Distributed Language Learning in 3D Virtual Environments

Proposal Abstract:

In language teaching, the hidden agenda of cultural values as they are dynamically co-constructed in situated conversations is usually replaced by teaching rules and conventions, in which sense values, meanings and communicative strategies are treated as static phenomena. This form-based learning and teaching implies the language bias (Linell, 2005) or the code view of language that there is language first, and communication second . The notion of languaging (Maturana, Linell, 2009; Thibault, 2011) integrates the local (here-now-it) communication as a first order phenomenon whereby agents coordinate interactions. In this notion, second-order language is referents of static meanings of lexicongrammer and sociocultural norms. In the Distributed Language approach (Cowley 2009), our languaging behavior spreads across diverse spatiotemporal scales ranging from neural to the cultural (Thibault, 2011).

This study stems data from a participatory design research in which intermediate Chinese language learners from the US and English language learners from Mainland China were invited to create quests/missions for China World, a virtual world of Quest Atlantis. The goals of the translanguaging interaction are to provide opportunities for participants to gain languaging experiences, and become attuned to cultural values and communication strategies, which eventually would benefit quest/mission creation. In this data set, we report languaging dynamics between Chinese and English learners. Preliminary analysis illustrates that both parties, in the beginning, had a strong propensity to realize values that orient to their own, and their communication strategies were limited to the utterance level, rather than on the project level. On the later time scale, participants demonstrated stronger orientation to the other, making use of second-order resources in the virtual world and other online spaces, which are good indicators of both parties becoming more and more coordinated. Multimodal analysis helps reveal the process of this coordination on the time scale of the four interactions.

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