مطالب مرتبط با کلیدواژه

Artificial Intelligence


۶۱.

The Impact of Artificial Intelligence on Social Networks: A Case Study of Political Participation in the 2024 Presidential Election

نویسنده:
منبع: International Journal of Political Science, Vol ۱۴, No ۲ , ۲۰۲۴ 127 - 148

کلیدواژه‌ها: Artificial Intelligence Social Networks political participation Presidential Elections

حوزه‌های تخصصی:
تعداد بازدید : ۱۴۰ تعداد دانلود : ۸۱
The primary issue of this research was to investigate the relationship between artificial intelligence (AI) and user behavior patterns on social networks, the impact of AI on voting behavior, and the connection between the use of online data analysis and students' decision-making in presidential elections. This question arises while considering the influence of AI on user behavior patterns and decision-making in presidential elections. The objective of this study was to evaluate the impact of AI variables and online data on user behavior and decision-making in various contexts. This re-search examined the study hypothesis to better understand how behavior and decision-making are shaped in the digital age and the role of modern technologies in these processes. To conduct this research, a survey method and available library resources were utilized. The study used existing sources and collected necessary data from the target population, namely students at universities in Tehran, and employed descriptive and inferential statistics for data analysis. The findings of this research indicate that demographic variables and AI play a significant role in user behavior and de-cision-making, and the use of online data analysis can influence students' decision-making in presi-dential elections. Additionally, AI can be effective in detecting user behavior patterns on social networks and influencing voting behavior. These results can be useful for policymakers, election officials, and social activists in designing effective strategies to monitor user behavior and decision-making in the digital age, contributing to a better understanding of AI's role in shaping behavior and decision-making in society.
۶۲.

Leveraging artificial intelligence for vocabulary development: Effects on recall and retention in English for specific purposes contexts(مقاله پژوهشی دانشگاه آزاد)

نویسنده:
منبع: Curriculum Research, Volume ۶, Issue ۲ , ۲۰۲۵ 52 - 76

کلیدواژه‌ها: Artificial Intelligence English for Specific Purposes Vocabulary recall Vocabulary Retention

حوزه‌های تخصصی:
تعداد بازدید : ۱۳۰ تعداد دانلود : ۱۱۵
English for Specific Purposes (ESP) education has gained prominence as a specialized field designed to address the distinct linguistic needs of learners. Although AI-enhanced instruction has been investigated within general English language learning, its implementation in ESP contexts particularly concerning vocabulary recall and retention has remained insufficiently explored. This study sought to evaluate the impact of AI-supported instruction on vocabulary recall and retention among Iranian ESP learners. Based on non-random convenience sampling, a total of 48 undergraduate students in an ESP course from a university in a southeastern province in Iran participated in the present quasi-experimental study. The participants were non-randomly assigned into two different groups: an experimental group (n=24) receiving AI-powered vocabulary instruction through Diffit, and a control group (n=24) receiving traditional print-based vocabulary instruction. Data were collected during a twelve-week intervention through AI-powered instruction of ESP vocabulary. To address the research questions, a univariate repeated measures analysis of covariate (ANCOVA) was employed. Findings revealed that AI-enhanced instruction significantly improved vocabulary recall and retention among ESP learners. The results offer robust evidence supporting the efficacy of AI-based instructional approaches in enhancing vocabulary learning outcomes within ESP settings.
۶۳.

Artificial Intelligence in Education: Examining the Impact of AI on the Teaching-Learning Process(مقاله علمی وزارت علوم)

نویسنده:
منبع: Iranian Distance Education, Volume ۶, Issue ۱, Winter & Spring ۲۰۲۴ 146 - 156

کلیدواژه‌ها: Adaptive learning Artificial Intelligence Education Teaching and Learning Process Teaching learning

حوزه‌های تخصصی:
تعداد بازدید : ۷۷ تعداد دانلود : ۶۱
Artificial Intelligence (AI), particularly with machine learning and deep learning techniques, is revolutionizing human cognitive processes. From increasing accuracy and speed in performing repetitive and complex tasks to improving decision-making processes, AI has made significant strides in various fields including healthcare, business, and law. In healthcare, AI is accelerating medical diagnoses, and in business, it serves as a powerful analytical tool, increasing efficiency. In the legal field, it has optimized justice processes by providing public legal education services. The application of AI in teaching and learning processes is also significant; this technology has the potential to personalize the learning experience, provide 24/7 access to knowledge, and assist students in completing assignments with higher quality. Moreover, by providing new opportunities for teachers to optimize teaching content and assessment tools, it enhances their performance. However, there is a need for human oversight and guidance in the application of AI to maintain professional ethics and protect privacy. Ultimately, AI has the potential to have a lasting impact on the future of education by enabling personalized and targeted learning.
۶۴.

