Getting culturally aware

Getting culturally aware

Problem being addressed

Training to improve cross-cultural interactions is difficult but simulations and games designed for this task have proven to be more effective than traditional classroom instruction. However​,​ most of these systems have used multiple-choice selection or menu-based interface​,​ which can be very restrictive and do not reflect the natural mode of human-to-human communication.

Solution

An intelligent tutoring system for cross-cultural training which incorporates dialogue-based interaction for cultural competency training. It trains multiple expert models to evaluate and score users’ responses in the simulation, integrates a speech recognition system as the input interface; implements an expert assessment model and an adaptive feedback mechanism that work together to provide feedback based on the trainee input; and finally conducts an experiment to evaluate the usability and performance of the system.

Advantages of this solution

The result showed that the suggested data-driven intelligent experts models gave comparable performance with what human would adjudge similar utterance. The feature abstraction technique and adaptive feedback mechanisms also allowed to solve the problem of manually scoring user’s spoken statements.

Solution originally applied in these industries

education

Education Sector

Possible New Application of the Work

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

Management Sector

Dialogue-based interactive simulation is a class of intelligent tutoring system that can be successfully used to gain negotiation skills and learn confrontation management; the suggested approach allows the learner to transfer the gained knowledge to a real world situation.

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Marketing

In the long run cross-cultural competence allows marketeers to fine-tune their campaigns when entering new markets and make them more interactive considering the local cultural specifics.

Author of original research described in this blitzcard: Sodiq Adewole, Erfaneh Gharavi, Benjamin Shpringer, Martin Bolger, Vaibhav Sharma, Sung Ming Yang, Donald E. Brown

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Name of the author who conducted the original research that this blitzcard is based on.

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