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This study aims to provide a comprehensive synthesis of the research landscape on Teacher Well-Being by integrating bibliometric and qualitative content analyses. Drawing on 1,256 peer-reviewed articles indexed in the Web of Science database between 1995 and 2025, the study first employs bibliometric techniques using R and VOSviewer to map trends, collaborations, and thematic tracks. Subsequently, a content analysis was conducted on a selected subset of 107 high-impact articles to categorize research purposes and contextual characteristics. Findings reveal strong thematic topics around resilience, burnout, job satisfaction, emotion regulation, positive psychology, equity, self-efficacy, reflective practice, and self-reflection. Both analyses highlight critical gaps in theoretical integration, methodological rigor, and international collaboration. While the United States, Australia, and the United Kingdom dominate in output and citations, emerging hubs such as China exhibit increasing engagement but limited global connectivity. The study underscores the need for longitudinal designs, culturally responsive research, and comparative international studies to advance the field. This research helps create a clearer, more inclusive and policy-relevant understanding of teacher well-being by emphasizing its systemic and relational aspects.

This study investigates the instructional strategies Vietnamese EFL lecturers prefer to employ to teach productive skills of general English in online and face-to-face teaching environments. Thirty-eight lecturers from 6 Vietnamese universities participated and responded to a questionnaire with 29 close-ended questions detailing instructional strategies. Four of the participants were invited to join the semi-interview about the reasons for their preference for instructional strategies. The collected data were analyzed with descriptive statistics for  Quantitative data and content analysis for qualitative data. The findings indicate that the most favored strategy in both teaching environments is describing pictures while opinion sharing and group discussion are much more favorable in the face-to-face than in the online teaching environment. Additionally, certain strategies are preferred in the face-to-face setting over instruction in the online setting and vice versa. Some primary reasons for lecturers’ preference for instructional strategies were identified and participants gave some recommendations of choosing appropriate strategies for teaching productive skills via interviews. These findings highlight EFL lecturers' preferences in selecting instructional strategies to teach English productive skills in the two teaching contexts and underscore implications for choosing proper instructional strategies.

Research on L2 learners’ engagement has highlighted the impact of emotional engagement on task performance to uphold their language development, but there remains a need for further empirical evidence, especially from the text-driven perspective on task-based language teaching. The present mixed-methods study aims to explore Vietnamese EFL learners’ emotional engagement during two task-based lessons driven by two text genres. One speaking task and a writing task that engaged the learners in solving problems driven by the texts were implemented in two three staged lessons. Quantitative data was collected by using a post-task questionnaire analyzed with SPSS v.29 to gauge 33 English undergraduates’ emotional engagement, and an interview was conducted with eight students on a voluntary basis to delve into factors that influence their emotional engagement. Observations during the lessons were further used to triangulate evidence. Descriptive statistics revealed that the participants were highly emotionally engaged in both task-based lessons, expressing high enjoyment and low anxiety. Further thematic analysis of engagement during the lessons indicated that pre-task visual prompting, text processing, the proper cognitive challenges of tasks and texts, and peer monitoring were the main influential factors. These findings imply that task design and implementation based on engaging texts potentially heighten learners’ emotional engagement in task-based performance, thereby facilitating their language acquisition.

This study employed a concurrent triangulation mixed-methods design to examine the impact of backward design (BD), central design (CD), and forward design (FD) on the speaking proficiency and engagement of 75 intermediate-level Iranian EFL learners, aged 18–21, selected through convenience sampling at Arak University, Iran. Participants attended nine weekly 105-minute sessions over one semester, with intermediate proficiency verified by the Oxford Quick Placement Test. Pre-tests established baseline speaking abilities, and participants were divided into three groups of 25: BD group (BDG), CD group (CDG), and FD group (FDG). Data were gathered using IELTS speaking pre- and post-tests, a student engagement scale (SES), and semi-structured interviews. The BDG focused on defining learning outcomes and using assessments such as observations and recorded speeches to track progress and adjust instruction. The FDG prioritized structured activities targeting specific speaking skills, using formative and summative assessments to evaluate mastery. The CDG adopted a learner-centric approach, incorporating personas, scenarios, and open educational resources to create collaborative, engaging activities emphasizing social context and emotional growth. Post-intervention results revealed CD as the most effective in enhancing speaking proficiency and engagement, followed by BD, with FD being the least effective. These findings underscore CD’s strength in fostering interactive, meaningful learning experiences for Iranian EFL learners. The study suggests that curriculum developers and educators should prioritize learner-centered approaches, such as CD, to improve EFL speaking outcomes and engagement.

This research looked at how using AI in education affects long-lasting learning results and maintaining English language abilities and vocabulary for Iranian intermediate EFL learners. The study used a quasi-experimental design. 60 students from a school in Tehran were split into two groups. The experimental group used AI tools like adaptive platforms, personalized feedback, and simulations. The control group learned with traditional teaching methods. Both groups took pre-tests, went through 12 weekly learning modules over four months, completed post-tests and then had a retention test six months later to see how well they understood English grammar, picked up new vocabulary, and developed language skills. The results showed that the AI group had a much higher average score and better consistency in keeping the language learned. The regression analysis also showed that using AI was a strong reason for improvement in performance. Feedback from focus groups revealed that students were more involved because of the personalized learning and instant feedback. About 78% of the participants in the AI group said they felt more motivated. These findings suggest that AI-assisted education is effective for achieving long-term academic success, especially through tailored content and interactive problem-solving tasks that help retain English skills over time. The study recommends that schools embrace AI in their curricula to increase the long-lasting retention of language skills and critical thinking in intermediate pupils.

