Teaching English Language and Literature Society of Iran (TELLSI)Journal of new advances in English Language Teaching and Applied Linguistics2676-29277220250901Understanding the Links between Emotional Intelligence, Empathy, and Authentic Personality in English Language Teachers: Employing Structural Equation Modeling12523234010.22034/jeltal.2025.7.2.1ENAhmedAbdulhadi MousaDepartment of Foreign Languages Teaching, Ma.C. Islamic Azad University, Mashhad, IranZahraZohoorianUniversity of NizwaDepartment of Foreign Languages Teaching, Ma.C. Islamic Azad University, Mashhad, IranMinaTahani1Department of Foreign Languages Teaching, Ma.C. Islamic Azad University, Mashhad, IranJournal Article20250621<span style="font-size: 12.0pt; line-height: 107%; font-family: 'Times New Roman',serif; mso-fareast-font-family: Calibri; color: black; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Emotions and personality traits are central factors within educational settings, significantly affecting the interactions’ quality and the establishment of effective relationships between teachers and students. Among the several emotional factors, emotional intelligence and empathy are particularly prominent. Moreover, teachers’ personality role in the instructional process has gained considerable attention, with authenticity as a key personality dimension that is connected to optimal performance. This study was an attempt to develop a model exploring the relationships among emotional intelligence, empathy, and authentic personality. Employing a cross-sectional correlational design, the study data were collected from 198 participants. Structural equation modeling analysis indicated that both emotional intelligence and empathy serve as positive and significant predictors of authentic personality. Furthermore, a moderate correlation was observed between teacher empathy and emotional intelligence. Accordingly, the initial proposed conceptual model of the study was supported by the empirical findings.</span>https://www.jeltal.ir/article_232340_c344ed23fcb16c3f1a2f05bc43b3623a.pdfTeaching English Language and Literature Society of Iran (TELLSI)Journal of new advances in English Language Teaching and Applied Linguistics2676-29277220250901The Impact of Emerging AI Platforms on English Language Teaching and Learning: A Review of 2022–2025 Literature264323234210.22034/jeltal.2025.7.2.2ENAlirezaBonyadiEnglish Department, Faculty of Humanities, Ur.C., Islamic Azad University, Urmia, Iran0000-0002-8355-4820Seyyed HosseinKashefEnglish Language Department, Ur.C, Islamic Azad University, Urmia, Iran0000-0002-0843-8563MinaTasouji AzariDepartment of English Language Teaching, Ministry of Education, Urmia, IranJournal Article20250620The rapid evolution of artificial intelligence (AI) platforms between 2022 and 2025 has significantly reshaped English language teaching and learning (ELT), as explored in this literature review. Focusing on platforms like ChatGPT, Claude, Gemini, Grok, and DeepSeek, this study synthesizes research from 2022–2025 to examine AI’s impact on pedagogy, learner outcomes, and classroom dynamics. Drawing from SciSpace and Elicit databases, the review identifies six key themes: personalization of learning, learner engagement through interactive tools, support for educators, inclusivity and accessibility, challenges of AI integration, and pedagogical implications. AI enhances ELT by delivering tailored exercises, automating assessments, and fostering engagement through chatbots, gamification, and speech recognition, while supporting teachers with curriculum design and progress monitoring. It also broadens access for diverse learners, including those with disabilities and multilingual backgrounds. However, challenges such as the digital divide, privacy risks, and AI’s limited grasp of cultural nuances highlight the need for balanced implementation. The findings suggest AI aligns with constructivist learning theories, shifting ELT toward learner-centered, experiential approaches, yet over-reliance risks diminishing human interaction, prompting calls for hybrid models. Limitations in current research include a focus on short-term outcomes, insufficient exploration of teacher readiness, and unresolved ethical concerns like equity and bias. Future research should prioritize longitudinal studies, teacher training, cultural responsiveness, and ethical frameworks to ensure AI’s sustainable integration. This review underscores AI’s transformative potential in ELT, advocating for a synergy of technological innovation and human instruction to maximize benefits while addressing emerging challenges.https://www.jeltal.ir/article_232342_22378dbb839efc046b9ce7163f58204e.pdfTeaching English Language and Literature Society of Iran (TELLSI)Journal of new advances in English Language Teaching and Applied Linguistics2676-29277220250901The Effect of Guessing Strategies on Intermediate EFL Learners’ Phrasal Verbs Learning446723282210.22034/jeltal.2025.7.2.3ENLeilaSohrabifarDepartment of Foreign Languages Teaching, Ahv.C., Islamic Azad University, Ahvaz, IranMohammad TaghiFarvardinDepartment of Foreign Languages Teaching, Ahv.C., Islamic Azad University, Ahvaz, Iran0000-0003-4998-8681Journal Article20250622This mixed-methods study examined the impact of guessing strategies on the learning of phrasal verbs by intermediate