درخت حوزه‌های تخصصی

This study examines the accessibility of translated navigational signs in Tehran Metro as a key site of public translation. Using field observations supported by the User-Centered Translation (UCT) framework, it assesses the clarity, consistency, and usability of bilingual signage and other multimedia  features across multiple metro stations and lines. The analysis identifies recurring inconsistencies in transliteration, translation choices, and the alignment between station names at stations and on the official metro map. These variations demonstrate the lack of a standardized approach to multilingual communication within the network and highlight the impact of such discrepancies on user navigation. The study contributes empirical data to ongoing discussions of translation in public spaces by showing how multilingual signage practices can either facilitate or hinder effective wayfinding in transit environments.

Although pair work interaction gained substantial attention in recent decades, little is known about the best method to enhance its effectiveness. This study investigated the impact of peer modelling demonstration of collaborative writing tasks as a pedagogical intervention on Language-Related Episodes (LREs) and pair dynamics. Using a one-group pretest-posttest design with a delayed posttest, twenty intermediate learners were randomly paired up to complete three tasks (information-gap, story reconstruction, and jigsaw), which also involved a paragraph-level writing over a three-week period. Each session, the participants were required to work on one task while recording their voices. In the second session of the study, the pairs were provided with the peer modelling video to explore its contribution to their performances. The pairs' audio-recorded performances (about 15 hours) were carefully transcribed and later analyzed for a) the frequency, types, and resolution of LREs and b) pair dynamics. Results of Negative Binomial Regression revealed that peer modelling had a significant positive effect on pair performance, in a way that, after the provision of peer modelling, the pairs produced a significantly greater number of LREs and correctly resolved the majority of the conflicts. Additionally, analysis of McNemar's test revealed that the pairs demonstrated more collaborative pair dynamics subsequent to peer modelling. The findings are pedagogically important as they support peer modelling as a valuable pedagogical technique to be integrated into language learning classes to ensure L2 development and foster qualities of pair work.

Political apologies serve as high-stakes communicative acts, addressing collective wrongdoing while seeking to repair damaged relationships between governments and affected groups. This study explored the evolution of political apologies in the 21st century, analyzing their role as public speech acts that respond to shifting societal and political norms. Despite their increasing prevalence in global politics, limited research has examined how these apologies have adapted linguistically and structurally over time to meet evolving public expectations. This research bridged this gap by employing a diachronic pragmatic approach. A corpus of 222 state-level political apologies, spanning two decades, was analyzed using the Cross-Cultural Speech Act Realization Project (CCSARP) framework, augmented with emerging pragmatic elements. Categorized into five sociopolitical periods, these apologies were coded and analyzed with Atlas.ti to identify shifts in their structural and linguistic components. The findings revealed a consistent use of Illocutionary Force Indicating Devices (IFIDs), alongside a growing emphasis on Explanation or Account and META (Reaffirmation). Novel elements, such as Commemorative Apologies and Forward-Looking Statements, demonstrated how political apologies are increasingly tailored to address systemic injustices and public demands for accountability and reconciliation. Theoretically, the study could enrich pragmatic frameworks by identifying new components of political apologies. Practically, it offers insights for crafting effective apologies that resonate with diverse audiences. This research underscored the adaptability of political apologies, positioning them as tools for fostering societal healing and advancing justice in a rapidly changing world.

Recent years have witnessed extensive research on motivation in second/foreign language (L2) contexts. Attempts have been made to develop motivation-based techniques and methods to boost learners’ learning outcomes in L2 programs. Yet, studies that have targeted L2 learners’ perceptions about the effectiveness of such programs in online classes remain scarce. This study addressed this gap and delved into L2 learners’ perceptions of two motivation-oriented instructions, namely the ARCS-based (Attention, Relevance, Confidence, and Satisfaction) and L2MSS vision-inspired (Second Language Motivational Self System) instructions, in an online English course. To this end, 41 learners of English were assigned to two groups. One group was instructed based on the ARCS motivation framework, and the other was instructed based on the L2MSS framework. Then, 10 volunteer participants from each group participated in focus group interviews. Thematic analysis of the data revealed 19 subthemes and 7 main themes, including 4 themes of attention-related pedagogy, relevance-oriented content, confidence-building elements, and sense of contentment/discontentment regarding the ARCS group, and 3 themes of ideal self-orientations, ought-to self-orientations, and situated learning/teaching experiences regarding the L2MSS group. The engaging content and appealing learning environment in the ARCS group and the future perspective enhancement and goal setting in the L2MSS group were motivating factors, creating positive perceptions of the two programs. The findings suggest utilizing attention-catching and vision-building strategies to motivate learners and enhance their L2 learning outcomes in online classes.

