درخت حوزه‌های تخصصی

This article examines the evolution of teacher education in Iran, with a specific focus on English language teacher training. Utilizing a qualitative analysis of historical documents, the study identifies six distinct periods in this evolution. The first period marks the foundation of teacher education with the establishment of the Dar al-Fonun School. The second period saw the formalization of teacher education through the Central and Higher Teacher Training Colleges. In the third period, teacher training expanded with the creation of Preliminary and Higher Colleges, focusing on multidisciplinary fields, including the French language. The fourth period introduced specialized programs, such as English language teaching, which replaced French. During the fifth period, teacher training centers reached their peak and then declined. Finally, the sixth period marks a shift in the educational system’s approach to teacher education, highlighted by the establishment of Farhangian University. Throughout these periods, English language teacher curricula evolved from classical and structural approaches to communicative and interactive methods. This shift not only highlights the changing pedagogical landscape in Iran but also underscores the need for curricula that better prepare teachers for contemporary classroom dynamics. The findings showcase the developmental trajectory of teacher education in Iran, emphasizing the need to address future challenges.

Discourse markers play a crucial role in textual cohesion and coherence. By identifying patterns of discourse marker usage, valuable insights can be gained into the underlying communicative strategies employed by text producers. Qur’anic discourse markers are of particular significance for several reasons, making their translation a critical area of study. Accordingly, this article aims to examine the second most frequent, complex, ambiguous, and multifaceted Qur’anic discourse marker, fa, in a Persian and English Qur’anic parallel corpus from a pragmatic perspective. To this end, six ajzā (parts) of the Holy Qur’an were randomly selected as the research sample and served as the source text of the corpus. The Persian translation by Ali Maleki and the English translation by Tahereh Saffarzadeh were chosen as the target texts through purposive sampling. The bilingual parallel corpus was designed to facilitate the investigation of variations and trends across the two languages, thereby providing a more in-depth understanding of the translation process. The analysis of this corpus revealed that translators rendered this Qur’anic meta-discursive component figuratively, communicatively, and dynamically by employing four different types and 81 unique discourse markers to establish various logical relationships between discourse units. These discourse markers conveyed discursive functions of contrast, elaboration, inference, and temporality. This figurative and communicative system, adopted and adapted in the construction of discourse, is substantiated through different theoretical perspectives in discourse analysis and pragmatics. Beyond its contribution to discourse analysis by highlighting the complexities of language use and the interpretation of sacred texts across languages, the study’s findings offer valuable insights for translators in general, and for Qur’an translators in particular, by shedding light on the intricate yet subtle process of discourse construction and its crucial role in facilitating more effective communication.

The study, which has been derived from a larger project, examined how effective ChatGPT, compared to human raters, is for scoring writing tasks when tasks were arranged from simple to complex or vice versa. In so doing, a correlational design was employed. The participants were 113 EFL learners. Two sets of writing tasks were customized based on the SSARC (simplify, stabilize, automatize, reconstruct, complexify) model. The participants were divided into two groups. They took a pre-test and did tasks in two different orders. The tasks were rectified by the researcher and returned to them later. The participants enhanced their text based on comments on tasks. After that, they took a posttest. Human raters and ChatGPT scored the pretests and posttests.  A Pearson Correlation test was run to obtain the correlation between a human rater and ChatGPT. The results indicated a strong positive correlation between scores assessed by human raters and those by ChatGPT when tasks were arranged from simple to complex (r = 968, p > 05) or complex to simple (r = 860, p > 05). These findings suggest that ChatGPT can be an effective tool for writing assessments. Suggestions for further research are discussed.

This research has been carried out with aim of designing a model for development of market share of Refah Kargaran Bank with approach of analyzing the competitive environment of Iranian banking. The current research is considered to be a type of mixed research in terms of its applied-developmental goal and in terms of its implementation. The statistical population studied in this research includes experts. To determine the sample size, the snowball method was used, and based on this, the sample size was selected as 25 branch managers of Refah Kargan Banks. In order to analyze the quantitative data in this research, descriptive and inferential statistics were used. The findings showed that use of customer relationship management policies (need assessment, responsiveness, satisfaction and loyalty) had the most impact on increasing the market share of Refah Kargaran Bank with coefficient of 0.8425 and support and facilitation services of Refah Kargaran Bank were also It has taken the last place with a proximity coefficient of 0.4449. Based on results of research, proposed model presented by connecting and creating integration in effective themes in competitive environment will lead to the creation of coherent, comprehensive and coordinated cycle of the performance of each element in activities of Refah Bank.