درخت حوزه‌های تخصصی

This study aimed to examine the effects of a teacher education course on EFL teachers’ self-efficacy in formative assessment. The researchers employed a mixed-method design that combined quantitative and qualitative approaches to investigate the effects of the course. Thirty EFL teachers participated in the study and completed pre- and post-intervention questionnaires to assess their formative assessment self-efficacy beliefs. In addition, semi-structured interviews were conducted to gather qualitative data on teachers’ beliefs about formative assessment. The quantitative data were analyzed using paired-sample t-tests, and thematic analysis was conducted for the qualitative data. The results indicated a significant increase in teachers’ formative assessment self-efficacy beliefs. The findings suggest that providing teacher education courses focused on formative assessment can effectively enhance EFL teachers’ self-efficacy and utilization of such assessment methods in online classroom. The current study has some pedagogical implications and recommendations for the implementation of similar courses and potential areas for future research are also discussed.

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.

The application of comprehension skills as a general cognitive ability has long been discussed in the literature on second language reading comprehension. To trace second language reading comprehension difficulties back to the text or reader attributes, the present study investigates the optimum load of linguistic and non-linguistic components of second language reading ability. The study followed a quantitative method of research, and the data were collected on the performance of 164 Iranian foreign language learners with different educational backgrounds. A group of Teaching English as a Foreign Language (TEFL) experts provided feedback on the specifications of the sample test items based on the Comprehensive Taxonomy of Reading Sub-skills (CTRS) derived from major taxonomies in the literature. Applying exploratory factor analysis and correlational computations, the results revealed that although the items were all convergent to measure the same latent construct, items aimed at measuring general cognitive comprehension skills had more contribution to the overall test scores. Teachers at both language institutes and ministry of education, test developing organizations, and students who seek to gain more success in reading comprehension examinations can benefit from this study feedback.

This article performs a CDA on White House press briefings and is especial in its focus on how gendered language impacts relations of power. Adopting a mixed-method approach, this study will examine linguistic strategies and deictic expressions used by male and female spokespersons articulating ideologies and constructing authority. The latter is based on Fairclough's three-dimensional CDA model, whereby text analysis is involved, together with discourse practices and social context in explaining how language reflects and constructs political realities. The research questions were as follows: (1) How are deictic expressions used by spokesmen and spokeswomen in the White House press briefings? (2) What is the inter-relationship between power and language through the usage of modal verbs, and is there a gender-based difference herein? (3) How do women spokespersons, through language, claim ideologies and power? It is a contribution to applied linguistics and presents evidence of subtle linguistic mechanisms that shape public perception of gendered language in political discourse. The research questions were as follows: (1) How are deictic expressions used by spokesmen and spokeswomen in the White House press briefings? (2) What is the inter-relationship between power and language through the usage of modal verbs, and is there a gender-based difference herein? (3) How do women spokespersons, through language, claim ideologies and power? It is a contribution to applied linguistics and presents evidence of subtle linguistic mechanisms that shape public perception of gendered language in political discourse.

Hot and humid climate is one of the robust climates in the world. Vernacular architecture in this area answer to climate conditions with solutions, one of these solutions are windcatchers. Nowadays most of these windcatchers are closed because they are not responsive to current thermal comfort conditions. The reduction of wind speed and the lack of control over the entering hot weather can be considered as two main weaknesses of the windcatchers in these areas. This research suggested to install Damper and Fan to improve the performance of windcatchers in vernacular houses of Bandar-Kong. five windcatchers have been selected as case studies and their performance has been simulated and measured in 24 different modes: open windcatcher (past method), closed windcatcher (current state), windcatcher with valve and windcatcher with fan are four general modes wich are divided to 6 subset. Design Builder 7.0.0.116 is used for simulations. operative temperature is calculated for each space in 24 different modes. The results show that using fan and damper, increase thermal comfort hours from about 43 to 52 percent. Besides using fans and dampers can obviously reduce temperatures over 35degrees.

