درخت حوزه‌های تخصصی

This study attempted to determine the effect of background music while silent reading on Iranian EFL learners’ reading comprehension. The participants were 57 Iranian EFL learners between the ages of 14 and 16 in two 3rd grade high schoolclasses at pre-intermediate proficiency level. Before treatment,both experimental and control groups took a reading comprehension pretest. In the experimental group, the researchers played Mozart sonatas as background music and asked them to read the passage silently and then answer the reading comprehension questions. In the control group, the procedure was the same, but no music was played while silent reading by the students. After ten sessions, the students of both groups were asked to answer another independent but parallel form of reading section of PET as their post-test. The independent samples t-testresultsindicated that the experimental group outperformed the control group in reading comprehension posttest, and listening to background music while silent reading had a significantly positive effect on Iranian EFL learners’ reading comprehension. The results of the present study have implications for EFL students, teachers, and teacher educators as well as syllabus designers and materials developers.

Throughout the evolution of humanity, various factors have influenced human life, enhanced its quality and sometimes posed threats. One could argue that humans have experienced nomadism, urbanization, and the industrial revolution, as well as technological transformation throughout the evolution of their lives. Just as the advent of machines transformed the face of cities, today, the in-troduction of technology and virtual services has revolutionized them. The theory of smart cities, based on information and communication technology, attempts to intelligently transform various layers of the city in order to address current problems and improve the quality of life. Despite the numerous advantages of smart cities, their implementation is considered challenging and complex. Many cities face failure in implementing smart cities. Therefore, a deep and systematic evaluation of influential factors becomes essential. This research aims to evaluate smart city policymaking in Tehran. The study employs an analytical and exploratory method to assess questionnaire questions on a Likert scale with a minimum score of 1 and a maximum score of 5. To determine the reliability and internal consistency, Cronbach's alpha coefficient is used. The research findings indicate that all the strategies and actions examined in this study, from the perspective of experts (specifically, the formulation and implementation of integrated policies, legislation, and a unified vision), are highly important for the smartification of Tehran. This article adopts a conceptual approach, fram-ing the necessary framework for creating smart cities in observed changes in management style. With theoretical inferences from the sociology of change and the theory of the network society, good urban governance is proposed as a causal condition for creating a smart city in Tehran. The implementation of a smart city necessitates a change in the institutional and managerial structure of the urban system.

Objective : This study tackles the reviewer assignment problem by proposing a model that optimizes reviewer-proposal matching based on thematic coverage, fairness, and expertise, while considering workload balance and team size constraints. The model incorporates practical constraints such as limits on the number of proposals each reviewer can handle and team composition requirements. This approach is especially relevant to institutions like academic conferences, journals, and funding organizations, aiming to enhance the integrity and efficiency of the review process. Methods : This study is classified as descriptive research with a practical orientation and relies on data collection through applied methods. The approach is grounded in mathematical modeling. Initially, the selected articles are grouped into clusters. Reviewers are then assigned to these clusters using a multi-objective binary integer programming model that incorporates all relevant criteria and constraints. To implement this model, 150 articles were selected through purposive sampling. The model was optimized using Python, employing both the branch-and-bound algorithm and a genetic metaheuristic algorithm to maximize the degree of reviewer-proposal matching within the proposed framework.  Results : The proposed model demonstrates strong practical relevance by closely reflecting real-world reviewer assignment challenges. By simultaneously optimizing thematic coverage, evaluation fairness, and reviewer expertise, the model captures the complexity of actual allocation scenarios. To validate its effectiveness, the model was solved using both the branch-and-bound algorithm and a genetic algorithm. The branch-and-bound method yielded an objective value of 177.349 in approximately one hour, while the genetic algorithm reached 120.35 in just seven minutes. Although branch-and-bound guarantees optimality, its longer runtime makes it less practical for larger datasets. Given the similarity of results, the genetic approach is a reliable and scalable alternative. Conclusion : This study introduces a new allocation strategy and mathematical model for reviewer assignment, addressing often-overlooked factors such as reviewer expertise, grouping, and conflicts of interest. By integrating these elements, the proposed model better reflects real-world conditions. Future work is encouraged to expand on these findings with new frameworks and methods.

The objective of this study was to explore the experiences of students and educators during the transition from special education to higher education. This qualitative study employed a phenomenological approach to gain an in-depth understanding of the participants' experiences. Data were collected through semi-structured interviews with 23 participants, including 15 students who had transitioned from special education to higher education and 8 educators, comprising special education teachers, higher education faculty members, and disability support staff. Thematic analysis was used to analyze the interview transcripts, with themes and subthemes identified through coding and categorization. The analysis revealed three primary themes: Transition Challenges, Support Systems and Resources, and Personal Growth and Development. Transition Challenges included academic difficulties, social integration issues, navigating support services, emotional and mental health challenges, and financial barriers. Support Systems and Resources encompassed institutional support, peer support, parental involvement, community resources, and technological aids, with a notable emphasis on the importance of faculty and staff training. Personal Growth and Development highlighted the development of self-advocacy skills, independence and responsibility, academic and career aspirations, and building confidence and resilience. The findings of this study underscore the multifaceted nature of the transition from special education to higher education, highlighting both the challenges and opportunities for students with disabilities. Effective support systems and comprehensive planning are crucial for facilitating successful transitions. The study's insights can inform the development of targeted interventions and support strategies to create more inclusive and supportive educational environments, ultimately empowering students with disabilities to succeed in higher education.