درخت حوزه‌های تخصصی

This cross-cultural study aims to examine how Iranian and American motivational speakers employ metadiscourse devices as a convincing tool to interact with their audience. To this end, eight motivational speeches in English and Persian were randomly selected from 2015 to 2021, and analyzed for the use of stance (i.e., hedges, boosters, attitude markers, and self-mentions) and engagement (i.e., reader-pronouns, directives, questions, shared knowledge, and personal asides) expressions. The findings showed that self-mention and attitude markers were the most frequently used stance markers in English and Persian corpus, respectively. Moreover, hedges found to be the least frequently used stance markers in the two corpora. With regard to the use of engagement markers, results showed that reader pronoun is the most frequently used engagement markers, and shared knowledge and personal asides were the least frequently used engagement markers in both languages. Finally, the results of chi-square test showed statistically significant differences in the use of stance and engagement expressions in the two languages, confirming cultural septicity nature of metadiscourse markers, and that speakers of different languages employ interactional devices according to their context.

 Juxtaposing the ubiquitous facets of mobile technology as everyware (Greenfield, 2010) and vocabulary as one of the most axial aspects of language learning (Bowles & Cogo, 2016; Schmitt & Schmitt, 2020) , besides the importance of considering learners’ attributes and needs (Taghizadeh, 2019) while developing a mobile vocabulary application (app), necessitates analyzing the relationship and impact of all these elements in a single structural model. To tackle the issue, first, via a mixed-methods design, the researcher developed a bespoke mobile application using the task model and the principles of agile methodology. and then investigated the impact of using the app on a sample of 62 Iranian EFL university students’ vocabulary recognition and recall, the results of which were published in two other articles. In this study, the researcher integrated the obtained data within a proposed structural model and assessed the model's fitness to investigate the interaction and interrelationship among the latent variables mentioned above. The results obtained from SEM-PLS analyses revealed that within the unified structural model, the learners’ preferences and needs were favorably influenced by their learning style orientation and technology savviness. Similarly, the findings verified the positive impact of considering learners’ preferences and needs during the agile app development lifecycle on the target participants’ vocabulary knowledge, encompassing vocabulary recognition and recall. Finally, the fitness of the proposed structural model was verified based on the criteria for model assessment mentioned by Sparks and Alamer (2022) . The SEM-PLS data analyses and the implications of the study are presented and discussed.

Cognitive diagnostic models (CDMs) have received sustained attention in educational settings because they can be used to operationalize formative assessment to provide diagnostic feedback and inform instruction. A large number of CDMs have been developed over the past few years. An important component of all CDMs is a Q-matrix that specifies a particular hypothesis about the relationship between each test item and its required attributes. The purpose of this study was to construct and validate a Q-matrix for the reading comprehension section of the Islamic Azad University English Proficiency Test (IAUEPT), as an advanced English placement test designed to measure language ability of Ph.D. candidates who tend to pursue their studies in the IAU. To achieve this, using item responses of 1152 candidates to twenty items of the reading section of the test, an initial Q-matrix was constructed based on theories and models of second/foreign language (L2) reading comprehension, previous applications of CDMs on L2 reading comprehension, and brainstorming and consensus of five content experts. Then, the initial Q-matrix was empirically validated using the method proposed by de la Torre and Chiu (2016) and checking mesa plots, and heatmap plot. Five attributes were derived for the reading comprehension section: vocabulary, grammar, making an inference, understanding specific information, and identifying explicit information. Finally, the analysis of the Generalized Deterministic Inputs, Noisy “and” Gate (GDINA) regarding absolute fit at item- and test-level as well as three residual-based statistics showed the accuracy of the Q-matrix and a perfect model-data fit.

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.

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 investigated the interplay of working memory capacity and language proficiency in the context of vocabulary acquisition through word-focused tasks. The involvement load hypothesis served as a theoretical framework, positing that the degree of cognitive engagement influences lexical learning outcomes. A total of 100 EFL learners participated in this study. They were divided into distinct groups based on varying levels of working memory capacity, language proficiency, and aspects of working memory (phonological short-term memory and executive working memory). The participants engaged in receptive and productive vocabulary tasks under different experimental conditions, including reading-only, reading plus blank-fill, and reading-plus production. The results revealed intricate relationships between working memory capacity, language proficiency, and vocabulary acquisition. While the efficacy of the hypothesis varied across conditions, its predictions were influenced by the nuances of individual cognitive capabilities and language competence. Learners with higher proficiency levels acquired more lexical items, both receptively and productively.  Although the difference with the phonological short-term memory was not significant, executive working memory was more facilitative of lexical gain. Additionally, the role of input modality in shaping vocabulary learning outcomes was highlighted. That is, reading plus production and blank-fill tasks resulted in more lexical gain than reading-only tasks.  The study contributes to the theoretical understanding of vocabulary acquisition by underscoring the complex interplay of cognitive processes and language factors. These insights hold implications for foreign language pedagogy, guiding educators in crafting more effective interventions for enhancing both receptive and productive lexical knowledge.

