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In-Depth Information
including subject matter expert first-person accounts, field reports, hand-authored
dialogs and dialog transcripts, and other sources. It supports the process of managing,
processing, and utilizing streams of updates to sociocultural data to keep the cultural
models up-to-date as new information is obtained or properties of the cultural
environment changes. It provides tools for comparing the behavior produced by
different character models, and for comparing different versions of the same character
model resulting from changes in the sociocultural data. The output of C-CORE will
be specifications for cultural simulations, including the cultural environment, scenario
logic, non-player characters and their behavior.
C-GAME, developed in coordination with C-CORE, is extending the overall
approach for cultural competence training, and developing it into an interoperable
framework that can be utilized with a variety of game engines and artificial
intelligence models. The cultural simulations in C-GAME will serve as rich learning
environments in which learners can develop their knowledge and awareness of the
culture, and then develop intercultural skills, all within the same environment.
The scenario construction toolset will enable trainers to develop their own
sociocultural training scenarios through a combination of libraries of reusable
sociocultural models and authoring tools. It will include mechanisms for
incorporating current sociocultural and human terrain data into the scenarios (e.g.,
from C-CORE), to keep them up-to-date. It will provide a way to annotate a variety of
entities in the virtual world in terms of their cultural significance, so that learners can
learn their meaning in the context of the culture. This may include clothing and other
examples of the material culture, locations (public, private, or sacred places), food
and other items associated with cultural practices, and even nonverbal gestures and
other human behaviors. These elements will be drawn from an ontology of cultural
entities developed in C-CORE, which in turn will relate back to the dimensions of
culture shown in Fig. 3.
C-GAME will also provide a way for trainers to define trainee cultural
performance standards. Trainers will be able to assess those performance standards
themselves by participating in or observing the training scenario, and they can rely on
automated cultural skills assessments built into the non-player characters.
The C-GAME run-time execution engine will incorporate instrumentation to
compare trainee performance to the training objectives and provide automated
performance review and remediation capabilities. This includes assessment of trainee
performance at each stage in the interpretation-decision-behavior cycle of the virtual
role players. In the interpretation phase, whenever learners say or do something that is
linguistically or culturally inappropriate, the role players will attempt to analyze and
classify the nature of the action. This analysis is similar to the analysis that takes
place in mini-dialogs, as described in section 5, but can apply to any immersive
scenario. Learners will get feedback on their cultural competence both from the
moment-to-moment reactions of the non-player characters and from the performance
review and the end of the scenario.
Acknowledgments.
The author wishes to express his thanks to the members of the
Alelo team who contributed to this work, and to LeeEllen Friedland for her help in
editing. This work was sponsored by USMC PMTRASYS, Voice of America, Office
of Naval Research, and DARPA. Opinions expressed here are those of the author and
not of the sponsors or the US Government.
