مطالب

Employing reliable evidence-based academic word lists has been a noticeable concern for numerous educators, students, and researchers in English for Academic/Specific Purposes (EAP/ESP) courses. Currently, many of these courses still lack research-oriented materials and rely heavily on traditional ways of teaching field-specific terminologies. This study aimed to create a specialized corpus to identify the most frequent academic words in Welding Metallurgy (WM) and to analyze the most prevalent three- and four-word lexical bundles (N-grams). We employed a corpus-based approach, and identified top-tier journals of WM; then, we analyzed the articles from 2017 to 2023 that followed the Introduction, Methodology, Results, and Discussion (IMRD) format. As such, 875 empirical research articles were compiled and analyzed to establish a specialized corpus with four million words. After applying word selection criteria, 608 lemmas were identified. Furthermore, we recognized 68 technical acronyms in the field and grouped them into an independent list. We also highlighted the most prevalent N-grams to explore the field's formulaic language. Consequently, 61 prevalent technical N-grams were recognized. As part of pedagogical implications, this study would deepen ESP course instructors’ knowledge and urges them to be more mindful of evidence-based material. It also encourages students to give more weight to their fundamental discipline-specific needs by incorporating authentic word lists in practice.

The present study was an attempt to investigate the effects of textually enhanced dual subtitles (TEDS) on vocabulary learning and listening comprehension among Iranian intermediate-level English language learners. The research explored how different types of subtitles—TEDS, plain dual subtitles (PDS), and no subtitles—impact learners’ ability to learn vocabulary and influence their listening comprehension. To achieve this goal, 51 Iranian intermediate English as a foreign language (EFL) learners from a private Institute (i.e., Iran National Language Institute) were randomly assigned to three groups: The first experimental group, namely TEDS watched six episodes of the American sitcom Friends with TEDS; the second experimental group with PDS, and the control group without any subtitles. Before and after the treatment, all the participants took tests assessing their vocabulary knowledge and listening comprehension. The results revealed that, regarding vocabulary posttest, the participants exposed to TEDS performed significantly better than those who watched videos with PDS or no subtitles. However, the difference in listening comprehension scores between the TEDS group and the PDS group was not statistically significant. Additionally, the PDS group performed significantly better than the no-subtitles group in both vocabulary and listening comprehension tests. This research highlights the potential of TEDS in supporting vocabulary learning. The findings suggest that further exploration into different types of textual enhancement of various language elements and their effects on various language skills is necessary to improve instructional practices and enhance language learning tools.

Advances in generative artificial intelligence (AI), particularly large language models, offer new possibilities for language learning. This study, grounded in sociocultural theory, examined the impact of an AI assistant ( Monica ) on English as a Foreign Language (EFL) students’ writing development. A total of 120 male students (aged 26–36, A2 proficiency) participated in a four-month in-service program. The participants were randomly assigned to either an experimental group, which engaged in AI-mediated collaborative writing, or a control group, which collaborated face-to-face. A sequential explanatory mixed-methods design was employed, integrating pretest–posttest measures, questionnaires and semi-structured interviews. Quantitative analyses (Split-Plot ANOVA) showed that the AI-assisted group significantly outperformed the control group in Organization, Language Use, and Mechanics, but not in Content or Vocabulary. Importantly, students’ perceptions shifted dramatically: While only 23% initially held positive expectations, 90% reported positive experiences post-intervention, highlighting the role of affective factors in technology adoption. Qualitative data confirmed cognitive, metacognitive, and motivational benefits of AI interaction, but also revealed challenges including overreliance on AI, uncritical acceptance of feedback, difficulty integrating new vocabulary, and cognitive overload when faced with multiple corrections. Sociocultural concerns, such as academic integrity, face-saving practices, and peer judgment, further influenced student engagement. From a theoretical standpoint, the study contributes to sociocultural scholarship by evidencing the ways in which student–AI interaction shapes and mediates writing development. Pedagogically, it calls for intentional scaffolding to foster critical and reflective practices, reframing AI not as a functional tool but as a meaningful collaborator in the learning process.

