درخت حوزه‌های تخصصی

This research aims to develop a questionnaire that measures students’ attitudes toward collaborative course design and identifies any barriers that might hinder student participation in course design. The questionnaire was developed in four phases. First, an item pool was created based on experts’ opinions, relevant literature, and the researchers’ experience. Second, the items were classified into two main sections: “attitudes” and “barriers”, with the latter further divided into five subcategories (social and cultural, educational and institutional, individual, practical, and attitudinal). The content validity of the questionnaire was assessed, with all items and subcategories achieving CVR>0.59 and CVI>0.79, thus surpassing the minimum required threshold. Third, the questionnaire was piloted with 330 students. The construct validity of the Collaborative Course Design Questionnaire (CCDQ) was confirmed through exploratory factor analysis (EFA) using Principal Component Analysis (PCA) as the extraction method, along with Varimax rotation, which identified six factors explaining 71.536% of the variance in the data. Finally, Cronbach’s alpha was calculated, yielding reliability indices ranging from 0.971 to 0.627, indicating internal consistency and reliability of the items within each construct. The findings suggest that the Collaborative Course Design Questionnaire is a valid and reliable instrument suitable for use with senior high school students.

This study addresses a critical need for effective curriculum alignment in higher education, particularly within Teaching English as a Foreign Language (TEFL). As educational institutions strive to enhance the quality of their programs, understanding the interconnections between intended, enacted, and assessed curricula becomes essential. This study examined the alignment among these curricula in the TEFL B.A. program at Shiraz University. Drawing on Anderson and Krathwohl's (2001) taxonomy of educational objectives, the researchers employed a mixed-methods design to analyze the cognitive processes and knowledge types in the curriculum standards, course content of instruction, and achievement tests of language teaching methodology, language testing, and linguistics courses. The qualitative content analysis revealed a notable overemphasis on lower-order thinking skills (LOTs) across all components of the courses studied. Specifically, the presence of higher-order thinking skills (HOTs) was quite limited within the curriculum standards, course content of instruction, and achievement tests. The quantitative analysis, using Porter's (2002) alignment index, further demonstrated a significant alignment (0.50) between the curriculum standards and achievement tests, but an insignificant alignment between the course content of instruction and the other two components. The findings highlight the need for policies that foster HOTs and support professional development for TEFL instructors. Educators should clarify learning objectives and align tasks with students' cognitive needs, thereby enriching TEFL curriculum design. The results advocate for integrating HOTs across the curriculum while ensuring alignment between intended, enacted, and assessed curricula. This study also contributes to ongoing research on curriculum design and implementation in TEFL higher education.

The study investigates the popularity, language use, and food menu naming of Thai cuisine on international social media by analyzing 210 Thai food dishes from Allrecipes, a leading cooking and recipe website. Data were categorized to identify popular dishes and the top six food groups were found: curry, Pad Thai, soup, sauce, rice, and noodles. Curry dishes, particularly green and red curry, are the most popular followed by Pad Thai and soups like Tom Kha Gai and Tom Yum. Thai food names are predominantly translated into English with additional descriptors. English transliterations are used for iconic and national dishes like Pad Thai and Tom Yum, reflecting a global preference for accessible names. A free program called HK Coder was employed to analyze the data, determine word frequency, and identify keywords. The linguistic analysis revealed frequent terms such as "Thai", "chicken", and "curry" highlighting the significance of national identity and key ingredients of Thai cuisine. Remarkably, a less traditional dish ‘Peanut Butter Noodles’ also received high ratings as a popular dish, indicating a blending of Thai flavors with Western preferences. The study provides insights into how Thai food is perceived and adapted internationally, contributing to the understanding of cross-cultural culinary exchanges.