In the present study, we analyze the semantic fragmentation and conventionalization in Persian compound nouns ending in the verbal stems –andāz ‘throw’, -band ‘fasten/close,’ -foruš ‘sell’, -gir ‘catch’, -keš ‘pull’, -paz ‘cook’, -yāb ‘find’, and -zan ‘hit’ from the usage-based perspective. The analysis is based on a 800 data set extracted from diachronic and synchronic corpora. The words produced from the general compounding pattern [XV PRS]N can be categorized in a range of semantic categories, including agent, instrument, location, and object. In describing the semantic fragmentation of [XV PRS]N, we propose the human agent as the starting meaning, from which the instrument sub-pattern is derived by the mechanism of metaphorical extension. However, to justify the object and location meanings, we consider the metonymic extension mechanism to be involved. The sense extension mechanisms do not only apply to the individual words but can happen on the pattern level. It is also argued that these mechanisms are not mechanically applied to all the patterns ending in the verbal stems, instead, it is the usage and the communicative needs of the speakers that determine the semantic fragmentation of any patterns. To illustrate this point, as a case study, we focus on the development of instrument meaning in the pattern [X-paz PRS]N. We show that the instrument sub-pattern is a recent linguistic phenomenon that coincides with the introduction of modern cooking equipment with mostly English names to Iranian society. The increasing use of these types of equipment has led to a new communicative need for naming such instruments. This extra-linguistic factor has motivated the pattern [X-paz PRS]N to be extended through analogy with English compound instrument nouns. The findings of this study may contribute to the understanding of word-formation patterns in general and compounding patterns in particular.

The documentation of test takers’ achievements has been accomplished through large-scale assessments to find general information about students’ language ability. To remove subjectivity, Cognitive Diagnostic Assessment (CDA) has recently played a crucial role in perceiving candidates’ latent attribute patterns to find multi-diagnostic information rather than single proficiency classification. However, there are some gaps in the literature about in detail investigation of test takers’ listening comprehension language ability in responding to placement test items of a public English language center. The present study aims to validate an English placement test at a language center through a retrofitting process. In an exploratory mixed-method design, 449 participants from the same language center, including 274 females and 175 males, were selected. The performance of randomly selected participants in a language center placement test was analyzed by applying the GDINA model from R-studio packages, to detect Differential Item Functioning (DIF). Results of the study revealed DIF in some items since there is some bias in test items. The implication of this study is to provide meaningful interpretations of respondents’ attributes and improve teaching and learning by finding the strengths and weaknesses of candidates. For this purpose, the findings derived from the result of the study can raise the awareness of test developers in preparing unbiased items for the placement test, and at the same time, assist test-takers to become more critical of their English language achievements. It is also helpful for materials developers to become aware of developing materials free from bias.

Language testing and assessment has grown in popularity and gained significance in the last few decades, and there is a rising need for assessment literate stakeholders in the field of language education. As teachers play a major role in assessing students, there is a need to make sure they have the right level of assessment knowledge and skills to accomplish their duties as assessors. The present study sought to develop and validate an assessment literacy test. To this end, a thirty-five scenario-based Language Assessment Literacy Test (LALT) was developed based on the seven standards covered by the Standards for Teacher Competence in Educational Assessment of Students (1990). Construct validity of the test was investigated by collecting data from 168 Iranian EFL teachers. To investigate the validity of the measure, tests of reliability, item difficulty, and item discrimination were carried out. The test was then subjected to EFA (Exploratory Factor Analysis whose results showed a seven-factor solution for the test items. The implications of the study for EFL teachers, language testers, teacher trainers, and curriculum developers are discussed.

Cognitive diagnostic models (CDMs) have received much interest within the field of language testing over the last decade due to their great potential to provide diagnostic feedback to all stakeholders and ultimately improve language teaching and learning. A large number of studies have demonstrated the application of CDMs on advanced large-scale English proficiency exams, such as IELTS, TOEFL, MELAB, and ECPE. However, too little attention has been paid to the utility of CDMs on elementary and intermediate high-stakes English exams. The current study aims to diagnose the reading ability of test takers in the B1 Preliminary test, previously known as the Preliminary English Test (PET), using the generalized deterministic input, noisy, “and” gate (G-DINA; de la Torre, 2011) model. The G-DINA is a general and saturated model which allows attributes to combine in both compensatory and non-compensatory relationships and each item to select the best model. To achieve the purpose of the study, an initial Q-matrix based on the theory of reading comprehension and the consensus of content experts was constructed and validated. Item responses of 435 test takers to the reading comprehension section of the PET were analyzed using the “G-DINA” package in R. The results of attribute profiles suggested that lexico-grammatical knowledge is the most difficult attribute, and making an inference is the easiest one.