درخت حوزه‌های تخصصی

English proficiency as the content knowledge for English as a Foreign Language (EFL) teachers determines their instructional quality. However, previous studies have not focused on the significance of this knowledge in support of Teachers’ Technological Pedagogical Content Knowledge (TPACK) on technology adoption in teaching. Therefore, this study aims at finding out the correlation between TPACK and technology applications, and how technology applications link to teachers’ English proficiency levels. The study adopted a quantitative method, and the data were collected using two questionnaires in Likert scale, one for TPACK and another for technology application. Teachers’ English proficiency levels are determined using the content knowledge dimension of TPACK. The questionnaires were completed online by 74 English pre-service teacher graduates who had participated in a national teacher certification program involving real teaching practice. The data were analyzed using the Spearman correlation coefficient to determine the correlation between TPACK dimensions and technology adoption and ordinal logistic regression analysis to find out the effect of teachers’ English proficiency levels on technology applications. The results show that most TPACK dimensions correlate to technology applications with the level of correlations between 0.26 (weak) and 0.47 (moderate). English proficiency has been found to affect technology applications only among teachers who regularly used technology in teaching. Teachers with high English proficiency used technology in teaching 3.06 times more frequently than those whose English proficiency was low. Therefore, it is recommended that English proficiency development be inscluded in teacher professional development to ensure that teachers use technology in teaching 

This research paper delved into the critical issue of applying English as a Lingua Franca (ELF) assessment principles in local English language tests used for non-native English speakers in Iranian language institutes. A qualitative content analysis was made on 60 local tests, dissecting them into domains, dimensions, and rating rubrics to scrutinize their alignment with ELF assessment principles. The study unveiled that despite some alignment with ELF assessment principles, key aspects like local communicative context, intercultural competence, and linguistic diversity are often overlooked. In particular, writing and reading tests failed to fully reflect these principles, and listening and speaking assessments showed biases towards native English varieties. The study provides crucial insights for test developers to foster a more nuanced and accurate assessment of non-native English speakers' abilities. Moreover, it highlights the need to embed ELF principles into test construction, argues for broader assessment scopes and a focus on locally relevant tasks, and contributes to more equitable and contextually relevant English language proficiency tests by emphasizing linguistic diversity in assessment frameworks.

The main purpose of this study is to present and evaluate a model to execute successful On the Job Training Course for Iranian EFL teachers. In order to achieve the goal of the study, 441 teachers of different language institutes in several cities of Iran were asked to complete a self-made questionnaire which was designed based on some face-to-face interviews and observation documents of 26 teachers. As factor analysis was the most crucial concern of this study, the 43 items of the questionnaire were piloted on a sample of 147 EFL teachers. Regarding this matter, the scale in this study enjoyed having a sufficient communality value greater than 0.5 for 25 questions in the questionnaire out of 43 questions. Pearson’s correlation coefficient and structural equation modeling (SEM) were run to analyze the relationships among the components. The result revealed that the research model was in the domain of acceptance. The findings of this study can provide fruitful information for English teaching and learning stakeholders, educational policy makers, supervisors, and those involved in second language teacher education as well as English language teachers in EFL contexts.

Despite research on preservice teacher practicums, few studies have examined these experiences through a complexity theory lens to capture the intricate, dynamic interplay of factors involved. Addressing this gap, this qualitative case study explored the multidimensional influences shaping the practicum experiences of three preservice English as a Foreign Language (EFL) teachers in Vietnam. Using an in-depth case study design with semi-structured interviews and classroom observations, the study analyzed the participants' lived experiences across diverse school environments through the lens of complexity theory principles. The findings revealed complex interactions of student factors, curricular demands, resource constraints, and contextual influences shaping the preservice teachers' dynamic, self-organizing learning trajectories as they adapted to emergent needs. Notably, the pivotal role of context profoundly influenced pedagogical decision-making. The study's insights underscore the importance of teacher education programs providing contextualized support and learning opportunities to nurture adaptable, reflective educators responsive to complexity. This research contributes a nuanced complexity theory perspective on the multifaceted nature of preservice EFL teacher learning.

This study sought to identify the challenges and needs of TOEFL iBT candidates in achieving C1 level scores in the speaking and writing sections of the exam. To this end, the researcher employed a mixed-method approach to collect data from a population of 46 students, both male and female, between the ages of 22 to 30. The participants were enrolled in two TOEFL preparation classes at Universidad Nacional de Educación. The data were collected through a survey, class observations, and TOEFL speaking and writing mock tests, and were subsequently analyzed both qualitatively and quantitatively. The findings indicated that the participants encountered challenges in discussing unfamiliar topics fluently, struggled with producing language at the C1 level while employing a variety of grammar and vocabulary, and demonstrated reduced accuracy due to influences from their first language (L1). To address these challenges, it is recommended to offer a bridging course prior to exam preparation courses wherein the primary focus is devoted to enhancing candidates’ accuracy and communicative competence in discussing unfamiliar topics through corrective feedback. The findings of this study could offer valuable insights to TOEFL iBT test preparation instructors, enabling them to better understand the challenges students face and plan strategies to address these challenges effectively within preparation courses.

As one of the most prominent components of native-like language use, lexical bundles play a crucial role in academic texts. Considering the amount of written language produced by writers, this study explored lexical bundles in non-native and native academic reports. To that end, 100 sample reports of non-native and native writers taken from the Michigan Corpus of Upper-level Student Papers (MICUSP) were selected and analyzed to find non-native and native writers’ use of lexical bundles regarding frequency, structure, and function. Results indicated that native writers generally used a more extensive variety of lexical bundles in their reports. Regarding the structure of bundles, both non-native and native writers tended to employ more noun phrases with of-phrase fragments. In terms of the functions of bundles, both groups of writers tended to use more research-oriented bundles, followed by text-oriented and participant-oriented bundles, respectively. Findings highlight the value of fixed expressions in producing coherent academic texts by proficient writers, hence their importance in materials design and second language instruction.  

"English Language and Literature" courses are essential components of university education. They provide a significant avenue for understanding the politics, economics, and customs of English-speaking countries. These courses facilitate a mastery of English grammar, which in turn enhances students' comprehension of spoken and written English content. However, traditional modes of instruction in English Language and Literature often lack engagement and interactivity, thereby limiting the effectiveness of learning in this field. In order to boost learners' interest and efficiency in studying English, it is imperative to shift away from conventional teaching approaches. With the rapid advancement of artificial intelligence in various domains, its integration with English Language and Literature education can yield intelligent learning experiences. This study employs a combination of Convolutional Neural Networks (CNN) and Gated Recurrent Units (GRU) to reform the teaching model in English Language and Literature. The results indicate that CNN and GRU methodologies offer substantial support in realizing intelligent approaches to teaching this field. These methods exhibit a high degree of similarity and accuracy in predicting linguistic features in English Language and Literature. They excel in terms of predictive and scatter error distribution, showcasing superior performance.