ABSTRACT
Today, most cultural training is based on or built around “cultural engagements” or discrete interactions between the individual learner and one or more cultural “others”. Often, success in the engagement is the end or the objective. In reality, these interactions usually involve secondary and tertiary effects with potentially wide ranging consequences that may result in changes to the attitudes of a populace. In these instances, attitude changes may travel, impacting both the immediate human terrain and that of neighbors located in other regions. The extent to which these cultural interactions branch across societies necessitates an approach to model this phenomenon. The concern is that learning culture within a strict engagement context, not accounting for this information transfer, might lead to “checklist” cultural thinking that will not empower learners to understand the full consequence of their actions. In this paper, we explore methods to create simulations, which more accurately relay the complex nature of a cross-cultural interaction. Understanding that accurately modeling human cultural and societal behaviors is extremely difficult we propose several methods to construct simulations that may serve as a first effort. The models described in this paper represent a broad effort to model information transfer across a large population and their reactionary behaviors. However, these models represent a blue print that we feel is repeatable and, over time, refine-able. Ultimately, we propose that the models we explore here serve as a baseline set for simulations of populace behavior which would not need
to completely capture accurate outcomes, but which would demonstrate to users the complexity of the cultural landscape. Thus, they would not necessarily support learning of what to do and think, but how to do and think. We begin by proposing the use of agent based modeling (ABM) to collect, store, and, simulating the effects of social networks and promulgate engagement effects over time, distance, and consequence. ABM is one method that allows us to capture individual behaviors, which we then aggregate to larger sections of a society. The information transfer, and subsequently storage of information, by agents in the model provides us the detail at the individual level to transfer information, and the ability at the macro level to demonstrate how it impacts populace behaviors. The ABM development allows for rapid adaptation to model any number of population types, extending the applicability of the model to any requirement for social modeling. From this point, we move to exploring other methods that may augment an ABM and create a more robust simulation tool. The results of our study demonstrate that creation of simulations to capture the effects cultural interactions over time and space is more ideal and relatively easy to implement. The results also highlight that cultural training programs need to capture and relay this sort of information to users in order to fully prepare them to function in cross-cultural settings. The framework we outline here would serve to augment a cultural training program which is focused on the cultural encounter and reinforce this process by adding the complex nature of a human network.
