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The present study sought to compare the effect of two modes of corrective feedback, that is, recast and elicitation, on the speaking accuracy of impulsive and reflective EFL learners. In doing so, 95 intermediate EFL learners who were studying at Tehran's Kish Language School were selected through nonrandom convenience sampling and sat for the Impulsivity Sub-Scale of Eysenck's Impulsive Questionnaire (EIQ). A total of 15 learners who were within the middle range were excluded, thus leaving 80 impulsive and reflective learners. Subsequently, a sample PET speaking test was administered as the pretest to assess the participants' speaking accuracy at the outset. Next, the participants were divided into four subgroups: 20 impulsive and 22 reflective learners undergoing a recast treatment, and 18 impulsive and 20 reflective participants experiencing elicitation. Once the 16-session treatment ended, another sample PET speaking test was administered as the posttest, and all four hypotheses were tested through a two-way analysis of covariance. The findings demonstrated that both recast and elicitation were significantly effective in improving the participants' speaking accuracy, while the elicitation impulsive group benefited the most compared to others. The pedagogical implications of this research and suggestions for further study are elaborated in the paper.

Education has evolved significantly over the centuries, ranging from the ancient and classical era to the Industrial Revolution, inclusive education, and technology integration. In the latter part of the 20 th century, technology was incorporated into education, starting with audiovisual aids and computer-based learning through to distance learning, online learning platforms, virtual classrooms, and collaborative tools, transforming education into a more flexible and accessible experience (Chiu et al., 2023; Ghahari & Nejadgholamali, 2019; Ng et al., 2023). Having emerged in the 2000s, personalized learning platforms and massive open online courses (MOOCs) offered free or low-cost online courses to a global audience and catered to individual student needs and learning styles. Finally and most recently, artificial intelligence (AI) has provided personalized recommendations, automated grading, and data-driven insights to optimize learning through such tools as Jasper, Sudowrite, Quillbot, and ChatGPT (Bates et al., 2020; Rahiman & Kodikal, 2024; Rospigliosi, 2023). The present handbook is a must-read for any aspiring teacher and researcher, providing a clear and concise guide on how to use ChatGPT in classrooms. It introduces ChatGPT as a cutting-edge tool that can revolutionize teaching and learning and spotlight the process rather than only the product. ChatGPT was created and offered by OpenAI as a pre-trained language model in 2022 and is an extension to a line of writing tools that build on Grammarly, the Hemingway app, Google Docs, Microsoft Word, etc. It is a variant of the GPT (Generative Pre-trained Transformer) model and is trained on a large dataset of conversational text. It is already reforming businesses and industries like higher education, similar to the printing press and the internet. At its core, ChatGPT uses AI to compose responses to queries spanning numerous topics. It can help educators optimize their classroom practices, particularly assignments, and evaluation, throughout the course rather than only addressing educational outcomes. Naturally, in education, the camps are divided between those opposing the use of ChatGPT as a result of concerns about academic integrity and potential cheating and those who believe it can be a valuable supplement to traditional instruction for supporting instructors and students. As an instructional technologist, Skrabut takes the latter stance and recognizes the potential benefits of ChatGPT in enhancing the learning experience. He maintains that ChatGPT for education is similar to calculators in math, which can be fine-tuned for a variety of natural language processing tasks such as language translation, question answering, and test construction.  "80 Ways to Use Chat GPT in the Classroom" offers a number of examples of using ChatGPT to enhance the classroom experience in teaching and learning. However, students need to be trained in information literacy, which is critical for developing critical thinking and lifelong learning skills. Simply rehearsing information from ChatGPT without verification does not contribute to meaningful conversation. Right at the beginning, the author provides the basic instructions to work with ChatGPT and then outlines a set of keys to using it more effectively. Surprisingly enough, the reader will find these instructions and hints highly comprehensive and informative. The keys to obtaining successful responses include (a) Be as specific as possible when making a request; (b) Use an iterative approach (asking the same question in different general or specific ways); (c) Ask ChatGPT to improve its responses to meet your expectations; (d) Assign ChatGPT a role/act to serve (e.g., act as Linux, interviewer, plagiarism checker); (e) Always validate its responses by applying critical thinking skills. Most favorably, the author has supplied multiple examples for each task that ChatGPT can do. Each example has two parts, including the prompt to provide to ChatGPT (bold-typed) and the response from ChatGPT (italicized). According to the author,  if ChatGPT is used appropriately and strategically, the possibilities are extremely helpful and time-saving. Chapter 2 indicates how ChatGPT can assist in the course preparation procedure, starting with the course description to developing classroom activities. In the first step, the user may ask ChatGPT to describe a course by clearly introducing what it is about. Next, ChatGPT can help in creating actual goals and objectives for the course. Here, the author suggests that users guide ChatGPT to create valuable results by citing Bloom's Taxonomy, for instance, in their prompts. An example of a good prompt suggested by the author follows: "Write learning objectives for a sports management course at the remembering level of Bloom's Taxonomy using verbs like Cite, Define, Describe, Draw, Enumerate, Identify, Index, Indicate, Label, List, Match, Meet, Name, Outline, Point, Quote, Read, Recall, Recite, Recognize, Record, Repeat, Reproduce, Review, Select, State, Study, Tabulate, Trace, Write" (p. 21). ChatGPT can also assist teaching practitioners in crafting lesson plans, classroom activities, warm-up questions and activities (i.e., icebreakers), community-building activities (e.g., teamwork and class discussions), lecture notes and outlines, and assignment prompts. What is highly important in persuading ChatGPT to prepare these tasks is to give it as specific prompts as the user can. Chapter 3 concerns using ChatGPT as a teacher assistant in personalizing instruction (i.e., personalized education). Some of its contributions include: (a) grading written assignments and essays (given either generic or specific guidelines), (b) facilitating reading comprehension by generating text summaries, (c) creating fill-in-the-blanks stories (i.e., Madlibs) usually in enjoyable and funny way, (d) crafting writing samples for any given prompt or topic, (e) creating personalized study plans attuned to each student's learning abilities, and (f) generating dummy data such as exemplars. What is highly important at this stage is to provide detailed and clear guidelines, precisely indicating the length, word size, and scope, before ChatGPT gets started. Here are some effective prompts as models: Generate questions about with corresponding answers at a college level; Provide ten creative writing prompts for an essay writing class at the high school level; What are some interesting or novel ways to begin a math class with children; What are some icebreaker activities one could use for a college-level course. In Chapter 4, ChatGPT is introduced as an effective tool for assessment by quickly and easily creating a variety of test tasks and questions. Among the ways in which it can serve as an assessment aid are creating assessment rubrics for subjective tasks and designing test items of a variety of formats, including multiple-choice, fill-in-the-blanks, dichotomous or true-false, matching, and ordering forms. After deciding on and determining the target article or text as a prompt, one may ask ChatGPT in the following exemplary way: "Create one (or more) fill-in-the-blank exercise on " (p. 65). Chapters 5 and 6 illustrate how ChatGPT can assist teachers and students in developing study aids and classroom activities. Using ChatGPT in building study aids such as summaries, notes, outlines, flashcards, and vocabulary lists can make learning procedures more convenient, enjoyable, and effective. Teachers may ask ChatGPT to generate example sentences using a certain word, write a list of words and definitions for an article, and create a list of flashcards for the given words. ChatGPT can also aid in checking the authenticity of students' essays and in generating arguments and counterarguments on a given topic for classroom debates. The last two agendas, for instance, can be accomplished by giving the following prompts, respectively: "Did AI write this essay? " and "Debate me on the use of AI in higher education. I believe it should be used. You are to take the opposing side" (p. 77). Even more interestingly, ChatGPT can be assumed as a classroom member interacting with teachers and/or students. After raising a question or topic in the class, the teacher can ask the students to predict ChatGPT's responses and then compare