Evolution of Learning Experience Management in Distance Science Education(مقاله علمی وزارت علوم)

نویسنده:
منبع: International Journal of Digital Content Management, Vol. ۶, No. ۱۰, Summer & Fall ۲۰۲۵ 132 - 162

کلیدواژه‌ها: Artificial Intelligence biology tutoring Learning experience Management

حوزه‌های تخصصی:
تعداد بازدید : ۷۲ تعداد دانلود : ۵۹
Purpose : The primary objective of this research was to integrate ChatGPT, an advanced artificial intelligence language model, into distance science education. By addressing the specific challenges inherent in online learning environments, this study aims to investigate how technological advancements, such as ChatGPT, can effectively enhance the management and overall quality of distance education experiences. Method : This qualitative, exploratory study aimed to provide a comprehensive understanding of the potential applications of ChatGPT in distance science education. This study identifies the various interactions that can occur in distance education and describes and evaluates the input and output instructions associated with each interaction. The chat bot used is https://chatbot.theb.ai and A biology tutoring platform uses ChatGPT to provide personalized support to students working on biology issues or concepts. Findings : Based on the results, the artificial intelligence can play an important role in improving distance science education. Furthermore, this study highlights the importance of developing metacognitive skills among learners and encourages educators to seek professional development opportunities to enhance the quality and engagement of distance science education. This study emphasizes the need for careful planning, research, design, evaluation, management, and responsible application of AI technology in distance education. Conclusion : This study was concluded that ChatGPT could be very useful for both learners and educators in distance education. This research showcases the innovative results facilitated by ChatGPT and provides valuable insights and practical guidance for educators, researchers, and policy makers on the effective use of AI technologies in distance science education.
۶۵.

Analyzing the Dimensions of Digital Transformation in Education with the Approach of the Roadmap(مقاله علمی وزارت علوم)

نویسنده:
منبع: International Journal of Digital Content Management, Vol. ۶, No. ۱۰, Summer & Fall ۲۰۲۵ 163 - 196

کلیدواژه‌ها: Artificial Intelligence Educational Digital Transformation Industry 5.0 Iran's Education Personalization of Education

حوزه‌های تخصصی:
تعداد بازدید : ۱۰۶ تعداد دانلود : ۸۳
Purpose : The purpose of the current research is to extract the components and dimensions of digital transformation and determine the levels and sequence of dimensions in Iran's education and upbringing, for the planning and implementation roadmap. Method : This research has a mixed approach (qualitative-quantitative). The qualitative section was able to extract the components of digital transformation by searching for authentic Persian and English articles published in the last ten years. With the help of seven experts, the digital transformation components were classified into eight dimensions in the form of 109 identified sub-components using the ISM method. Dimension levels were determined by SSIM matrix calculations in the quantitative part. MICMAC software version 5.3.0 was used to calculate the impact of relationships. Findings : Based on the opinion of experts and the results of ISM calculations, the identified dimensions including: institutional, education, technology, infrastructural, social, cultural and economic were placed in four levels. Conclusion : According to experts, the institutional dimension, being placed at the fourth level, has the greatest impact on digital transformation in Iran's education. Therefore, it is one of the key dimensions to achieve digital educational transformation that is placed at the first level of the model. According to the results of ISM, the economic and cultural dimensions were placed at the third level. Also, in analyzing the impact of relationships between dimensions using MICMAC software, the results indicate that the institutional dimension has a significant impact on infrastructure development.
۶۶.

Artificial intelligence and disaster risk management: A need for continuous education

نویسنده:
منبع: Socio-Spatial Studies, Vol ۵, Issue ۱, Winter ۲۰۲۱ 13 - 29

کلیدواژه‌ها: Artificial Intelligence crisis management Natural Disasters Continuous Education earthquakes

حوزه‌های تخصصی:
تعداد بازدید : ۵۶ تعداد دانلود : ۴۶
Artificial Intelligence has is a pivotal tool in enhancing crisis management during natural disasters such as earthquakes. This article examines the role of AI in generating real-time information, predicting stakeholder and population responses, and optimizing decision-making processes. A meta-analysis of existing literature highlights AI's potential to transform traditional crisis management approaches by enabling rapid assessment of disaster scenarios, efficient resource allocation, and communication strategies tailored to situational dynamics. However, the integration of AI in such critical domains requires not only technological advancement but also a paradigm shift in the skills and competencies of crisis management professionals. This paper argues for the necessity of continuous education for stakeholders, emphasizing training in AI tools and data literacy to ensure effective utilization of these technologies in high-stakes environments. Furthermore, it explores the ethical implications of AI use in crisis contexts, including issues of accountability, data privacy, and bias mitigation. To address these challenges through sustained education and interdisciplinary collaboration, stakeholders should harness AI’s full potential while minimizing risks.
۶۷.