The evaluation of students' writings and the allocation of scores are traditionally time-intensive and inherently subjective, often resulting in inconsistencies among human raters. Automated essay scoring systems were introduced to address these issues; however, their development has historically been resource-intensive, restricting their application to standardized tests such as TOEFL and IELTS. Consequently, these systems were not readily accessible to educators and learners. Recent advancements in Artificial Intelligence (AI) have expanded the potential of automated scoring systems, enabling them to analyze written texts and assign scores with increased efficiency and versatility. This study aimed to compare the efficacy of an AI-based scoring system, DeepAI, with human evaluators. A quantitative approach, grounded in Corder's (1974) Error Analysis framework, was used to analyze approximately 200 essays written by Persian-speaking EFL learners. Paired sample t-tests and Pearson correlation coefficients were employed to assess the congruence between errors identified and scores assigned by the two methods. The findings revealed a moderate correlation between human and AI scores, with AI diagnosing a greater number of errors than human raters. These results underscore the potential of AI in augmenting writing assessment practices while highlighting its pedagogical implications for language instructors and learners, particularly in evaluating the essays of EFL students.

The present study attempted to comparatively investigate English as a Foreign Language (EFL) teachers’ and English for Specific Purposes (ESP) teachers’ beliefs about language learning and teaching and their distinctive characteristics. To this end, 150 EFL and ESP teachers, selected randomly from various universities in Iran, were asked to fill out two pilot-tested validated five-point Likert-scale questionnaires, one on beliefs (including 45 items) and the other on characteristics (comprising 16 items). To do multiple-level analysis and triangulate the data for validation purposes, 25 teachers, selected randomly from among the study participants, were also interviewed. The results of (Quantitative data analysis such as Independent Samples t-tests, Chi-Square and Pearson product-moment correlation analyses, as well as qualitative content analysis of interviews) found no significant mismatch between ESP teachers and EFL teachers’ beliefs overall; however, significant differences were found between characteristics of ESP teachers and EFL teachers overall as well as between the specific beliefs and also between specific characteristics of the two groups of the teachers. The results are discussed in detail in the paper, and the implications, which are significant for the field of language education and ESP, and the pertinent implications are presented.

The ecological turn in translation studies subverts anthropocentric perspectives and redefines translation as a multispecies, semiotic process that transcends human language. Eco-translation, a central concept within this turn, extends the field of translation to include non-human actors and ecological networks, allowing for a more inclusive description of meaning-making. Yet this turn has also brought academics a sense of disorientation and solastalgia as scholars have to grapple with the tension between preserving traditional disciplinary boundaries and embracing the expansive horizons of transdisciplinary approaches. The current article traces the ecological turn using Doris Bachmann-Medick’s three-stage model of disciplinary turn: thematic expansion, metaphorical application, and methodological refinement. It maps the evolution of eco-translation from narrowly defined practices focused on ecological themes to a broader, inclusive framework that challenges the field’s traditional foundations. The article also examines the emotional and intellectual consequences of this turn, particularly the solastalgic experience of scholars experiencing the loss of familiar disciplinary contours while adapting to new paradigms.

Objective: Despite the renewed interest in individual differences in second language acquisition (SLA), there is still limited research on the interconnections among regulatory focus (promotion and prevention), L2 grit (Consisting of perseverance of effort and consistency of interests), and emotions. Methods: A total of 85 undergraduate English majors (54 women, mean age = 20 years) from two comprehensive universities in Iran took part in the research. In order to assess the participants' promotion and prevention focuses, L2 grit, and English writing enjoyment, three questionnaires were used. The data collected was analyzed using IBM SPSS (26.0) software. Results: The correlational analysis revealed that regulatory focus, L2 grit, and L2 writing enjoyment are interconnected. Specifically, promotion focus positively correlated with L2 writing enjoyment and L2 grit. Additionally, L2 grit (Perseverance of Effort) showed a meaningful connection with L2 writing enjoyment. On the other hand, prevention focus demonstrated significant negative correlations with L2 writing enjoyment and L2 grit. Lastly, there was no significant relationship found between L2 Grit (consistency of interest) and L2 Writing Enjoyment. Conclusions: The study's results demonstrate the crucial findings regarding the interplay between different dimensions of grit, emotion and personal best goals.

