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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.

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. 

One of the effective ways to increase the learning opportunities in language classes is provide conditions in which learners can provide feedback on one another’s performance. The results of studies have also confirmed its beneficial effects and even its superior effects compared to teacher feedback. Despite its positive effects, the results of some studies reveal that teachers are hesitant or cautious in their use of peer correction. It is not clear, however, what factors and conditions negatively influence the teachers’ willingness to embrace its potentials in learning. Accordingly, the present study was conducted to investigate the teachers’ attitudes and beliefs in this regard as well as the factors they take into account in their decision to advocate activities that involve the use of peer feedback. For this purpose, in-depth interviews were conducted with 63 Iranian EFL teachers using questions developed based on the related literature. Content analysis of the interviews revealed five major themes including effectiveness of peer corrective feedback, concern about learners’ negative emotional response to PF, the role of learners’ age in being receptive to PF, the role of learners’ proficiency level in PF effectiveness, and teachers’ perception of their learners’ preferences for and attitude toward PF. Generally, the majority teachers seemed to be doubtful in their tendency to use peer correction primarily because they thought their learners are not receptive to peer comments on their linguistic performance. The results carry significant implications for language teachers and teacher education programs.

This paper aims at studying the speech act of congratulation in Persian and English with regard to semantic formulas. To gather the semantic formulas related to congratulation, the researchers chose 100 movies (50 in Persian and 50 in English) as the instrument of the study. The only model of cross-cultural comparison was related to that of Elwood (2004). Therefore, we used Elwood’s model as the yardstick to design a new classification for coding congratulation utterances. The new model which is designed in this study covers the categories of the Elwood’s model but omits the overlapping strategies which were observed in that model. The new model enjoys more clarity and is more clear-cut. Also, the non-congratulatory categories of Elwood’s model are deleted in the new design. Six generic categories were recognized as the model of analysis: (1) offering congratulation; (2) mentioning the occasion; (3) blessing wish; (4) expressing feeling; (5) divine statement; and (6) complimenting. In order to investigate the significant of differences between Persian and English categories, the researchers employed Chi-square formula. The results of the study revealed that a) there is a significant difference among various semantic formulas in each language and b) Persian and English congratulation utterances are significantly different with regard to mentioning the occasion, expressing feeling, and divine statement. However, no significant difference was observed with regard to complimenting, offering congratulation and blessing wish. Pedagogical implications are discussed in the context of EFL to link theory into practice.

In spite of numerous studies on the effect of AIAT on foreign language learning, few have examined its impact on university students’ academic writing proficiency over an extended period. This study, therefore, investigated the effect of Google Translate (GT) on the writing proficiency of English as a Foreign Language (EFL) university students. It examined fluency, lexical density, accuracy, and syntactic complexity across four versions of students’ writings: the pretest, writing with the aid of GT, the posttest, and a retention test conducted two to four months after the treatment. The findings indicated that syntactic complexity, accuracy, and fluency improved when students used GT for writing; however, these measures showed a significant decline in the posttest and retention test without GT. This decrease was more pronounced in lexical density and less so in syntactic complexity. Despite this decline, all factors assessed in the retention test still showed improvement compared to the pretest, indicating the positive effect of GT on students’ foreign language writing performance.

This research attempted to examine the underlying construct of writing self-regulation inventory extrapolated to Iranian EFL university context. A total sample of 116 sophomore EFL university learners attending essay writing course participated in this study. They were asked to do an in-class writing task assignment and immediately fill in an inventory. Pearson product-moment correlation and confirmatory factor analysis procedure using principal component analysis were applied to ascertain the relationships among the variables and construct validity of the instrument, respectively. The inventory yielded a strong internal consistency as to make the results of the present study reliable and to prove replication studies justifiable. The highest overall means and internal consistency reliability estimates were recorded both for goal subscale. However, achievement on task was negatively associated with cognitive, meta-cognitive, motivational, and behavioral dimensions of writing self-regulation. The results of factor analysis disclosed that goal, efficacy, meta-cognitive, cognitive, motivational, and behavioral variables are loaded on a single component; that is, they measured the same underlying theoretical construct. On the whole, the findings imply that the construct of writing self-regulation is consistent in EFL university context.

