Abstract

Despite large literature on Cross-Cultural Competence (3C) there is a gap in understanding learning processes and mechanisms by which people arrive at successful 3C. We present a novel perspective for 3C learning and decision-making in innovative assessment contexts. We use Mindset theory (i.e., believing ability is fixed or changeable) because it is shown to be a powerful motivator for general learning and performance and in cross-cultural contexts. We propose the notion of cultural mindsets – beliefs, affect, and cognition that govern how people adapt, learn, and update cultural information. To understand how cultural mindset affects learning and performance, we apply computational cognitive modeling using Markov decision process (MDP). Using logfile data from an interactive 3C task, we operationalize behavioral differences in actions and decision making based on Mindset theory, developing cognitive models of fixed and malleable cultural mindsets based on mechanisms of initial beliefs, goals, and belief updating. To explore the validity of our theory, we develop computational MDP models, generate simulated data, and examine whether performance patterns fit our expectations. We expected the malleable cultural mindset would be better at learning the cultural norms in the assessment, more persistent in cultural interactions, quit less before accomplishing the task goal, and would be more likely to modify behavior after negative feedback. We find evidence of distinct patterns of cultural learning, decision-making, and performance with more malleable cultural mindsets showing significantly greater cultural learning, persistence, and responsiveness to feedback, and more openness to exploring current cultural norms and behavior. Moreover, our model was supported in that we were able to accurately classify 83% of the simulated records from the generating model. We argue that cultural mindsets are important mechanisms involved in effectively navigating cross-cultural situations and should be considered in a variety of areas of future research including education, business, health, and military institutions.

Highlights

  • Working and interacting effectively with individuals from different cultural backgrounds has become increasingly important in many workforce and educational settings

  • We model the fixed-mindset players as not expecting to learn from their non-player characters (NPCs) interactions unless they are completely uncertain of the correct formality

  • We used the simulation results to: provide validity evidence based on testing behavioral criteria, investigate the Markov decision process (MDP) model classification for fixed and malleable players as well as exploring differences in fixed and malleable interactions with different non-player characters (NPCs)

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Summary

Introduction

Working and interacting effectively with individuals from different cultural backgrounds has become increasingly important in many workforce and educational settings. Culturally homogenous groups have been shown to be more productive than culturally heterogenous ones (DiStefano and Maznevski, 2000) These productivity gaps arise from barriers to shared understanding and failures to competently tap into the range of valuable skills that diverse groups offer (DiStefano, 2003). More diverse teams are shown to outperform less diverse ones only after acknowledging and working around differences and establishing team norms (DiStefano, 2003). Taken together, these findings highlight the importance of better understanding the processes and mechanisms of cross-cultural interactions that enable successful performance in a variety of fields

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