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To date, with the everyday growth of technology and the increase of online classes, busy modern teachers seek to lighten their burdens and boost their learners’ autonomy. Thus, this multi-method action research aimed to probe the differences between receiving computer-generated and direct corrective feedback (CF) on the syntactic accuracy and complexity of female adolescent Iranian EFL learners’ writing. Two intact classes took part in the study; one group (Group C) received CF from an AWE (Automated Writing Evaluation) tool, called Ginger software, and the other group (Group T) received CF from their teacher. Subject-verb agreement and verb form errors were considered to measure the syntactic accuracy while the average sentence length and verb form variation were regarded as the syntactic complexity. Moreover, via a questionnaire, the students’ perceptions of the kind of CF they had received were taken into account to see which one was more effective. Findings obtained from MANOVA revealed that both groups made significant improvements regarding syntactic accuracy. Group C produced more complex outputs after being exposed to the treatment while Group T didn’t make such progress. The results obtained from the questionnaire also indicated that both groups found the CF satisfactory. However, Group C held more positive attitudes. Not only was the Ginger application effective in decreasing the number of students’ writing errors but also it motivated them to be better writers and write more. The study further points to the likely merits of technology-enhanced feedback in improving EFL learners' writing ability in general, and their written syntactic accuracy/complexity in particular.

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.

Traditional methods of scaffolding for language teaching have turned out ineffective, leading to the exploration of innovative approaches such as blended learning. While blended learning has shown effectiveness in various language aspects, its impact on scaffolding for speaking proficiency remains unclear. This study investigated the impact of peer scaffolding on speaking proficiency in traditional face-to-face classes versus blended classes. The participants consisted of 42 advanced learners, randomly assigned to a control group (traditional classes) and an experimental group (blended classes). Pre-tests and post-tests were conducted using speaking topics to assess speaking proficiency, and evaluations were done using established criteria. The control group received instruction and speaking practice using conventional methods, while the experimental group had access to online resources and was engaged in face-to-face sessions guided by peers and the teacher. Dscriptive statistics and t-tests were employed to analyze the data. The findings indicated that the experimental group, which received peer scaffolding in the mixed class, performed better in speaking ability compared to the group that received peer scaffolding in the conventional class. These findings have implications for language teachers, material developers, and policy makers, emphasizing the potential benefits of integrating peer scaffolding within blended learning environments to enhance speaking proficiency for advanced learners.

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

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.

This paper discusses the use of Persian in comparison with Dari, a dialect of Persian language used in Kerman, one of the cities of Kerman Province located in southeast Iran. It is based on a random selection of 47 subjects from different sex, age, and occupational groups of Zoroastrian people with different levels of education in seven domains, i.e. family, friendship, neighborhood, transaction, education, government, and employment. In this study, the subjects were asked to determine which language they use in different domains on Likert’s 4-point scale. After collecting the data by the use of a questionnaire with 30 situations in the seven domains and analyzing them, the researcher concluded that there is a Persian-Dari diglossia in Zoroastrian speech community in which Dari functions as the Low language whereas Persian is the High one. As a matter of fact, Dari has been restricted to family domain and the young generation has lost it to a large extent.

Since 2010, deep learning has been further developed, and the concept of multi-modality has penetrated into all walks of life. However, it has not been fully researched and applied in college English teaching, so this study modeled and practiced the multimodal teaching method of college English under the deep learning mode and its application. The definitions of modality and medium are first introduced, and then the definition of multimodality in this study is clarified. Then the classification of multimodal transport is expounded. The random forest algorithm is chosen as the main algorithm of this research, and a dynamic multimodal model is established. After that, there was a collaboration with a university and sophomore students were selected for practice. After processing and analyzing the collected data, it was found that in the data sample of 268 students, the number of students who did not study independently accounted for 24%, which indicates that most college students lack interest in learning English. Preliminary tests were also conducted on students' English proficiency throughout the year, and the results showed that the students' English proficiency was at a pass level and the overall English proficiency was weak. Reassessment of students' English proficiency showed that the actual teaching effect of each English proficiency was greater than 85%, and the effectiveness of English teaching in the selected universities was significantly improved. The average score improved by 8 points, indicating that multimodal teaching is scientifically effective After a semester of multimodal teaching, the English teaching effectiveness of the university selected in this article has significantly improved. The research results indicate that the development of deep computer learning has introduced multimodal concepts into the teaching field, which is very suitable for assisting language learning based on its own advantages. After a semester of multimodal teaching, the English teaching effectiveness of the university selected in this article has significantly improved. The research results indicate that the development of deep computer learning has introduced multimodal concepts into the teaching field, which is very suitable for assisting language learning based on its own advantages.