the students' responses to those of ChatGPT. Given enough rubrics and guidelines, the students can also be invited to grade ChatGPT's responses and essays and realize the strengths and weaknesses of AI by themselves. Taking the students' side, Chapter 7 indicates how students can improve their writing and communicative skills by using ChatGPT as a digital tutor and partner. ChatGPT can help students in crafting essays, paper summaries, research papers, lectures, and presentations by improving both form (e.g., grammar, vocabulary, coherence) and content (e.g., themes, main ideas, ordering, and organization). In addition, it can provide feedback on their writing assignments before submission and help them revise their drafts after getting reviewed. ChatGPT can also serve as an assistant translator and conversation partner, thereby contributing to the student's language skills development. It is also a digital tutor, being accessible anytime not only to reply to the students' questions but also to personalize learning materials by adjusting the responses to their needs, age, and level of ability. For this purpose, the user may only need to guide ChatGPT in the following exemplary way: "Answer this question or explain this topic to a 15-year-old or beginning student". Further, ChatGPT can serve as an exceptional research assistant by helping students discover trending research topics, formulate research questions, develop annotated bibliographies, paraphrase and summarize content, find credible sources, and draft and edit sections of a document. Chapter 8 showcases how ChatGPT can be used in computer programming and application development. Given a specific and accurate script, ChatGPT can quickly and easily write codes, explain what a certain code does, troubleshoot the codes, clean up unnecessary codes, write scripts for Microsoft, Google, Apple, and Linux products, and enhance programs like spreadsheets or word-processing. Chapter 9 extends to other applications of ChatGPT, such as developing blog posts, writing book reviews, drafting grant proposals, writing play/video scripts, and role-playing scenarios. It also effectively assists in drafting email messages, letters of recommendation, job interview questions, press releases for projects, and award packages suitable for nominees and accomplishments. It can be further used for converting references to different formatting styles (e.g., APA, MLA, Chicago), converting grammatical structures (e.g., number, gender, tenses), analyzing data sets, and summarizing large amounts of content before a meeting or classroom session. Chapter 10 illustrates how practitioners can suppress their inhibition and/or fear of using AI as an education and assessment tool. It offers fundamental guidelines and strategies that help teachers and students find ChatGPT an asset rather than a threat. There are times when AI is appropriate and others when it is not. Teachers may ask the students to detect its flaws and limitations; they should be explicit on what is allowed and what is not. For example, if they are not allowing tools like ChatGPT, explain why it is essential to refrain from using it and the educational benefit of the assignment. ChatGPT would not have access to proprietary academic databases. Additionally, it does not have access to current events. Another point to consider is that "ChatGPT is a textual interface. It cannot see images or hear audio files. The more friction you introduce into the assignment, the less appealing it will be to use AI" (p. 159). Although organizations and instructors can enhance their productivity and save time through ChatGPT, there is a caveat regarding the accuracy of the information it offers, requiring the users to check the information from multiple other sources. Skrabut explains his point very clearly by stating that AI will inevitably impact teaching and learning, just as previous technologies have, but educators are required to prepare students for this future. While ChatGPT is an intriguing emerging technology, it is not yet a perfect tool and it is essential to weigh the potential drawbacks. While the book provides comprehensive instructions with practical examples, it lacks depth in addressing ethical concerns and academic integrity. For instance, it does not sufficiently explore ChatGPT's potential drawbacks, such as the risk of over-reliance on AI tools or diminishing critical thinking skills among students. Furthermore, the discussion on academic integrity could benefit from providing instructors with a list of hands-on techniques on how to minimize the possibilities of AI-assisted cheating. Although the book is highly practical and advisable, these limitations may explain the need for further research and instructional guidance on how to mitigate the potential threats associated with ChatGPT use in educational milieus. 

