Linguistic Features

Using a mixed methods design, the present study attempted to identify the factors influencing Iranian untrained EFL raters in rating group oral discussion tasks. To fulfil this aim, 16 language learners of varying proficiency levels were selected and randomly assigned to groups of four and performed a group discussion task. Thirty two untrained raters were also selected based on their volunteer participations. They listened to the audio files of the group discussions and assigned a score of one to six to each language learners based on their own judgments. They also provided comments on each language learners’ performance pointing to why they assigned such scores. The researchers had an interview with the raters after the rating session as well. The quantitative phase investigated whether linguistic features of accuracy, fluency, complexity and amount of talk were attended to by the raters in terms of having any relationship to the scores the raters assigned. Speech rate as an index of fluency and amount of talk turned out to be significantly correlated with the scores. Of more importance was the qualitative phase with the aim of identifying other factors that may account for the scores. The comments provided by the raters on each score and the interviews were codified based on Content Analysis (CA) approach. It was found that the raters attend not only to the linguistic features in rating oral group discussions, but they are also sensitive to the interactional features like the roles the participants take in groups tasks and the overall interaction patterns of the groups. The findings of this study may shed light on group oral assessment in terms of training the raters rating group oral tests and developing rating scales specific for group oral assessment.

The present study sought to examine the linguistic and discoursal features in the language of the text messages created by Iranian EFL learners. To this end, 400 text messages were collected from both genders. The contents of the collected data were analyzed in terms of linguistic features as well as discoursal features. The results highlighted the important role of gender in linguistic and discoursal features of text messages created by Iranian mobile phone users. More specifically, females’ use of complex sentences, formal opening and closing, and expression of thoughts, feelings, and emotions in their messages were much higher than men who created simple, short and to the point messages. The findings of this study highlight the role of text messages as a pedagogical tool since they are widely used to send or receive learning or information contents.

This study compared the Discussion section of theses written by M.A. English L1 and L2 students regarding lexical sophistication. Certain linguistic features were applied to investigate whether texts written in English L2 had any similarities or differences with native speakers’ (NSs) texts. To achieve this, 20 English L2 theses authored by Iranian M.A. students of Islamic Azad University of Isfahan (Khorasgan), were sampled. As such, 20 English L1 theses written by M.A. English NSs of the same major in the US and UK were randomly downloaded as a comparison corpus of English L1. The corpora were later uploaded to Coh-Matrix that processes text and discourse at different levels of language. Two main statistical procedures for data analysis were the MANOVA (Multivariate Analysis of Variance) and Discriminant Function Analysis. According to Coh-Metrix analysis, the results revealed certain similarities and differences between the corpora. Specifically, more CELEX content words were used in the NSs theses. However, the differences between the two corpora did not reach a statistical significance in terms of other indices of lexical sophistication (i.e., polysemy, concreteness, hypernymy, age-of-acquisition scores, and lexical diversity). Concerning these similarities and differences, academic writing pedagogy and theses writing abilities of Iranian English L2 learners can be improved by applying both word processing tools like Coh-Metrix, appropriate writing strategies and techniques according to the given results of current contrastive corpus study.