Artificial intelligence in MBA education: Perceptions, ethics, and readiness among Iranian graduates

نویسنده:
منبع: Socio-Spatial Studies, Vol ۵, Issue ۱, Winter ۲۰۲۱ 31 - 42

کلیدواژه‌ها: Artificial Intelligence MBA education graduate perceptions Curriculum reform Iranian Universities

حوزه‌های تخصصی:
تعداد بازدید : ۴۸ تعداد دانلود : ۴۲
This study explores the perceptions of Iranian MBA graduates regarding the integration of AI into business education. Drawing on survey data from 379 alumni across a range of Iranian universities, the research assesses five core dimensions: perceived usefulness of AI, ethical concerns, faculty preparedness, job market implications, and interest in AI-focused coursework. The study also investigates whether demographic factors such as age, gender, income level, and marital status significantly influence these perceptions. Results indicate a generally favorable view of AI integration, with particularly strong support for incorporating AI coursework into MBA programs. Despite broad enthusiasm, respondents expressed concerns about data privacy, algorithmic bias, and the limited readiness of faculty to teach AI-related content. Inferential tests and path analysis reveal that demographic variables had little predictive power over AI perceptions or preferences, suggesting widespread acceptance across social strata. The findings underscore both the readiness of Iranian MBA graduates for AI-related curricular reform and the need for targeted institutional responses, including faculty development and ethical frameworks.
۶۸.

AI-Driven credit risk assessment in Iranian banking

نویسنده:
منبع: Socio-Spatial Studies, Vol ۵, Issue ۲, Spring ۲۰۲۱ 1 - 13

کلیدواژه‌ها: Artificial Intelligence credit risk assessment Iranian Banking hybrid decision-making algorithmic ethics Organizational Change

حوزه‌های تخصصی:
تعداد بازدید : ۶۰ تعداد دانلود : ۵۷
This study explores how AI is perceived and operationalized in credit risk assessment within Iranian banking institutions, with a particular focus on the experiences of electronic banking professionals in Tehran. Drawing on grounded theory methodology and semi-structured interviews with 38 practitioners from both public and private banks, the research reveals a complex landscape of technological promise and institutional constraint. Participants emphasized the efficiency, consistency, and expanded analytical reach afforded by AI models, particularly in leveraging alternative data and enhancing fraud detection. However, these benefits are tempered by operational challenges, including fragmented data systems, outdated IT infrastructure, and opaque algorithmic outputs. Ethical and regulatory concerns—especially surrounding algorithmic bias, accountability, and the absence of formal oversight—emerged as significant barriers to responsible deployment. Moreover, organizational resistance, hierarchical decision-making structures, and cultural skepticism toward automation further complicate adoption. The findings suggest strong practitioner support for hybrid decision-making models that integrate AI capabilities with human expertise. This model offers a viable pathway toward responsible innovation, balancing the computational advantages of AI with the contextual judgment and ethical sensitivity of human agents.
۶۹.

Doctors for AI? A systematic review

نویسنده:
منبع: Socio-Spatial Studies, Vol ۶, Issue ۱, Winter ۲۰۲۲ 13 - 26

کلیدواژه‌ها: Artificial Intelligence Healthcare Pysicians Doctors medical education

حوزه‌های تخصصی:
تعداد بازدید : ۷۱ تعداد دانلود : ۴۵
Artificial intelligence is transforming all aspects of human life and healthcare industry is one of the areas of change due to introduction of AI. This systematic review examines the perspectives of doctors on the use of AI in clinical settings, synthesizing findings from peer-reviewed articles to provide a comprehensive understanding of their attitudes, experiences, and concerns. Drawing on studies conducted across diverse healthcare environments, the review identifies prevailing themes, including the perceived benefits of AI in improving diagnostic accuracy, streamlining workflows, and personalizing patient care. However, it also highlights persistent challenges, such as ethical dilemmas surrounding accountability and autonomy, concerns about data privacy, and the potential for algorithmic biases. The findings reveal that while many physicians are optimistic about the transformative potential of AI, significant gaps remain in education and infrastructure that hinder effective adoption. Doctors frequently underscore the need for explainable AI systems, robust regulatory frameworks, and targeted training programs to address these challenges. This review contributes to the growing body of literature on AI in healthcare by offering insights into how medical professionals perceive and engage with this rapidly evolving technology.
۷۰.