The Arg or Toopkhāneh Square was an essential part of Karim Khān's citadel complex in his new capital, Shīrāz, Iran, in the mid-18th century, which was destroyed in the early 1920s. However, the studies conducted regarding its form and functions have not been accurate enough, and their hypotheses are inconsistent with reality. This paper calls into question previous studies and takes a new look at the design, geometry, and spatial relations of the Square in the days of the Zand dynasty (17511794) and studies the changes of the Square in the Qājār (1789-1925) and Pahlavi (1925-1979) eras. This study analyzed European travelogues and historical photographs with little existing evidence by applying a historical research method. The study revealed that the Arg, later named Toopkhāneh Square, was rectangular, about 130 by 185 meters, with an east-west orientation. The Arg square and its adjacent buildings should be considered a governmental-military open space with various internal relations. The architecture of the main gate and the Naqqāra Khāneh mansion were the prominent features of this Square, and its location has always been questionable. The previous studies did not have a correct understanding of the location of the Naqqāra Khāneh, the number of entrances to the Square, the height of the walls of the Square, as well as its layout. Finally, it is crucial to notice that The design of this Square differs from the example of Naqsh-e Jahan Square in Safavid Isfahan and Toopkhāneh Square in Qājār Tehran.

The current research was conducted with the aim of providing a sustainable marketing model in the insurance industry with a focus on artificial intelligence. According to the type of data, the research method is mixed (qualitative-quantitative) of exploratory nature. In the statistical population, 12 people were selected from among the experts until the theoretical saturation was reached. The experts included professors of the faculty of business management and senior managers of Alborz insurance company, who were selected by non-probability, targeted and chain sampling. Quantitative part of 400 managers were insurance industry experts, using Cochran's formula, 196 people were selected by stratified random method. To collect data, semi-structured interviews and researcher-made questionnaires were used. The analysis method has been carried out in several consecutive steps. In the first stage, to identify the components of the model, the qualitative method and semi-structured interviews using the grounded theory have been used. In the next section, using interpretative structural modeling, the identified indicators were leveled. Finally, in order to fit the designed model in the qualitative part, a quantitative method with structural equation modeling approach was used with PLS4 software. The findings showed that 6 components were identified and there is a significant relationship between all components and sustainable marketing and the designed model has an acceptable fit. It can be concluded that AI can be incorporated as an essential component of a sustainable marketing strategy, enabling marketing professionals and businesses to make positive changes while increasing their brand reputation and profitability.

The present study aims to examine the relationship between cost stickiness and conservatism levels according to the type of industry. This purpose is achieved using the combined data technique and three models of non-operating accruals, the Basu model, and the market value model with a sample consisting of 113 companies listed on the Tehran Stock Exchange (TSE) over the period 2011 to 2020. Findings show that based on the model of non-operating accruals in the automotive, pharmaceutical, chemical, and food industries, cost stickiness decreases the level of conservatism. However, in the machinery industry, the relationship is significantly based on this model, but cost stickiness does not reduce the level of conservatism. According to the Basu model in the chemical, food, and basic metals industries, cost stickiness reduces the level of conservatism. But in the pharmaceutical industry and machinery and equipment, there is a significant relationship according to this model, but cost stickiness does not decrease the level of conservatism in companies. Also, based on the market value model in the automotive, chemical, machinery, and basic metal industries, there is a significant association, but cost stickiness does not decrease the level of conservatism in companies.

This study investigates the relationships between Bitcoin (BTC) prices and fluctuations in relation to gold, USD, and Iran's oil prices from 2019 to 2022. We employed the dynamic conditional correlation generalized autoregressive conditional heteroscedasticity (DCC-GARCH) method to model the fluctua-tions of financial variables. Additionally, the smooth transition regression (STR) method was applied to explore the relationships between the variables. The results reveal significant positive correlations between BTC prices and gold, as well as oil, and a negative correlation with USD prices. We observed volatility persistence, causality, and phase differences between BTC and other financial instruments and indicators. Notably, a negative relationship was identified between Bitcoin and the USD in both linear and non-linear aspects, with a larger coefficient in the second regime. Furthermore, a posi-tive relationship was found between Bitcoin and the variables of gold and oil prices, with coefficients being larger in the second regime compared to the first.

