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Recruiting efficient EFL teacher educators (TEs) is crucial for language institutes as it can directly affect the quality of language instruction and, consequently the success of language institutes. Nevertheless, language institute policies for employing TEs and strategies for their professional development have not been well-documented. To this end, semi-structured interviews were conducted in this qualitative study to investigate 30 language institute managers’ recruitment policies and professional development strategies for employing non-native English TEs in the Iranian EFL context. The participants’ answers to interview questions were transcribed and analyzed based on the three levels of the open, axial, and selective coding process. The results revealed that job experience, academic/educational competencies, and digital literacy are the most important features implicating the recruitment of TEs. As for professional development strategies for TEs, the main ones included holding regular meetings for TEs, asking TEs to take part in professionally relevant seminars, workshops, and webinars, and encouraging them to make peer observations of teacher education courses. These findings have implications for language TEs' recruitment and their professional development.

This study is aimed at investigating the effect of reading-based vs. discussion-based pre-writing activities on the writing ability of Iranian EFL learners. To this end, a quasi-experimental study was conducted with 40 Iranian intermediate EFL learners within16 to 20 age range who were selected based on their performance on an Oxford Solution Proficiency Test. They were divided into two experimental groups: Reading Group and Discussion Group. The former group was made to involve in some reading activity prior to doing the main writing task, and the latter group was made to participate in a discussion activity before the main writing task. After the treatment for 10 sessions, both groups were post-tested. The findings indicated that both groups’ writing ability improved over the course of the study, but the difference between the performances of the groups on the post-test was not statistically significant, although the Reading group’s mean score was greater than the Discussion group. The results of this study have some implications for students, language teachers, syllabus designers and material developers.

This study aimed to examine the impact of Group Dynamic Assessment (G-DA) on the listening comprehension of Iranian intermediate EFL learners. To this purpose, through the Preliminary English Test (PET) 140 Iranian EFL female learners in four English Language Institutes of Ahvaz, Iran, were tested, and 80 of them were selected as the sample of the study using convenience sampling. They were taught through group dynamic assessment. After the pretest and treatment sessions, the participants were given the listening comprehension post-test and the resultant scores were statistically analyzed to detect their development from pretest to post-test. The obtained results revealed that Group Dynamic Assessment (G-DA) had a positive impact on the participants’ listening comprehension. This finding implies that EFL teachers may need to consider the positive impact of dynamic assessment on EFL learners’ listening comprehension improvement and provide them with more opportunities to interact. They may also need to create a change in the traditional models of listening comprehension assessment which emphasize psychometric quantification of students' performances

Predicting students’ performance in a course is one of the major aims of educational data mining systems. In the present study, two and three-layer artificial neural networks (ANN) and neuro-fuzzy systems (NFS) were used to predict Iranian EFL learners’ final scores and compare them with scores given by their instructor. Sixty-six students’ scores in an English reading comprehension course comprising of five sub-scores of midterm (out of 40), quiz (out of 60), final (out of 50), class participation (out of 5) and bonus (out of 2) were used for training the systems. Two and three-layer ANNs and an NFS were trained to predict students’ final scores using training data. Researchers compared the students’ final scores given by their instructor and those achieved through the ANNs and NFS. The results showed that the NFS could predict and deliver scores that were closer to the linear sum of students’ scores. Moreover, three-layer ANN had a better performance than the two-layer ANN. According to these results, data mining techniques could deliver an accurate estimate of students' abilities in a particular course.

The current study primarily explored the link between EAP students’ L2 situational interest (SI) and academic reading transformative engagement (TE). Moreover, it explored SI and its subcomponents, triggered SI and maintained SI as predictors of TE. We also sought the role of different disciplines as moderators of the relationship between SI and TE. Finally, we investigated the big five personality traits as predictors of TE. The participants of this study were 160 undergraduate EAP students recruited through quota sampling. A quantitative research method with a correlational design was employed to conduct the study. Two questionnaires were adopted to measure academic reading TE and personality traits, and a questionnaire was adapted from math SI to English learning SI to assess the students’ L2 SI. The results revealed a significant and positive relationship between students’ L2 SI and their academic reading TE. SI significantly predicted TE, and between its subcomponents, only maintained SI strongly and significantly predicted TE. Neither the difference between the disciplinary groups in terms of students’ TE nor the interaction of the comparative disciplinary groups by SI was significant. The result indicated the agreeableness trait as the sole predictor of TE. Our findings have fruitful pedagogical implications discussed in the conclusion section.

Following the COVID-19 outbreak, educational institutes around the world including Iran transitioned from the face-to-face method to an online modality to sustain education. Adapting to this abrupt transition was challenging for teachers, especially those working in remote and low-resource schools. To have a profounder understanding of Emergency Remote Teaching (ERT) in rural secondary schools, in this qualitative study, the researchers explored the technological tools, teaching platforms, and assessment strategies employed by 12 Iranian English teachers during the pandemic. The analysis of the data, collected through semi-structured interviews and e-observations, revealed that the participants mostly, but not exclusively, used SHAD application as their online platform and used different technological tools for creating pedagogic content such as screen recorder, video editors, and PowerPoint. The teachers also adopted different methods for delivering teaching including flipped method, live broadcasts, pre-recorded teaching materials, voices, and images. They used Google forms, Digi forms, and video calls for evaluating the students; nevertheless, they chiefly deployed these tools for designing traditional exam types. The implications and limitations of the study are discussed.

This study explores how professional and student writers manifest their authorial identities and project their gender voices in their academic texts. To this end, 38 male-authored and 38 female-authored articles published in seven leading international journals were selected. Moreover, 38 articles written by male students and 38 articles authored by female students were collected from two universities in Iran. Taking an academic writing course, these students handed in their papers as term projects. These academic writings were analyzed based on Hyland’s metadiscourse framework comprising two major resources: interactional and interactive metadiscourse resources. The findings indicated the male authors mainly attended to discourse organization using more interactive resources while the female authors mostly solicited solidarity by employing more interactional resources. The professional authors engaged in a more critical stance using self-mentions and attitude markers and the students focused on discourse organization. Attitude markers and self-mentions, as markers of stance-taking, were absent in the students’ writing. The professional authors made use of their gender identity to promote their authorial identity instead of suppressing it. These results suggest that EAP programs should inform students how to employ both metadiscourse resources and their gender-based discourse choices to express their authorial identity more effectively.

Thanks to the significant achievements in Artificial Intelligence (AI), Machine Translation (MT), in general, and Google Translate (GT), in particular, have been extensively used in all facets of life, including language learning. However, faced with a plethora of research evidence on GT’s educational contributions, erroneous translations create disparity regarding its use in language learning. To address this lacuna, the present study systematically reviewed 10 databases, namely, Web of Science, Scopus, ERIC, ScienceDirect, Taylor & Francis Online, Wiley Online Library, SAGE Journals, Springer Link, Springer Open, and DOAJ. Additionally, it hand searched the reference lists of 44 studies selected to be included in the synthesis from database search along with references cited in three previous systematic reviews on similar topics to capture a comprehensive view of the literature related to the use of GT in language learning between 2010-2021. It reviewed 50 studies witnessing a rise in the number of studies in this area. Studies reported that although significant improvements in the quality of GT led to pedagogical gains and more tendency to implement it in language learning, instructors still distrust it. Accordingly, this research provides pedagogical implications and suggests avenues for future research on the use of GT in language learning.