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This empirical investigation examines the repair strategies used by trainee interpreters in English-Persian simultaneous (SI) and consecutive interpreting (CI) modes. The research seeks to investigate two main questions: whether there are differences in the frequency of repairs between SI and CI, and whether there are variations in the sorts of repair strategies employed in both modes. The study involved nine trainees from Shahid Bahonar University of Kerman who were learning interpreting. The study employed a 4-minute speech from Voice of America English News, which discussed the influence of vitamins on preventing the advancement of AIDS in women. Occurrences of self-repairs were detected using Tang’s (2020c) framework. The findings revealed a notable disparity in the frequency of repair strategies between CI and SI modes, with CI trainees utilizing a greater number of repairs. In addition, the trainees in the CI mode achieved superior scores in explicitation and synonym techniques. The results emphasize the unique patterns of repair strategies in both consecutive and simultaneous interpretation, reflecting the importance of focused training to improve interpreters’ abilities in both modes. Interpreter training programs may consider including explicit instruction on repair procedures and placing emphasis on evaluating their use in performance assessments.

Teacher accountability, referring to teachers’ responsibility for instructional effectiveness and student outcomes, is a fundamental concept in education. However, barriers to teacher accountability in English as a Foreign Language (EFL) education in Iran have not been previously investigated. This study aimed to identify these barriers by developing and validating a context-specific instrument. A mixed-method approach was adopted, starting with semi-structured interviews with 60 EFL teachers to generate questionnaire items. Following the pilot study, a 27-item questionnaire was administered to 460 EFL teachers in private language institutes. Structural equation modeling (SEM) was run to develop an adjusted model of inhibitors to EFL teachers’ accountability and to assess the psychometric properties of the BTAS. Additionally, descriptive statistics explored teachers' perceptions of the identified barriers. The analysis supported a three-factor model of teacher accountability barriers: Internal obstacles, including motivational factors; external inhibitors, such as systemic constraints and assessment limitations; and environmental inhibitors related to cultural, sociocultural, and political constraints. The findings highlight the complex and interrelated motivational, institutional, and contextual challenges that hinder teacher accountability, and they present practical implications for policymakers and educational authorities to foster supportive environments that enhance teaching quality and learner achievement.

A critical component of cognitive diagnostic models (CDMs) is a Q-matrix that stipulates associations between items of a test and their required attributes. The present study aims to develop and empirically validate a Q-matrix for the listening comprehension section of the International English Language Testing System (IELTS). To this end, a listening comprehension test of the IELTS was administered to 820 Iranian test takers. According to theories, taxonomies, and models of second/foreign language (L2) listening comprehension, previous studies on the utility of CDMs to L2 listening comprehension, detailed content analysis of the test items, and consultation with several content experts, an initial Q-matrix was first developed. Through the technique suggested by de la Torre and Chiu (2016), along with checking heatmap plots and mesa plots using the GDINA package in R, the Q-matrix was then empirically validated. Generally, six attributes were extracted for the listening section, namely, (1) Linguistic knowledge (LKA), (2) understanding prosodic patterns (UPP), (3) ability to understand and make paraphrases (PAR), (4) ability to understand specific factual information such as names, numbers, and so forth (UFI), (5) ability to understand explicit information (UEI), and (6) ability to make inference (INF). Finally, the results of the fit of the GDINA model to the data, at both item and test levels, indicated the adequate model-data fit and the plausibility of the Q-matrix. The implications of the study were also discussed.

This study examines how linguistic style in One Flew Over the Cuckoo’s Nest by Ken Kesey and The Bell Jar by Sylvia Plath enacts psychological disturbance through formal textual mechanisms. Drawing on Foregrounding Theory, cognitive narratology, and clinical psycholinguistics, it investigates how stylistic deviations—such as metaphor saturation, syntactic fragmentation, referential ambiguity, and narrative disjunction—function as mimetic simulations of schizophrenia and depression. Through a mixed-methods approach that integrates close literary analysis with corpus-based annotation tools, the research analyzes selected passages for psycholinguistic markers associated with mental illness, including deictic confusion, lexical minimalism, and temporal distortion. Chief Bromden’s hallucinatory narration and Esther Greenwood’s affectively flattened voice are shown to linguistically instantiate psychosis and depressive cognition, respectively. The study contributes to interdisciplinary understandings of literature as a diagnostic interface, demonstrating that literary texts do not merely represent mental illness but cognitively perform it. Ultimately, this research offers a novel framework for analyzing narrative pathology, expanding the analytical reach of cognitive stylistics and underscoring literature’s potential to model and communicate disordered mental states.