This study investigated the impact of Google Meet instruction on learner autonomy in EFL learners, considering the potential moderating role of learner motivation. A quasi-experimental design with two groups involving 40 intermediate EFL learners was employed. Learner proficiency was assessed using the Oxford Placement Test (OPT). Learner motivation and autonomy were measured by the English Learning Motivation Questionnaire (ELMQ) and the Learner Autonomy Questionnaire (LAQ) before and after the intervention period. The results revealed a statistically significant increase in learner autonomy scores in the experimental group who received instruction through Google Meet, while the control group receiving traditional face-to-face instruction did not experience a significant change. Further analysis explored the interaction effect between learner motivation and Google Meet use. A two-way ANOVA revealed that learners with high motivation scored higher in both groups compared to those with low motivation. However, the experimental group consistently scored higher than the control group regardless of motivation level. Notably, learners with high motivation in the Google Meet group achieved the highest scores, while learners with low motivation in the control group scored the lowest. The results also confirmed that both learner motivation and Google Meet instruction, along with their interaction, significantly affect learner autonomy development. These findings contribute to the understanding of technology-assisted language learning environments and their potential to foster learner autonomy, while highlighting the important role of learner motivation in this process.

Artificial Intelligence (AI) is affecting various aspects of education and there is a need to consider the consequences of this technological improvement on achievement and attitudes of the most direct stakeholders. Therefore, this study has focused on the effect of AI on teaching English with three key areas of concern: the effect of Chat-GPT-driven materials on learning outcomes, the attitudes of teachers who use Chat-GPT -informed pedagogy, and the students’ attitudes towards Chat-GPT-integrated materials. This study used a quasi-experimental intervention-based research design to achieve the intended objectives. Based on the type of educational institution, the participants were divided into three groups (90 students from Iranian language institutes, 100 students from public high schools, and 100 students from private high schools). Furthermore, fourteen teachers from these institutions shared their viewpoints on the use of AI, particularly Chat-GPT, in developing instructional materials. Pre- and post-tests were administered to check the effect of treatments on each group (based on the syllabus developed for those specific educational institutions). Moreover, two researcher-developed questionnaires were administered among teachers (composed of 27 Likert-Scale items) and students (composed of 23 Likert-Scale items). The obtained results indicated that Chat-GPT significantly improved EFL learners' performance in language institutions. Teachers looked upon AI with favor. This was based on its potential to change the produced educational materials and improve students’ engagement in the learning process. Students, in all three environments, looked positively toward Chat-GPT-driven materials. In short, this study showed the potential for AI to upgrade EFL teaching in Iran.

This study aims to investigate the digital literacy of Iraqi Kurdish English as a Foreign Language (EFL) teachers. The study employed a quantitative approach with a sample of 418 participants, consisting of 228 females and 190 males, who teach English at Middle school, High school, and University levels. A targeted sampling was used to select the participants. A questionnaire designed by the Cambridge Assessment Center was used to explore the participants’ digital literacy. It was designed based on the Cambridge English Digital Framework for Language Teachers. The gathered data were analyzed using an independent sample t-test to compare the digital literacy of male and female Iraqi Kurdish teachers, and a one-way ANOVA test to explore any significant differences caused by different academic levels of the participants. The results showed statistically significant differences between male and female teachers in all six categories, except the evaluating learning category which deals with assessing digital resources and tools for language teachers. The results of the ANOVA test showed that there was not any significant difference between the digital literacy of middle school and high school teachers. However, it was found that the university lecturers were significantly more competent users of digital literacy skills than the middle school and high school teachers. The results also revealed that in general the Iraqi Kurdish EFL teachers demonstrated an average level of digital literacy and thus suggested more educational and technological support for the teachers at various levels across the region.