The desirability of the financial reporting can greatly help the users of finan-cial information in making investment decisions. The purpose of this re-search is to measure the readability of financial reporting using a multi-indicator decision-making model and the artificial neural network method and the role of information presentation time in its improvement. In this research, various indicators have been used to measure the readability of financial reporting, and the quality of reporting is obtained through the rank-ing of companies by the stock exchange. In this research, the number of 149 companies admitted to the Tehran Stock Exchange in the period of 2010-2020 was examined, and to measure the financial readability through struc-tural equations and Stata software, and to test the hypothesis of the research, the regression model and Eviews econometrics software were used. In this study, we have tried to Use machine learning techniques and optimization tools as a way to derive adaptive-robust nonlinear models that can reduce the risk of model error as much as possible. The findings of the research show that the time of providing information has an impact on the readability of financial reporting. The obtained outputs from the estimation of the artificial neural networks and results obtained from estimation, using of this method with evaluation scales concerning random amount and comparing it with adjusted R, we found that there is meaningful relation between the associated variables and return. However, such network has the least error than other networks. The results show an overall improvement in forecasting using the neural network as compared to linear regression method. In other words, our proposed system displays an extremely higher profitability potential. The obtained result can be argued that the more the company's information is provided by the managers to the company's shareholders and investors on time and at the right time, the more readable and understandable the financial reports will be.

The increased number of restatements in recent years has increased the wor-ries about the quality of financial reporting among the beneficiary groups. The pres-ence of prior period adjustments and, subsequently, the financial restatements have a negative impact on the relatedness and reliability of the financial state-ments. The present study is aimed to present an appropriate criterion for predict-ing the financial restatements based on the Beneish model and its indices in companies admitted to the Tehran Stock & Exchange between 2009 and 2020. For this purpose, a total of 265 companies were selected considering the limitations. Also, the model estimation was per-formed using Beneish's primary model, a meta-heuristic neural network model, and optimization through genetic programming. As indicated by the obtained results based on the confusion matrix, the efficiency of the pro-posed model derived from the enhanced Beneish model with a genetic algo-rithm had a total prediction accuracy of 73.21%, which was the highest prediction power compared to the Beneish Model .

A strong brand differentiates the product from competitors' products, reduces search costs, minimizes perceived risks, and offers high quality from the customer's point of view. He considered that one of the most important problems of Iran's food industry is related to the brand name, especially in the field related to the internalization of awareness and association of the brand name in the customer's mind. Cognitive distortions, as psychological factors that cause perceptual errors in people, can be effective in their negative feelings and, as a result, affect the expected results of customers' behavior; Therefore, identifying the psychological components of branding in the food industry with the foundation's data approach (case study: Gaz Asari) is of great importance. The method of this research is qualitative and grounded theory method (foundation data) which has been used in this research due to some of its special features. The statistical population consists of interviews with 17 people, including all managers and expert managers in the Gaz Asari brand industry, which means analyzing the data obtained from the interviews, using the qualitative-inductive grounded theory method (including the steps of open coding, central coding, and selective coding). The results include 19 general categories in the form of a paradigm model, which include causal conditions (competitive pressure, changing customer characteristics, market uncertainty, understanding the importance of branding and lifestyle changes), central phenomenon (psychological branding), background conditions (sustainability of brand effects) flexible characteristics of the brand and branding skills, intervening conditions (customer, company capability, brand competition capacity and the challenges of Sanat Gaz administration) and strategies (differentiation strategy, modeling strategy, discovery strategy, and resistance strategy) and consequences (short consequences duration and long-term consequences).

With the aim of comprehensively investigating the most important consequences of website quality in e-commerce, this research has collected and analyzed data about the relationship between website quality and customer trust, satisfaction, and loyalty. In this regard, various studies were collected and coded. After that, the eligible studies to enter the meta-analysis based on the determined criteria were identified to be 49, 68, and 29 studies for the relationship between website quality and trust, satisfaction, and loyalty, respectively. The findings of data analysis using CMA2 software showed that website quality has the strongest relationship with satisfaction with an effect size of 0.591 and the weakest relationship with loyalty with an effect size of 0.516. The effect size of trust was also positive and equal to 0.555. In addition, the findings from the analysis of moderator variables also showed that an increase in the year of publication led to a decrease in the effect size of website quality-trust studies but an increase in the effect size of website quality-satisfaction and website quality-loyalty studies. Additionally, with an increase in the sample size, the effect sizes of website quality-trust studies increased, but the effect sizes of website quality-satisfaction and website quality-loyalty decreased.

