Abstract

The research motivation derived from the acknowledgement of the need to raise intercultural awareness in language education in Taiwan. In recent years, language learning draws on the importance of developing intercultural competence in language learning. However, the notion of culture is often seen in the classroom only as a static concept presented in the content of the language textbook (Littlewood, 2000; Guest, 2002). It has been argued that learning culture from the text in the classroom is problematic since the culture values introduced in the text are often generalised from the national perspectives (i.e. Chinese highlights group membership whereas American values individualism).The purpose of this study is to investigate how people from different backgrounds negotiate meanings in interactions. In particular, this study looks at how Chinese and English speakers employ (im)politeness strategies in their emails to develop intercultural understanding. It considers such issues as the role of this particular mediating technology, the cultural background of participants and other contextualised factors.The research intends to ”look beyond the texts of interaction to the broader contextual dynamics that shape and are shaped by those texts” (Kern & Warschauer, 2000, p. 15). In light of the research aims, ethnography seems to provide opportunities for the researcher to gain more in-depth understanding of the process of how meanings are formed in interactions by the interactants. However, due to the nature of computer-mediated communication, this research modifies ethnography for the use of online investigations. In attempt to investigate the negotiation of meaning in email interaction discursively, ethnographically-informed discourse analysis is formed for the research purposes. This oral presentation discusses the philosophical stance of ethnography and how it impacts on this research design. Finally, an example is shown to illustrate how speech act theory, politeness theory and ethnography of communication are used to analyse email data.

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