EFL learners and assessed their attitudes regarding the utilization of these strategies. To this end, 40 Iranian students were put into either a control group or an experimental group. The experimental group received lessons on how to guess based on context, while the control group learned vocabulary in a more traditional way. We used paired and independent samples t-tests to compare the scores from the pretest and the posttest. Results showed that both groups did better, but the experimental group did better on the posttest. This shows that guessing strategies helped people acquire phrasal verbs. During the qualitative phase, semi-structured interviews were performed with 5 participants to provide insights into their experiences. Learners generally thought that guessing strategies were helpful at making them more aware of the context. However, some learners were worried about how unclear they were and how hard it was to figure out idiomatic interpretations. The results show that guessing strategies cannot work for everyone or for every phrasal verb, but they can be useful when used with feedback, repetition, and training for the learner. These findings imply the necessity of embedding contextual guessing within scaffolded, feedback-rich vocabulary instruction with systematic repetition.https://www.jeltal.ir/article_232822_05feab53d086f45883ca8b61f93bb090.pdfTeaching English Language and Literature Society of Iran (TELLSI)Journal of new advances in English Language Teaching and Applied Linguistics2676-29277220250901Identifying Threshold Vocabulary for IELTS Writing Skill688823937910.22034/jeltal.2025.7.2.4ENAtikaEtemadzadehDepartment of Foreign Languages Teaching, ToH. C., Islamic Azad University, Torbat Heydarieh, Iran.0000-0002-6075-6294HamidAshrafDepartment of Foreign Languages Teaching, ToH. C., Islamic Azad University, Torbat Heydarieh, Iran.Journal Article20250622<span style="mso-bidi-font-size: 12.0pt; line-height: 150%; mso-ascii-font-family: 'Times New Roman'; mso-ascii-theme-font: major-bidi; mso-hansi-font-family: 'Times New Roman'; mso-hansi-theme-font: major-bidi; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: major-bidi;">This paper reports on empirical research that endeavors to investigate the threshold vocabulary knowledge for writing section of IELTS. In other words, how many vocabulary is required for a L2 learner to get 7 in IELTS writing section? The scarcity of studies on investigating the relationship between productive vocabulary size and writing skills prompted us to do this study on 131 postgraduate international students studying in Universiti Teknologi Malaysia (UTM) who obtained the minimum score (i.e., 6) in IELTS as a requirement for enrollment. PVLT was given to participants. Then, participants’ scores from the test were correlated with their score in the writing section of IELTS. The results revealed significant correlation coefficients between productive vocabulary size and academic writing skills. Moreover, the findings of Multiple Regression indicated that productive vocabulary levels test (PVLT) could be a good predictor for IELTS academic writing. Finally, by use of the participants’ mean score in different levels of PVLT and the Zimmerman formula for calculating the number of vocabulary at each level revealed a threshold of 2000 words for a L2 learner to get 7 in IELTS writing section. The findings drawn from the study have some pedagogical implications useful for curriculum planning, decision making, and classroom implementation.</span>https://www.jeltal.ir/article_239379_75d02cae87d52cacf9cfc8c736d1ddf6.pdfTeaching English Language and Literature Society of Iran (TELLSI)Journal of new advances in English Language Teaching and Applied Linguistics2676-29277220250901Evaluating the Predictive Power of Fine-Grained Syntactic Complexity Measures for IELTS Writing Scores8911223938010.22034/jeltal.2025.7.2.5ENEhsanAbbaspourCentre for Academic Writing, Middle East College, Muscat, Oman0000-0002-8501-3200PriyaMathewCentre for Academic Writing, Middle East College, Muscat, Oman0000-0001-9993-3246Journal Article20250522The present study investigates fine-grained syntactic complexity measures and their potential role in predicting the quality of L2 writing in IELTS Writing Task 2. A corpus of 105 IELTS essays, covering a wide range of band scores for Grammatical Range and Accuracy (GRA), was systematically analyzed using the Tool for the Automatic Analysis of Syntactic Sophistication and Complexity (TAASSC). In total, thirty-one clausal and eighteen phrasal syntactic indices were examined in detail. Correlation analyses revealed that several indices, such as passive constructions and nominal phrase dependents, serve as strong predictors of GRA scores. In particular, indices linked to noun phrase elaboration and passive structures demonstrated significant positive associations with higher GRA bands, suggesting that these features contribute to more advanced and sophisticated perceptions of grammatical complexity. Overall, these findings reinforce previous research and highlight that incorporating fine-grained syntactic complexity into writing assessments can improve scoring accuracy, strengthen objectivity, and enhance the reliability of automated evaluations.https://www.jeltal.ir/article_239380_96de20be4eb2c68467e58e4ec9793ec7.pdf