tasks, such as interacting with advanced technology, requires the development and validation of new methods. This paper describes PRONET, a method for summarizing, representing, and analyzing event sequences. The first section outlines how the PRONET method can be applied to any sequence of events, with lessons learned from previous applications of the method. The second section presents demonstrations of the application of PRONET. In the first demonstration - a computer-based simulation of operant training - the PRONET analysis and representation clearly shows the change in the behavior of the simulation produced by changes in reinforcement contingencies, but also shows interesting aspects of behavior that were not affected. In the second demonstration - involving transfer of word processing skill - network-related and performance measures showed the expected pattern of positive transfer. In addition, the network of the far transfer participant suggested that she used task knowledge to search for conditions that would permit the correct action. Two previously-published examples showed the usefulness of the PRONET method in characterizing a hybrid event sequence consisting of environmental conditions and behavioral actions and a sequence of events from a team.