This study investigated the effects of gamified language teaching on motivation and writing proficiency of Iranian pre-intermediate English as a foreign language (EFL) learners. Adopting a mixed-methods design, the study involved 60 learners aged 12–16, registered in four language classes of a private institute. Two classes were randomly selected as experimental groups receiving gamified language instruction, and two classes were chosen as control groups receiving traditional instruction. The quantitative data were collected through pre- and post-writing tasks scored using Jacobs et al.’s (1981) analytic rubric and a validated Persian version of Dörnyei and Taguchi’s (2009) motivation questionnaire. The results of mixed-design Analysis of Variance (ANOVA) revealed that learners exposed to digital gamification demonstrated significantly greater gains in motivation and writing performance than those in the control group. The qualitative data from semi-structured interviews further supported these findings, revealing themes of increased motivation, enhanced engagement, perceived improvement in writing skills, user-friendly technology, and a strong preference for gamified learning. The findings suggest that well-designed digital gamification can effectively enhance both affective and linguistic outcomes in EFL writing instruction. Pedagogical implications highlight the importance of aligning game elements with instructional goals while balancing extrinsic rewards and intrinsic motivation.

Integrating Self-Regulated Learning (SRL) principles within Electronic Portfolios (e-portfolios) promotes reflection, progress monitoring, and strategic refinement, potentially strengthening learners’ speaking self-efficacy. Despite this alignment, empirical research on self-regulatory e-portfolios for speaking self-efficacy is limited. To address this gap, the present study examined the effects of a OneNote-based self-regulatory e-portfolio on Iranian EFL learners’ speaking self-efficacy and their attitudes toward the tool in an online speaking course. Grounded in SRL and social cognitive theory, speaking self-efficacy was conceptualized as a multidimensional construct encompassing performance, linguistic, and self-regulatory self-efficacy. A total of 52 intermediate and upper-intermediate Iranian EFL learners, selected based on a PET sample test, were randomly assigned to an experimental or a control group. Over a five-week online course, the experimental group developed self-regulatory e-portfolios in OneNote structured according to Zimmerman’s (2000) cyclical model of self-regulation. In contrast, the control group received conventional instruction. Data were collected using the 18-item Self-Efficacy for EFL Speaking Scale (SEESS), an attitude questionnaire, and semi-structured interviews. A Multivariate Analysis of Covariance (MANCOVA) revealed statistically significant gains in performance, linguistic, and self-regulatory self-efficacy for the experimental group, with medium to large effect sizes. Learners also reported positive attitudes toward the e-portfolio, valuing its accessibility, organizational features, and support for reflection, goal setting, and feedback, despite some initial emotional and usability challenges. Overall, the findings underscore the pedagogical value of OneNote-based self-regulatory e-portfolios for enhancing speaking self-efficacy in online EFL contexts.

Though research into the dynamic nature of motivation has gained momentum, there are still some aspects of the issue which are in need of further scrutiny. One such under-researched area is the effect of different learning modules on the direction and pattern of motivational changes, particularly in virtual learning environments. Informed by this gap, the current study explored how EFL learners’ motivation fluctuates based on different learning modules. In so doing, the participants were selected from institute, high school and university contexts. Thus, a major objective of the study was probing the differences among the three contexts as regards motivational fluctuations caused by involvement with different lesson modules. Motometer was utilized as the main means of data collection. Also, in an attempt to triangulate the data collection procedure, retrospective thinking was employed following the collection of Motometer data. Based on the findings, for institute learners, the mid-time of their performance process was the peak motivation time. Furthermore, it was found that the learners experienced more motivation on the activities included in the oral module as opposed to reading activities. Conversely, high school students reached higher levels of motivation on the reading module as opposed to speaking and listening sections. Finally, although significant differences were identified between the institute and school settings concerning mean motivational values for oral modules, no significant difference was observed among the patterns of motivational fluctuations occurring for institute, high school and university students on reading module. The implications of the findings are discussed throughout the paper.