The present study explored the effectiveness of Google Docs as a cloud-based technology in enhancing the complexity, accuracy, and fluency (CAF) facets of writing competence. Forty-nine Iranian EFL learners, majoring in English, from two intact classes participated in the study. The classes were randomly assigned to the Google Docs (GD) group and the Conventional Teaching group (CT) after their proficiency levels were identified. The GD group (n=25) used the Google Docs writing instruction platform, while the CT group (n=24) received traditional writing instruction. Furthermore, ten students from the Google Docs group participated in semi-structured interviews to express their perceptions of the treatment they received. A mixed-methods design, incorporating Multiple Analysis of Covariance (MANCOVA) and theme-based analysis, was employed to assess quantitative and qualitative outcomes. The findings indicated that the GD group demonstrated a significantly improved ability in CAF writing compared to the CT group. The interviews revealed several important themes, including the positive experiences associated with collaborative writing through Google Docs, the convenience and flexibility of real-time collaboration, and the effectiveness of peer support in enhancing writing competence. Additionally, the teacher’s role as a facilitator was found to be crucial. Overall, the results suggested that the interactive attribute of Google Docs, combined with peer correction and editing, noticeably supports more sophisticated and accurate writing skills.

This study aims to analyze the factors associated with motivation and attitude towards English learning through the application of structural equation modeling (SEM). A quantitative, ex post fact, cross-sectional and explanatory study was carried out on 1202 university students. Eight motivational factors were examined, namely: Motivational Intensity (MI), Attitude towards Learning English (ATLL), Integrative Orientation (IntO), Instrumental Orientation (InsO), Interest Towards Foreign Languages (ITFL), Evaluation of English Teaching (EET), Desire to Learn English (DLE), Evaluation of the English Course (EEC). The multiple regressions showed that EET, DLE, InsO, and EEC are predictors of the MI. It was found that DLE, InsO, and EEC are predictors of ATLL. The SEM showed a weak positive influence of InsO on DLE, ITFL, EET, EEC, MI and ATLL. IntO had a weak positive impact on DLE, EET, EEC, and ITFL. There was a weak positive impact of DLE on ITFL, ATLL and MI, and it had a strong effect on EEC. Finally, EET had a weak positive effect on MI, whereas EEC had a weak positive impact on ATTL and MI. This research provided information that serves to understand the factors affecting the intensity of motivation and attitude in L2 learning

Various articles have addressed the field of audiovisual translation and its related issues, but the pragmatic aspects of this area have not been addressed as they should be. As pragmatic issues are mainly covert in dialogues, and films are dialogue-oriented, it is crucial to consider these aspects in this area. Implicature is one of these hidden aspects of meaning which challenges the translators’ knowledge and competency. Sometimes ignoring this pragmatic aspect results in misinterpreting the intended meaning of the original version, whether it is a text or a film. Therefore, the present study intends to examine the translation of implicatures and their intricacies in Persian dubbing. To this end, four American films (Notting hill, The bucket list, The ultimate gift and Still Alice) were selected, all of which had been dubbed into Persian. All parts of these films were analyzed to determine whether there is any mismatch between original and dubbed versions in terms of this pragmatic aspect. The translation techniques and their frequency of occurrences which were applied to translate this pragmatic aspect are illustrated too. The results indicate that there are mismatches between the original and dubbed versions in terms of implicature, and the most frequent number of mismatches refers to scalar implicatures. Conventional and conversational implicatures follow it respectively. Moreover, deletion is the most frequent translation strategy which was applied to render this pragmatic aspect.

This study examined the impact of AI-driven feedback on the writing complexity of Iranian intermediate EFL learners using a quasi-experimental design. Through convenience sampling, 100 participants (male and female, aged 18-25) from two language institutes in Tehran were divided into four groups: two experimental groups receiving direct and indirect feedback from AI ChatGPT, and two control groups receiving the same feedback types from their teacher. Participants completed a pre-test, ten writing tasks over 14 weeks, and a post-test. Results, analyzed via descriptive statistics and one-way ANOVA, indicated notable improvements in writing complexity across all groups. The AI direct feedback group showed the highest improvement, with a mean difference of 5.24 (p < 0.05), followed by the teacher direct feedback group, which also demonstrated significant gains. The AI indirect feedback group exhibited moderate progress, while the teacher indirect feedback group showed the least improvement. Analysis of syntactic measures revealed that AI feedback, particularly direct feedback, effectively enhanced sentence structures and encouraged the use of more sophisticated vocabulary. These findings highlight AI-driven feedback’s potential to enhance EFL learners’ writing complexity, with direct feedback yielding the greatest benefits.