Transfer of learning from English course to other contexts is one of the most fundamental objectives of English for Special Academic Purposes (ESAP) instruction. Providing opportunities to transfer the acquired knowledge from the ESAP writing course to writing tasks of specialized disciplines as well as analyzing students’ perceptions of transfer catalysts and barriers might suggest a foundation for future educational planning. This study examines how engineering graduate students who participated in an ESAP course assessed the four constructs of learning transfer inventory that might facilitate or inhibit the transfer of learning in discipline-specific academic writing programs. Sixty engineering graduate students participated in this study. During the ESAP course, collaboratively designed discipline-specific writing tasks were presented and practiced through multimodal input. The variation in participants’ writing skills throughout the semester was recorded and analyzed. The catalysts and the barriers to the learning transfer act were identified by administering the Learning Transfer System Inventory (LTSI). The participants’ evaluations of the treatment they had received was assessed through a focus group interview. Results indicated that the students could obtain significant levels of academic writing skills and finally transfer their acquired instruction to authentic discipline practices. Furthermore, data analysis of the LTSI demonstrated that transfer of writing outcomes will be increased if more consideration of work-related factors is considered in higher education. All participants reported personal capacity as the main impediment induced by the work-related construct. Students’ positive attitudes toward three ability factors and all motivational factors suggested that an auspicious foundation for future educational planning exists if disciplinary and institutional considerations are embraced.

Being rooted in imagery and metaphor, Jungian psychology suggests that metaphors are expressions of archetypal imagery. While extensive research has examined how archetypal theory informs literal metaphors across various languages, less attention has been paid to whether metaphorical conceptualizations can serve as a modality—similar to dreams or active imagination—for representing archetypes and the collective unconscious. Linguistic data from intercultural interactions are crucial for uncovering shared conceptual structures across diverse communities. This study explored the "Document on Human Fraternity for World Peace and Living Together" signed by Pope Francis and the Grand Imam of Al-Azhar as a pivotal text in contemporary interfaith dialogue. We analyzed how the processes of metaphorizing archetypes were woven into this discourse. Specifically, we investigated whether archetypes are represented within the conceptual blending processes of metaphors, how the collective unconscious is reflected in the conceptual metaphors employed in interreligious dialogue, and how these metaphors may foster shared understanding among religious leaders. Using Conceptual Blending Theory (CBT), we identified metaphorical expressions that projected archetypal content, revealing the presence of key Jungian archetypes, such as the Mother, Rebirth, Shadow, Innocent, and God-Image. Our findings indicated that significant shared conceptualizations existed between Islamic and Christian leaders, which were grounded in the collective unconscious and articulated through archetype-based conceptual metaphors.

This study aimed to explore Iranian teachers’ cognition of L1 use in L2 teaching as a component of classroom management, in EFL classes at private language schools in Iran. The study comprised 12 in-service teachers, and the sample size was decided based upon data saturation. The instrument employed in this research was a semi-structured interview, designed to elicit the participating teachers’ cognition. The interviews were audio-recorded and were subsequently transcribed. Thematic analysis of the data demonstrated that the teachers believed the extent and frequency of L1 use should be balanced based on the objectives of L2 lessons, so that classes could be smoothly managed and learners could be sufficiently exposed to L2. Besides, the participants held that for effective classroom management, teachers should use L1 judiciously and selectively. In addition, they accentuated the significance of attention to learners’ English language proficiency level, psychological factors, and educational needs in this respect. Moreover, they were aware of the potential role of L1 use with regard to classroom management strategies, such as establishing rapport, maintaining discipline, and managing time. Overall, the participants were cognizant of using L1 in L2 teaching as a classroom management component. This inquiry provides implications for supervisors of language schools, language teachers, and language teacher educators.

AI-assisted translation has gained increasing attention in recent years, yet its effectiveness remains underexplored. The present study sought to shed light on the role of AI (ChatGPT) in mediating translation. To this end, 46 postgraduate ESP students majoring in three sub-disciplines of politics (across three classes) were selected through convenience sampling. No outliers were identified in these classes, and each was assigned to one experimental group (AI-assisted group, N = 16; AI–Human Revised group, N = 16; Human-only Scaffolded group, N = 14). A posttest-only control group design was adopted, and each group was mediated according to its respective intervention protocol. AI was instructed to follow a graduated mediation protocol developed for the purposes of this study. The final translations were evaluated both qualitatively and quantitatively. Findings revealed that the end product of the AI-assisted group, compared with the human-involved groups, exhibited major translation deficiencies ranging from the lexico-semantic level to syntax, the syntax–semantic interface, and rhetorical patterns. Additional procedural deficiencies were also observed and reported. Furthermore, participants’ translations were assessed using a rubric, and quantitative analysis showed that both human-involved groups significantly outperformed the AI-only group.