مجید حیاتی

The present study on politeness is an attempt to examine (dis)agreeing strategies utilized by EFL learners while chatting on the internet. Subjects of the study were forty male and thirty-three female Iranian natives whose internet relay chat (IRC) interactions, composed of 400 excerpts, were collected between December 2007 and September 2008. Data analysis was based on the general taxonomy of politeness strategies suggested by Brown and Levinson (1987) which is the baseline of many politeness studies today. The results indicate that IRC is a mode of communication whose characteristics are typically different from face-to-face and real-life conversational settings. Some common face threatening acts (FTAs) like ‘direct disagreements’ are performed widely in chat channels. Furthermore, gender-oriented differences were found not to be statistically significant on the internet.

Language learners have frequently been classified according to individual difference variables such as aptitude, personality, cognitive style, and motivation. However, a language teacher’s view seems to have been missing from such classifications. This exploratory research investigated whether and by which criteria Iranian EFL teachers classify their students. Based on preliminary interviews with 29 high-expertise Iranian EFL teachers, 21 criteria were identified and included in a questionnaire that was completed by 175 Iranian EFL teachers. The respondents almost unanimously agreed that they did classify their students according to their understanding of the character type, behavior patterns, and achievement patterns of their students. Then they rated the 21 criteria on a scale from 0 to 4 according to how important each classification criterion was for them. Factor analysis of questionnaire responses revealed six major classification criteria. Subsequently, in a case study, 26 EFL students in a typical Iranian high school class were asked to rate their classmates according to the six major criteria. Only five of the criteria were found to predict English achievement and Grade Point Average (GPA). A cluster analysis of the students’ peer ratings using the five criteria generated three clusters. An ANOVA revealed that the three clusters were accurately differentiated not only on the clustering criteria but also on the two non-clustering variables: EFL Achievement and GPA.