Machine translation (MT) of literary texts presents unique challenges due to their stylistic complexity and cultural nuances. This study evaluated the performance of Google Translate (GT) and Microsoft Bing Translator (MBT) in translating Camus’s The Stranger from English to Persian. Data collection for this study involved automated evaluation using the Bilingual Evaluation Understudy (BLEU) metric and human evaluation conducted by three experts using the Localization Industry Standards Association (LISA) rubric. The results showed that GT significantly outperformed MBT across nearly all dimensions. GT achieved a BLEU score of 21.57 compared to MBT’s 6.36, with superior n-gram precision at all levels. The human evaluation phase also revealed GT’s fewer critical and major errors in almost all categories compared to MBT. However, both systems struggled to preserve the aesthetic and philosophical richness of The Stranger . These findings highlight the persistent limitations of MT in literary translation, particularly for linguistically distant pairs like English and Persian. While MT shows potential as a supplementary tool, it remains unsuitable as a replacement for human translators in capturing the depth and artistry of literary works.

Abstract The present study developed a model of L2 speaking proficiency investigating how lexical sophistication, lexical diversity, syntactic sophistication, syntactic complexity, and cohesion are associated with holistic scores of L2 speaking proficiency employing structural equation modeling (SEM). A corpus of 419 monologues delivered by Iranian EFL learners was compiled and rated to develop the model. Based on the overall scores, the corpus was divided into independent (B1 and B2) and proficient (C1 and C2) users. The results of SEM analysis revealed that the developed L2 speaking proficiency model had an acceptable fit, with partial generalizability across independent and proficient users. Structural regression analysis showed that lexical diversity, lexical sophistication, syntactic sophistication, cohesion, and the indirect effect of syntactic complexity through lexical sophistication explained 34% of the variance in L2 speaking proficiency in descending order of importance. However, their relative importance changed depending on proficiency level. Based on the results, while lexical, syntactic, and cohesive features are sound predictors of L2 speaking proficiency, they function differently across proficiency groups. These findings offer valuable insights for improving speaking proficiency assessment by showing that lexical sophistication, lexical diversity, syntactic sophistication, syntactic complexity, and cohesion do not contribute equally to overall L2 speaking proficiency, and their order of importance varies across proficiency levels. Therefore, prioritizing indicators of L2 speaking proficiency in assessment frameworks based on their importance in each proficiency level can add to the validity and reliability of speaking assessments.

English Language Teacher Education (ELTE) programs in Iran have been designed in a distinctive bilingual environment where private language institutes offer influential training foundations for most English as a Foreign Language (EFL) teachers. This study examines the structure and content of teacher preparation programs in four prominent Iranian language institutes to identify the core components of their training courses. To gather data, semi-structured and focus-group interviews were conducted with two novice teachers and two teacher educators from each institute, selected through purposive sampling. Thematic analysis of the data revealed that training programs emphasized seven key themes: Teaching Methods, Flexibility, Practical teaching, Reflection, Native language use, Culture, and Technology. These findings can offer English language teachers valuable insights into their future roles and provide policymakers with rich data to evaluate existing programs and make necessary modifications in areas that require improvement. Potentially bridging the gap between theoretical training and practical classroom demands.

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.

Language learners find it hard to change a text’s wording and present it differently while maintaining the original meaning in the text. This research, therefore, examined the effect of concept mapping instruction on summarizing short stories for EFL learners. Two intact grade-eight classes were assigned to experimental (n = 20) and control (n = 18) groups randomly. They summarized a starter-level short story, Drive into danger, using a maximum of 450 words as a pretest. Next, the experimental group experienced concept-mapping instruction, whereas the latter group received the traditional way of teaching summarization, for six consecutive weeks. Both groups summarized the same story again, based on their instruction, into a 450-word text at a maximum as a posttest. Pretest and posttest summaries were assessed in terms of content, organization, vocabulary, and language use. The experimental group positively improved on overall performance, content, and organization, marginally improved on vocabulary, but did not improve on language use. Furthermore, the participants’ feedback on the instructional treatment supports the statistical results. The findings offer several instructional implications.

This article investigates how native Persian speakers process and comprehend affirmative and negative discoursal causal assertions. To examine this, an eye-tracking experiment was conducted with 10 male and 20 female Persian-speaking participants. The main experiment involved 32 Persian vignettes, each containing three sentences: an opening sentence, a target sentence (affirmative or negative discoursal causal), and a concluding sentence. The polarity of the target and concluding sentences was varied (affirmative vs. negative) within participants. When participants heard an affirmative discoursal causal assertion (e.g., Because my skin was dry, I applied moisturizer ), they primarily fixated on the factual phrase ("applying moisturizer"), with a fixation probability of 63%, whereas the conjectural phrase received little attention, attracting only 12% of fixation probability. A similar pattern was observed for negative assertions (e.g., Because my skin was not dry, I did not apply moisturizer ), where participants focused on the factual phrase ("not applying moisturizer"), attracting only 63% of fixations, largely ignoring the conjecture, with a fixation probability of only %19. Fixation data confirmed that factual phrases consistently received more attention than conjectural ones during early processing stages. In the final analysis, the effect of specificity on fixation patterns was tested. Results showed that specificity did not significantly influence either early attention or increased attention to factual content across polarity conditions. Overall, the findings align with Mental Model Theory, emphasizing the cognitive priority given to factual representations