Pragmatic competence, being a crucial aspect of communicative competence, is among the key competencies necessary for successful communication. The present study was an attempt to investigate the effect of EFL learners’ grammatical competence (knowledge of linguistic features such as grammar and vocabulary) and proficiency level on their pragmatic competence. The participants were 165 Iranian intermediate and upper intermediate EFL learners. They were freshman and junior students (considered as intermediate and upper intermediate learners) in eight intact classes (four freshman and four junior classes) at some universities in Qom, Iran. Initially, the participants took a general proficiency test (TOEFL Test, 2002) to homogenize the participants at each proficiency level and indicate that the junior students were truly more linguistically proficient than freshman students. Subsequently, they were given a discourse completion test, involving 12 multiple-choice questions assessing learners’ recognition of appropriate speech acts and pragmatic markers. The results were analyzed using some SPSS statistical techniques, which revealed that there was a moderately significant correlation between grammatical and pragmatic competences, and language proficiency has a significant effect on the pragmatic competence of the learners, as the junior students outperformed the freshman students.

his study conducts a bibliometric analysis of Artificial Intelligence (AI) in English education, employing co-citation and co-occurrence analyses to investigate significant research trends, theoretical frameworks, and interdisciplinary connections. The analysis delineates four primary research clusters: AI-assisted language acquisition, ChatGPT in educational methodologies, AI chatbots for English as a Foreign Language (EFL) students, and AI-facilitated student engagement. The co-citation analysis identifies pivotal studies that influence the intellectual framework of the field, whereas the co-occurrence analysis underscores thematic trends and research deficiencies. This study enhances the Technology Acceptance Model (TAM) by integrating pedagogical and ethical aspects, illustrating the interaction between perceived ease of use, usefulness, policy frameworks, teacher readiness, and AI implementation in education. Notwithstanding AI’s transformative potential, challenges persist, encompassing data privacy issues, algorithmic bias, ethical dilemmas, and the necessity for interdisciplinary collaboration. To connect AI with sustainable and equitable education, future research has to investigate the long-term adoption of AI, geographic disparities, and strategies for effective pedagogical integration. This study presents a framework for the ethical, effective, and interdisciplinary integration of AI in English education by promoting collaboration among educators, AI researchers, and policymakers.

This comparative study deals with the archetypal journey of self-realization as represented in Paulo Coelho's The Alchemist and Elif Shafak's The Forty Rules of Love. Both novels feature protagonists who starts a spiritual journey to realize their true selves and fulfill their fates. The study also discovers how the writers use different literary techniques to transmit the archetypal journey of self-realization. For example, Coelho deploys the theme of the personal legend which stands for a person's unique ideal which serves as a guiding force for Santiago throughout his journey. On the other hand, Shafak benefits from the Sufi concept of the dervish, which represents a person going after spiritual enlightenment through separation from material possessions. Indeed, it focuses on the protagonists' self-realization journeys to discover the archetypal motifs, symbols, and narrative structures. These selected novels share thematic points embedded in mysticism, spirituality, and personal growth. From these perspectives, the purpose of this article is to provide a general understanding of how these contemporary works contribute to the wider discourse on self-discovery within the context of the protagonists’ archetypal journey.

Pragmatic testing depends on a variety of factors that can impact its dependability. This study intended to examine these factors using a two-phase approach. The first phase examined the impact of test methods, items, raters, and test-takers' characteristics on the variance in pragmatic test scores using generalizability theory, and the second phase explored potential rater bias using the Many-Facet Rasch model. Two test types, including a Written Discourse Completion Test (WDCT) and a Discourse Self-Assessment Test (DSAT), were administered to 110 English language students (98 female, 12 male) aged 17-24 at Vali-e-Asr University of Rafsanjan. Four raters scored the WDCT by using a standardized rubric developed by Lui (2004). The DSAT was self-assessed by test takers based on the same rubric. The findings revealed no significant difference between the WDCT and DSAT test types. However, items and the interaction between items and test takers emerged as substantial contributors to the variance of the scores. This highlights the importance of item calibration and rater training to mitigate bias in pragmatic testing. Finally, the implications were discussed.

Among increasing interest in emotional and relational dimensions of language teaching, this conceptual review highlights the essential effect of interpersonal justice in promoting learner well-being and engagement in English as a Foreign Language (EFL) settings. Based on Self-Determination Theory (SDT), asserting that learning is most effective when individuals' basic psychological needs for competence, autonomy, and relatedness are fulfilled, this review investigates the effect of interpersonal justice can address these needs and it also synthesizes extended empirical results to investigate the effect of respectful, empathetic, and dignified class interactions on cultivating engagement, and well-being in EFL students. Recontextualization of the previous research in this review illustrates that previously examined justice-related elements had contributed to enhancing learner engagement and well-being. Justice educational activities, including unbiased feedback, active listening, and dignity-preserving communication, reduce anxiety, foster trust, and maintain learner persistence, thereby promoting engagement and well-being. The review ends with practical implications for teachers and policymakers and outlines future research directions focused on extending comprehension of interpersonal justice as an affective and motivational structure in EFL settings.