مطالب

The increasing availability of scientific knowledge through digital platforms has transformed how scientific discourse reaches the general public. This study examined the use of interactional metadiscourse markers across four leading popular science subgenres: books, TV documentaries, magazine articles, and newspaper articles. The aim was to investigate the language features of these markers, focusing on how they engage readers and highlight writer presence in different subgenres. A corpus of 987,625 words was analyzed using AntConc software (Anthony, 2019) and 80,260 instances of interactional markers were identified according to Hyland’s (2019) Interpersonal Model of Metadiscourse. The study revealed how hedges, boosters, attitude markers, self-mentions, and engagement markers function to create persuasive and accessible content. Interestingly, interactional markers appeared most frequently in TV documentaries, suggesting a heightened effort to engage audiences through this medium. Chi-square tests revealed significant differences in marker usage across subgenres; however, the small effect sizes (Cramér’s V) indicated that these differences are of only modest practical significance. These results provided insight into how popular science writers adapt their rhetorical strategies to suit different communicative contexts and audience expectations. The findings also have pedagogical implications. Incorporating features of popular science into ESP/EAP materials, such as authentic texts and structured practice with interactional metadiscourse markers, can make scientific content more engaging and accessible for learners. Raising learners’ awareness of interactional metadiscourse markers can improve writing skills, especially for novice writers in non-English academic settings, helping them better engage readers and communicate more effectively.

Grammatical accuracy has always been a concern for most Iranian EFL learners. This grammatical variability is more visible in the writing of Iranian IELTS candidates. In this study, the impacts of (distributed, peer and reciprocal scaffolding on IELTS learners' horizontal grammatical variability were investigated. An explanatory mixed design was employed to measure the differences among scaffolding types and to develop a better understanding of teachers' and learners' perception toward them. 120 IELTS candidates were randomly selected from a pool of 367 candidates, and they were put in three experimental groups and a control group. Each scaffolding type was used in one of the experimental groups as the treatment. Five different essay topics were given to each student before the course and after the course. Two official IELTS mock examiners rated the writing performances according to the details of IELTS criteria about grammar accuracy and variability. Next, using an ANCOVA procedure, the data were analyzed. Moreover, the data collected in the qualitative phase were content analyzed. The findings showed that in distributed and reciprocal scaffolding classes, the differences were significant. The qualitative findings showed that although there was a discrepancy between the teachers' and the learners' attitude toward the possible success of the treatments, at the end, both parties confirmed that they can be beneficial. Due to the fact that 'time' has always been a precious parameter in IELTS preparatory classes, these findings can be of help to IELTS teachers and candidates.

The goal of this inquiry was to scrutinize how Iranian university students’ motivation, creativity, emotional intelligence (EI), and intellectual awareness (IA) were affected by artificial intelligence (AI). Sixty Iranian university students in Ahvaz, Iran, were chosen based on a convenience sampling method to reach this objective, and they were separated into two groups: the experimental group (EG) and the control group (CG). Both groups were administered four relevant questionnaires to gauge their proficiency in each dependent variable. Next, utilizing AI-ChatGPT, some modified materials (ten reading texts) were trained to the EG. The CG received traditional instruction using the same materials. Four questionnaires were given to each group as research posttests following the ten-week course of treatment. The results of ANCOVA and independent samples t-tests revealed meaningful differences; the EG did better than the CG on all dependent variables. Based on the gained results, the EG outperformed the CG on the posttests of motivation, creativity, EI, and IA. The research’s implications can encourage EFL teachers and learners to acquaint themselves with different AI applications and apply them in their teaching and learning.