Augmented reality (AR) and virtual reality (VR) have emerged as transformative technologies in English as a Foreign Language (EFL) education, offering immersive, adaptive environments that enhance learner engagement, retention, and motivation. This systematic review synthesized 48 peer-reviewed studies published between 2019 and 2024 to examine AR/VR applications, implementation strategies, challenges, and learning outcomes within EFL contexts. The researchers established inclusion criteria—English language studies published from 2019 onward in Scopus-indexed language teaching and learning journals, fully accessible online, and thematically aligned with research objectives—and applied exclusion criteria to studies that were non-English, dated before 2019, restricted in access, or published in low-impact or non-verified outlets. Data from the selected articles were imported into MAXQDA 24 for qualitative coding, yielding 64 open codes that were consolidated into 12 axial codes and further synthesized into six overarching themes: learner engagement, integration strategies, implementation practices, learner perceptions, adoption challenges, and language acquisition outcomes. Findings indicate AR/VR interventions significantly bolster engagement and linguistic competence when embedded within pedagogically sound frameworks, although technical constraints, cost considerations, and teacher readiness can hinder adoption. Educators should design scalable, user-friendly experiences and invest in targeted professional development to optimize outcomes. This review advances our understanding of AR/VR’s pedagogical potential in EFL settings by highlighting evidence-based practices and persistent challenges. It offers actionable recommendations for future research.

Lexical bundles, starting with the anticipatory it, mostly serve as stance expressions (e.g., it is necessary to ). While most research centers on anticipatory, it-bundles in one single discipline, not much has been done across different disciplinary areas. Therefore, based on an adaptation of the functional taxonomy proposed by Hewings and Hewings (2002), this research attempted to detect it-bundles using a corpus of 400 research papers in L1-English and L1-Persian in applied linguistics (AL) and information technology (IT) to probe the possible significant resemblances and disparities. According to the results, IT writers employed fewer bundles than their AL counterparts, and their overuse was more impressive than that of their L1-English peers in AL. However, AL and IT writers showed similarity in their use of functional categories; AL writers also made heavier use of two functional categories: emphatic and epistemic. As for practice, writing instructors can exploit the findings of this study to facilitate academic writing instruction. They can also help students to achieve a better comprehension of anticipatory it-bundles .

The use of portfolios as a tool for assessment in educational settings has attracted significant attention in recent years due to its potential to capture multifaceted aspects of student learning. This study investigates students' perceptions of portfolios as an assessment tool, examining their experiences, attitudes, and beliefs towards its effectiveness in assessing their learning progress and achievements. Additionally, the study explores the influence of factors such as prior exposure to portfolio assessment, instructional support, and personal learning styles on students' perceptions. The research examined students’ responses to portfolio-based assessments over three academic years, from 2020 to 2023. The respondents were third-year elementary education students enrolled in the Faculty of Education at the public University of Gjakova, Kosovo, where the research was conducted. Additionally, the study incorporated a focus group consisting of five English language teachers to examine both the advantages and disadvantages of portfolio assessment, as well as the challenges associated with evaluating students through this method. A qualitative research approach was employed, utilizing qualitative analysis for the questionnaire responses and a descriptive approach for the data collected from teachers. The analysis of student outcomes yields several insights into portfolio-based assessment. The findings suggest that this assessment method enables a more convenient preparation process, as students have ample time, a supportive environment—such as their homes—and the flexibility to engage in learning according to their unique preferences and styles. According to teachers, the portfolio is perceived as straightforward in its appearance, yet it presents significant complexities in terms of implementation and assessment. The integration of portfolio assessment in curriculum design and the provision of structured guidelines and support could be underlined as practical implications and recommendations to enhance the effectiveness of assessment-based portfolios in educational settings.