Despite its pivotal importance in comprehension and production, many English as a Foreign Language (EFL) learners struggle with retrieving and applying new vocabulary beyond class. This study investigated the comparative effects of the Ripple Effect Approach (REA) and the Word Wall Approach (WWA) on vocabulary retrieval and production among Iranian intermediate EFL learners. Sixty participants (30 females and 30 males), aged between 18 and 23 years ( M age = 20.5), were selected through the Preliminary English Test (PET) and randomly divided into two experimental groups. The REA group was taught through interconnected, contextualized vocabulary exercises, while the WWA group received visual aids and interactive word displays. A quasi-experimental pretest-posttest design was employed, with data collected through vocabulary tests. Statistical analyses, including repeated-measures ANOVA and MANOVA, revealed significant improvements in vocabulary retrieval and production for both groups. However, the REA group demonstrated higher retention rates, with a mean increase of 3.6 points in retention from pre-test to post-test, compared to a 3.2-point increase for the WWA group. These findings underscore the effectiveness of interactive and varied instructional approaches in enhancing vocabulary acquisition and retention among EFL learners. Implications for educators suggest incorporating the REA and WWA to meet diverse learner needs and improve teaching practices, emphasizing the importance of integrating innovative, learner-centered techniques into educational curricula. Incorporating these approaches might develop adaptive and responsive educational frameworks, enhancing EFL learners’ learning outcomes and experiences.

Social media platforms, particularly Twitter, have transformed how academics communicate, disseminate research, and engage with broader audiences. This study explored intertextuality within academic tweets crafted by applied linguists across five English-speaking countries: the United States, the United Kingdom, Australia, Canada, and Ireland. By analyzing tweets from prominent Applied Linguistics associations, the research identified intertextual representations and examined how they refer to or incorporate other texts. The study used a qualitative approach to uncover the forms and functions of intertextuality, highlighting the complex relationships between texts and social actors on Twitter. A corpus of 300 tweets from major associations in Applied Linguistics provided a rich dataset for analysis. Key findings indicated that intertextual practices in academic tweets are crucial for self-promotion, publicizing research outputs, and building academic communities. Multimodal quotations, digital mentions, and hyperlinks enhance engagement, extend reach, and provide additional context. Tweets served multiple functions, including community building, networking, and public dissemination of academic knowledge. The study highlighted the evolving nature of academic communication on social media, suggesting that applied linguistics groups strategically use Twitter to enhance their scholarly presence and impact. Practical implications included the strategic use of hashtags, multimodal elements, and active engagement through retweets, mentions, and replies, which improve visibility, impact, and foster a sense of community within the field.

Although generative artificial intelligence (GenAI) is reshaping language education globally, its integration into English for Specific Purposes (ESP) instruction in Iran has remained limited by rigid curricula, restricted autonomy, and lack of authentic, discipline-specific resources. This study sought to address this gap by developing a contextualized co-design framework to align AI affordances with local pedagogical realities. Guided by theoretical triangulation, a hybrid methodology was employed that combined design-based research, co-design, and participatory qualitative approaches. The needs analysis phase involved twenty-six ESP stakeholders, including eight instructors and eighteen learners. In-depth interviews were then conducted with a subset of nineteen participants—eight instructors and eleven learners. Three instructors and three learners, chosen purposively among those involved in both prior phases, along with three policymakers and three AI experts, participated in the last co-design phase to ensure multiple perspectives in model development. As revealed by the findings, the learners prioritized personalization, writing support, and disciplinary adaptability, whereas the instructors emphasized controlled prompting, ethical literacy, and assessment redesign. Concerns shared between the two groups included overreliance, epistemic authority, and unequal digital access. The co-design process generated a cyclical instructional model incorporating dual human-check mechanisms, ethical self-reporting, bias-awareness checkpoints, multimodal feedback loops, and institutionalized teacher training. Offering a theoretically grounded and adaptable reference for discipline-specific AI use in ESP programs, this study’s framework can guide educators, curriculum designers, and policymakers in ESP contexts analogous to those investigated in this research.