In the domain of Persian literature, the Holy Qur’an has consistently played an influential subtextual role in shaping the formal and semantic aesthetics of literary works. The present study, aiming to analyze intertextual relations, investigates Saleh Hosseini’s utilization of Quranic terms and concepts in his translations of English literary works. To this end, based on Kristeva’s (1966) theory of intertextuality and Genette’s (1982) taxonomy, selected examples from seven translated works were analyzed. Following the examination and analysis of the data, a comprehensive interview with the translator was conducted to triangulate the findings. The results indicate that the translator employed two main strategies—explicit intertextuality (direct use of Quranic terms and verses) and paratextuality (using footnotes and appendices)—to create complex references in translations. This approach, while maintaining fidelity to the source semantic networks, reconstructed the text within the cultural context of the target language, providing a multilayered and polyvocal experience for the target readers. In light of the analysis of the collected textual data and the translator’s responses in the interview, it can be concluded that literary translation, far beyond the mere transfer of words, is a creative, interpretive, and intertextual process that facilitates deep cultural and discursive interaction among various texts.

Critical discourse analysis was developed by three outstanding linguists such as Fariclough, Van Dijk and Wodak, who offered rather similar approaches towards discourse analysis. Their common point is that CDA should take a critical orientation to discourse and investigate the aspects of ideology and power hidden in the discourse. The salient purpose of CDA which differs from other related approaches is that it tends to explore the implicit underlined ideological and power patterns in the written and spoken discourses. As a whole, CDA tends to uncover the implicit ideological prejudice in the discourse which brings about a dominance, hegemony, inequality and racism, and discrimination. These scholars basically give an ideological perspective to their approaches by the inspiration from Halliday's systematic functional linguistics. Halliday's systematic functional linguistics (SFL) is one of influential frameworks which has been extensively applied for the textual analysis of a number of domains such as critical discourse analysis. This study intends to discover how it is possible to find out the ideological dimension of discourse by exploring the linguistic elements particularly the transitive verbs. It is hoped that it provides insightful guidelines for the CDA researchers to analyze a discourse with its ideological perspective. It concludes that the transitive verbs are most significant in transferring the ideological attitude of writer or speaker. These types of verbs are deliberately used within a textual discourse in which each textual element is interrelated to each other and has an influential impact of the signification of these verbs.

The present study aimed to find the effect of artificial intelligence (AI)-mediated speaking assessment on speaking performance and willingness to communicate (WTC) of Iraqi EFL Learners. More specifically, the study sought to find whether AI-mediated speaking assessment enhance the speaking performance (grammar, vocabulary, pronunciation, intonation, and fluency) of Intermediate Iraqi EFL learners and whether AI-mediated speaking assessment enhanced their WTC in English. In so doing, 40 intermediate Iraqi EFL learners were randomly selected and assigned into experimental and control groups, each comprising 20 learners. The experimental group participants received ten 60-minute treatment sessions with ELSA Speech Analyzer, while the control group received no treatment. The speaking pre-test of both groups was run prior to the treatment, and all participants were post-tested at the end of the study. The Willingness to Communicate in a Foreign-Language Scale was also administered to groups prior to and after the treatment. A speaking assessment rubric, including vocabulary, grammar, intonation, pronunciation, and fluency, was used to assess the speaking performance of both groups. The findings demonstrated that AI-mediated speaking assessment enhanced the grammar, vocabulary, intonation, and fluency of the experimental group. However, the two groups did not differ in terms of pronunciation. Furthermore, this assessment tool enhanced the willingness to communicate with native speakers, the willingness to communicate with non-native speakers, and the willingness to communicate in the school context of this group. In general, the speaking assessment mediated by AI significantly enhanced the speaking performance and WTC of the learners. These findings might advance the current scholarly discourse on AI within the domains of language pedagogy and assessment.

Exploring L2 affective variables requires innovative research analytic approaches that can adequately address the complexity and dynamicity of the variables. Not always can the normality of distribution and linearity of relationships be assumed. Neither can the homogeneity of variance be always met. Latent profile analysis (LPA) is suggested to deal with the heterogeneity of data and non-linear relationships. It allows for hypothesis testing and model testing to tackle the ergodicity issue in second language acquisition (SLA) research from a person-centered approach. LPA, which primarily serves to classify a population or sample into several sub-groups, can be effectively employed in SLA research to classify L2 teachers or learners in terms of the different positive and negative emotions (e.g., enjoyment, boredom, anxiety, etc.) they experience while learning a foreign or second language. A classroom-based L2 learning experience occurs interactively with several personal and contextual variables involved. The relationship between any single affective variable can hardly be conceived as linear. Thus, LPA holds promises for dealing with these non-linear relations and provides insightful information about the profiles of learners or teachers concerning a particular affective variable. The purpose of this conceptual analysis is to provide a review of the basic tenets of LPA and to explain how it can contribute to the exploration of emotional variables in SLA. By identifying distinct emotional profiles, the study offers guidance on tailoring instructional strategies to address the specific emotional needs of language learners, thereby enhancing the effectiveness of language acquisition interventions.