After nearly a decade since the recognition of the importance of theticals, traditionally referred to as parenthetical constructions (see Kaltenböck et al. 2011; Heine et al. 2013), there has been a flurry of research on these linguistic elements across various languages, including but not limited to Romance languages (Schneider, 2007), Chinese (Long et al., 2019), Persian (Kazemian & Amouzadeh, 2019), and Arabic (Haddad, 2020). However, it appears that theticals still remain relatively understudied and warrant more comprehensive and fresh examination. This lack of interest in studying theticals, particularly those inherent in interaction, has prompted Bernd Heine to undertake writing a new book, “The Grammar of Interactives”, dedicated to these items and analyzing them as a distinct level called interactive grammar (IG) which works alongside sentence grammar (SG) to facilitate successful communication. The book is structured in a cohesive and organized manner, consisting of an introduction, six main chapters, and a conclusion, totaling eight chapters in all. This structure properly presents the book's content by establishing the context and scope in the introduction, delving into the subject matter in the core chapters each exploring a specific theme related to the overall subject, and providing a sense of closure and reflection in the conclusion.

With the spread of English, the conception of English is currently changing into English as a Lingua Franca (ELF) worldwide. However, the form of English teaching and learning is still identified by reference to native-speaker norms. In response to the increasing use of ELF and an emergent need to describe it in various domains, the current study takes a preliminary step in linguistic analysis of the written mode of ELF. Adopting an exploratory case study, the morphological marking of third-person singular present tense main verbs, i.e., -s/es has been analyzed using the Written ELF in Academic Setting (WrELFA) corpus. The selected corpus included 82369 tokens. It was tagged by the LancsBox software, and all instances of variation were categorized into two groups: omission and addition of the suffix. The quantitative analysis revealed that most ELF writers conform to the grammatical rules of English simple-present tense, yet, there is a negligible amount (0.5%) of variation in the use of this suffix in a way that writers either drop it or overgeneralize it. Dropping the third-person singular suffix accounts for around half of the entire variety (56%), and overusing this feature accounts for the other half (44%). Moreover, through qualitative analysis, factors contributing to such variations were identified. The overall findings indicate that such minor grammatical errors shouldn't be overemphasized, as long as they do not hinder the reader's understanding. The results may contribute to constructing a framework for teaching ELF in general and English for Research Publication Purposes (ERPP) in specific.

Crowdsourcing Translation as a Post-Editing Method (CTPE) has emerged as a rapid and inexpensive method for translation and has drawn significant attention in recent years. This qualitative study aims to analyze and synthesize the approaches and aspects underpinning CTPE research and to identify its potential that is yet to be discovered. Through a systematic literature review focused on empirical papers, we examined the limited literature thematically and identified recurring central themes. Our review reveals that the topic of CTPE requires further attention and that its potential benefits are yet to be fully discovered. We discuss the eight core concepts that emerged during our analysis, including the purpose of CTPE, CTPE areas of application, ongoing CTPE processes, platform and crowd characteristics, motivation, CTPE domains, and future perspectives. By highlighting the strengths of CTPE, we conclude that it has the potential to be a highly effective translation method in various domains.

Computer-Mediated Communication (CMC) modes can ease scaffolding through multimodality in collaborative writing tasks. However, there is an ongoing debate regarding synchronous and asynchronous CMC environments. Additionally, there are conflicting results regarding gender’s pedagogical beliefs in CMC applications. The current study aimed to explore if there is a difference between synchronous and asynchronous multimodal scaffolding on the freewriting complexity of EFL learners. Besides, genders’ perceptions about applying multimodal scaffolding were compared. Participants were 84 EFL learners who randomly assigned into three groups. For the pre-test, a picture, podcast, and movie were shared, and the participants were asked to complete their freewriting tasks individually within the allocated time. For treatment, one experimental group was scaffolded in a synchronous environment by sending messages on WhatsApp, and the other experimental group experienced asynchronous scaffolding via email. The results indicated that multimodal scaffolding is beneficial. However, no significant difference was found between the writing complexity of synchronous and asynchronous groups. Furthermore, a significant difference between males’ and females’ tendency to use multimodal scaffolding was uncovered. The findings highlighted the role synchronous and asynchronous multimodal scaffolding can play in collaborative writing tasks