مطالب

Scientific thinking is a type of knowledge seeking involving intentional information seeking, including asking questions, testing hypotheses, making observations, recognizing patterns, and making inferences. The purpose of this research was designing a package of scientific thinking training and its ‘effect on problem-solving skill in preschool children. For this purpose, a study was designed in two steps. At first time, based on Kuhn theory and by reviewing and analysing available resources, the scientific thinking training package was designed. This teaching package includes discussions between the researchers and the child about stories with topics related to children's environment that they may not have encountered in everyday situations in the form of questions. At second step, in order to determine the effect of scientific thinking training on problem-solving, 30 children aged 5 to 6 (15 girls-15 boys) with a moderate score in Raven intelligence test was chosen from three primary schools. Subjects were trained individually in scientific thinking for 8 sessions. Data were analysed using repeated measures analysis of variance. Findings showed that teaching scientific thinking significantly improves problem solving skills (p <005) and this effect is stable over time. The results of this study show that preschool education and interaction with teacher is an opportunity to provide stimulus situations appropriate to children's abilities, and provide conditions for improving problem-solving.

The purpose of study is Identifying the factors affecting the establishment of "quality culture" and effective factors in the quality of virtual education of Farhangian University.The research method was a two-stage combined exploratory exploration. In the qualitative section, using a semi-structured interview technique, 23 academic and thematic experts were interviewed in a purposeful manner from educational and research centers and the research method in the qualitative part is foundational data theorizing, which seeks to create a theory, model and pattern (Sharmaz, 2007: 462),. A descriptive-survey method has been used in the quantitative part. To analyze the data in order to evaluate the fit of the proposed model from confirmatory factor analysis and structural equation modeling technique by using Smart PLS software. In the quantitative part of research, the initial structure of questionnaire which was compiled with 136 items, in the initial study among five quality monitoring and evaluation experts at Farhangian University. The information obtained from the examination the indicators of each of dimensions and indicators of the quality culture using the criteria of the absolute magnitude of the factor loadings, T-statistics and R2, it should be said that all the items have a suitable factor loading (above 0.7) on the related variable. And these factor loadings were significant at 0.05 and 0.01 levels. In other words, the value of t associated with each factor load is greater than its critical value (1.96) at the 0.05 level and (2.58) at the 0.01 level. Then, in the quantitative section, 389 faculty members and non-faculty members were selected by multi-stage cluster sampling and answered the questionnaires. Findings from first and second confirmatory factor analysis showed that culture quality of factors; "Structural / managerial elements"(0.388), "Cultural/ psychological elements" (0.248), "Leadership" (0.500), "Communication" (0.584), "Trust"(0.457), "Commitment"(0.150) and responsibility"(0.528),"Participation"(0.176), "Empowerment"(0.312), "Infrastructure reform"(0.161), "Results of quality culture"(0.458) has been formed and its native model has a suitable structural validity for establishment in Farhangian University. As a result, it can be said that the structural model under study is of good quality and the observed values are well reconstructed and the model has a good predictive ability.

Accurate traffic classification is important for various network activities such as accurate network management and proper resource utilization. Port-based approaches, deep packet inspection, and machine learning are widely used techniques for classifying and analyzing network traffic flows. Most classification methods are suitable for small-scale datasets and cannot achieve a high classification accuracy owing to their shallow learning structure and limited learning ability. The emergence of deep learning technology and software-driven networks has enabled the application of classification methods for processing large-scale data.In this study, a two-step classification method based on deep learning algorithms is presented, which can achieve high classification accuracy without manually selecting and extracting features. In the proposed method, an Autoencoder was used to extract features and remove unnecessary and redundant features. In the second step, the proposed method uses the features extracted by the autoencoder from a hybrid deep-learning model based on the CNN and LSTM algorithms to classify network traffic.To evaluate the proposed method, the results of the proposed two-stage hybrid method is compared with comparative algorithms including decision tree, Naïve Bayes, random forest. The proposed combined CNN+LSTM method obtains the best results by obtaining values of 0.997, 0.972, 0.959, and 0.964, respectively, for the evaluation criteria of, accuracy, precision, recall, and F1 score.The proposed method is a practical and operational method with high accuracy, which can be applied in the real world and used in the detection of security anomalies in networks using traffic classification and network data.