In this paper, we present a comprehensive approach for evaluating efficiency in complex networks by integrating network data envelopment analysis (NDEA) with the Malmquist productivity index. The proposed method addresses the inherent challenge of accommodating negative data within the network efficiency evaluation framework, which is a common occurrence in real-world network operations. Through the introduction of a two-stage structure, the model not only effectively manages the presence of negative values, but also provides a robust and insightful assessment of network efficiency. A case study from banking sector is employed to demonstrate the efficacy of the proposed approach, showcasing its capacity to offer valuable and actionable insights for decision-making in complex network environments. The results highlight the practical applicability and importance of the extended approach in addressing the complexities associated with evaluating efficiency in diverse network settings.

Rural tourism, with careful planning, can enhance the quality of life and create economic, social, and cultural benefits. The aim of this research was to present a sustainable rural tourism model with a focus on social capital. The research was applied in terms of its goal and qualitative in terms of methodology, based on the foundation data theory. The research was framed using a cognitive approach, utilizing various data collection methods such as library research, examination of specialized sources and texts, as well as semi-structured interviews. Fourteen elites, experts, and managers in tourism and rural area management were interviewed in 2023. The conducted interviews were coded using Atlas .t i software.

The purpose of this research is to select the best energy supply methods for blockchain technology and to optimize the use of each of the selected methods.For this purpose,a two-part hybrid approach based on best-worst multi-criteria decision making methods,VIKOR method and mathematical programming model has been used under uncertainty conditions.To implement this approach,first by reviewing the literature,the effective criteria in selecting the best method were extracted and then,the options or energy supply methods using blockchain technology were determined based on the experts’ opinion.Finally,the weight of the criteria and the final ranking of the selected options were determined by the best-worst and VIKOR methods, respectively.In the second part,in order to determine the optimal amount of using available facilities for blockchain technology to implement the selected method,a robust mathematical model is designed in which the NPV criterion is used as an economic evaluation measure of using the selected method in the first part. was taken As the obtained results show,the criteria of "implementability"and"productivity level"and"coordination with consumption pattern correction policies"have the highest level of importance with the weight of 0.339, 0.14and 0.14, respectively,in order to choose the best option.Also, the best score compared to other options belongs to the energy supply method"electricity generation from the combined use of national grid and solar panels".Solving the mathematical model shows that the highest level of economic efficiency belongs to the use of solar panels to provide a significant part of the need for power.

This research tried to probe the effects of incorporating learners’ preferred learning styles in instructions on their narrative writing development and their mental patterns and imagination. 74 homogeneous secondary EFL learners were divided into three groups based on their sensory styles of visual, auditory and tactile. The learners in the three groups were provided with instructions anchored to their learning styles. In the meantime, they were required to produce narrative writings on a number of topics in accordance with their course book. Prior to narrating, they had to think loudly and record their voices to reveal the approach and pattern they utilize for performing the required activities. Their voices were transcribed and later analyzed by the researchers for further investigations. The obtained results displayed a significant improvement in their writings as well as an ongoing progress of their thinking patterns. Furthermore, the data revealed the dominant mental approaches of top-down, considering the whole plot of the topic in advance, and bottom-up, considering the details prior to the entire story, used by the students. The study also displayed the positive impact of instruction on the improvement of learners’ narrative writing revealing their self-imaging of the plot with which they could narrate the given topics in accordance with their own life experiences and understanding.

In recent years, attention to environmental education especially in rural environments has attracted the attention of many educational experts. The aim of the present study was to investigate the experiences of teachers in relation to environmental education in rural schools. To serve that end, a qualitative approach and phenomenological method were used. Consequently, unstructured interviews were conducted with 13 teachers using the purposeful sampling method. To analyze the data, thematic analysis was used. The analysis of the interviews revealed three main themes (regressive approach, progressive approach, and indifference approach), 13 sub-themes, and 31 refined themes. The findings of the research indicated teachers' lack of real involvement in environmental education, lack of trust in the efficiency of environmental education, absence of employing of new methods, superficial knowledge about the environment, and absence of attempts to use new methods in education. It is concluded that teachers play a significant role in environmental education, so training and preparing them can improve environmental education.