The present study aimed at exploring the predictive validity of achievement goals for EFL university students’ attainment emotions, and academic success in the context of Iran. To this end, 440 EFL university students responded to the relevant instruments. The results revealed that learners’ mastery-approach, mastery-avoidance, and performance-approach goals were significantly positively correlated with positive attainment emotions, and negatively associated with negative attainment emotions. Furthermore, EFL learners’ performance-avoidance goals were significantly negatively associated with their positive attainment emotions, and positively related to their negative attainment emotions. Additionally, EFL learners’ mastery-approach, performance-approach, and performance-avoidance goals were significant predictors of all attainment emotions, while EFL learners’ mastery-avoidance goal was a significant predictor of their hope, anger, and hopelessness. Besides, EFL learners’ achievement goals significantly correlated with their academic success. Finally, all achievement goals predicted students’ academic success, and also mastery-approach goal was the strongest predictor of students’ academic success. The results can benefit EFL teachers, and learners to grasp a better picture of the association between achievement goals and attainment emotions, and academic success of EFL students in the context of Iran.

Enhancing one's proficiency in English grammar represents a foremost objective for individuals who are learning a foreign language. In EFL contexts, it is commonly observed that children tend to acquire knowledge of grammar rules incidentally, whereas adults usually require formal instruction to attain a more advanced level of proficiency. Numerous contemporary approaches have undergone substantial investigation, yet comparatively limited emphasis has been placed on the acquisition of grammar learning strategies. This article investigates the perspectives of learners with regards to the utilization of grammatical learning strategies during the duration of an English language course. This research centers on the cognitive and affective viewpoints of individuals participating in a grammar study group. The objective of the research is to investigate the utilization of specific strategies by learners for the acquisition of varied grammar structures. Novel methodologies and empirical investigations have the potential to enhance the comprehension of the educational process and self-regulation. The aforementioned holds the possibility of significant repercussions for individuals engaged in the English as a Foreign Language (EFL) learning process, educators facilitating such learning, and professionals responsible for designing EFL curricula.

While Iran was never formally colonized by Western powers, it’s governing regimes before the Islamic revolution were loyal to both the East and the West;  the country was therefore more or less a de facto colony of Russia, Great Britain, and the United States. One of the most pernicious consequences of such presences can be described as the "colonization of the mind," which has subtle and lasting manifestations. Using Edward Said's four major characteristics of Orientalism (i.e., binary opposition, over-generalization, fear and control, and depicting the Orient as stuck in past primitiveness), the present paper attempts to analyze the self-perception of the Iranians toward themselves to see whether the way they perceive themselves is similar to the Western discourse of the "Orient." In the first step, a number of interviews with a representative sampling of the population under investigation were conducted to develop a questionnaire. The questionnaires were then distributed and 650 responses were collected. The survey was meant to assess the four components of Orientalism as proposed by Said, among the respondents. It also contained questions about the respondents' lifestyle, their perceptions toward nationalism, and media consumption. The results reveal evidence of Orientalist self-perception among the Iranians when they compare themselves with the West.

Ziba Mir-Hosseini employs feminist theory and global human rights principles to promote and implement legal changes to Islamic law to achieve gender equality. She proposes the pursuit of an alternative “sacred spiritual project” as a means to advance gender equality through these legal reforms.To achieve this goal, four underlying assumptions inform her work that are essential for her spiritual project to be successful. (Mir-Hosseini's approach includes: 1) Advocating religion's adaptation to societal changes, prioritizing individual autonomy over religious demands. 2) Applying social constructionism to challenge binary gender concepts and traditional roles. 3) Asserting that Orientalism influenced male scholars' misinterpretation of Islam's sacred texts. 4) Embracing Western individualism to counter Traditionalist or Neo-Traditionalist Islamic teachings while overlooking Western women's sexualization experiences in her pursuit of equality. The possible consequences of her philosophy include that it might aid secularization and syncretic tendencies within the sphere of Muslim women; it might emphasize a personal interpretation of religious texts leading to distrust of male authority; it might intersect with evolving attitudes towards gender roles, family dynamics, and women’s rights within society, which may affect Muslims and their families as a whole. It might contribute to tensions already there among women.

Previous studies have demonstrated the efficacy of speech rhythm measures in speaker identification across various languages with different phonotactic structures. In Persian language, in particular, two categories of speech rhythm metrics were examined: duration-based and intensity-based metrics. Building upon these prior works, the current study delves deeper into the discrimination capabilities of the mentioned measurement types—duration-based versus intensity-based—in the context of Persian speakers. To achieve this, a multinomial logistic regression model was employed on a dataset comprising 20 male Persian speakers, each reciting 100 sentences at a normal speaking pace. Findings revealed that, when distinguishing between Persian speakers, duration-based measures outperform intensity-based ones, however, this excellence is very slight. This observation is significant, as it sheds light on the suitability of specific rhythm metrics for Persian speaker identification. I postulate that this discrepancy in performance may be attributed to the simple syllable structure of Persian and the lesser reliance on intensity as a primary indicator of lexical stress. This research contributes valuable insights into the choice of rhythm metrics for optimal Persian speaker identification and underscores the importance of considering linguistic features when developing speaker recognition systems.Top of Form