Reimagining MBA education in the age of artificial intelligence; A meta-synthesis

نویسنده:
منبع: Socio-Spatial Studies, Vol ۶, Issue ۱, Winter ۲۰۲۲ 43 - 50

کلیدواژه‌ها: MBA education Artificial Intelligence Curriculum reform Digital pedagogy Educational Technology Management learning

حوزه‌های تخصصی:
تعداد بازدید : ۵۸ تعداد دانلود : ۴۴
The integration of artificial intelligence into Master of Business Administration (MBA) education is reshaping the foundations of management learning worldwide. This study conducts a qualitative meta-synthesis of 17 peer-reviewed sources published between 2001 and 2021 to examine how AI technologies—ranging from generative models and adaptive learning systems to predictive analytics and federated learning—are influencing MBA curricula, pedagogy, student engagement, and institutional strategies. Findings reveal that AI holds transformative potential for enhancing personalization, academic performance, and curriculum relevance, while also addressing enrollment challenges and labor market misalignments. However, integration remains uneven and fraught with ethical, infrastructural, and pedagogical challenges, including concerns over academic integrity, faculty preparedness, and digital equity. Conceptual frameworks such as the Technology Acceptance Model (TAM), paradox theory, and interpretive structural modeling elucidate the enabling and constraining factors surrounding AI adoption. The study highlights the urgent need for business schools to pursue a holistic and ethically grounded AI strategy that balances technological innovation with humanistic leadership development. Ultimately, AI is not only redefining how MBAs are delivered, but also reorienting their purpose toward preparing future-ready leaders for complex, data-driven environments. The paper concludes with a call for adaptive, inclusive, and ethically sound educational reforms in MBA programs worldwide.
۷۱.

Artificial intelligence in credit risk assessment

نویسنده:
منبع: Socio-Spatial Studies, Vol ۶, Issue ۲, Spring ۲۰۲۲ 1 - 14

کلیدواژه‌ها: credit risk assessment Artificial Intelligence Machine Learning Explainable AI model interpretability Financial Technology

حوزه‌های تخصصی:
تعداد بازدید : ۴۸ تعداد دانلود : ۴۶
This study presents a structured literature review on the application of AI in credit risk assessment, synthesizing empirical and conceptual research published between 2016 and 2022. It critically examines a range of AI models, including artificial neural networks (ANN), support vector machines (SVM), fuzzy logic systems, and hybrid architectures, with an emphasis on their predictive accuracy, robustness, and operational applicability. The review highlights that AI-based models consistently outperform traditional statistical techniques in handling nonlinear patterns, imbalanced datasets, and complex borrower profiles. Furthermore, AI enhances the inclusivity of credit evaluation by integrating alternative data sources and adapting to dynamic financial environments. However, the study also identifies ongoing challenges related to model interpretability, fairness, and regulatory compliance. By evaluating model performance metrics and methodological innovations across multiple contexts—including emerging markets, peer-to-peer platforms, and digital banking—the study offers a nuanced understanding of AI's strengths and limitations. The paper concludes with a call for balanced integration of explainable AI tools and ethical governance to ensure responsible deployment in financial institutions.
۷۲.

The representation of artificial intelligence in world cinema; A comparative study of the pre-1990 and post-2010 periods

نویسنده:
منبع: Socio-Spatial Studies, Vol ۹, Issue ۱, Winter ۲۰۲۵ 47 - 59

کلیدواژه‌ها: Artificial Intelligence Science fiction cinema cultural discourse Representation

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تعداد بازدید : ۴۱ تعداد دانلود : ۴۳
Previous studies have predominantly examined the representation of artificial intelligence in fictional literature, revealing a notable gap in analyzing cinema as an influential medium. The period before 1990 marked the onset of fundamental shifts in communication technologies and the public’s perception of technology, while the era after 2010 witnessed artificial intelligence becoming widely integrated into everyday life. These two historical ruptures have generated significant semantic transformations in cinematic portrayals that demand precise comparative and theoretical analysisThis study aims to conduct a comparative analysis of the “representation of artificial intelligence” in world cinema during the periods before 1990 and after 2010. Its central research question investigates the conceptual, narrative, character-development, and cultural-discourse differences and similarities surrounding artificial intelligence across these two eras. Twenty films (ten from each period) were selected based on their global acclaim and the centrality of artificial intelligence in their narratives. These films were analyzed using Saussurean–Peircean semiotics alongside Stuart Hall’s constructivist approach. The findings indicate that pre-1990 cinema predominantly focused on the “threat of technology” and the “human–machine war,” whereas post-2010 works emphasize “ethical crises,” “human–machine emotional relationships,” and “responsible coexistence.” Nevertheless, in both periods, artificial intelligence consistently functions as a “challenging Other,” perceived both as a threat and as a mirror reflecting humanity’s desires, hopes, and fears. The results underscore the necessity of rethinking the cultural-communication discourse surrounding technology and the shared future of humans and machines.
۷۳.

Advancing Sustainability in IT by Transitioning to Zero-Carbon Data Centers(مقاله علمی وزارت علوم)

نویسنده:
منبع: پژوهشنامه پردازش و مدیریت اطلاعات دوره ۴۰ تابستان ۱۴۰۴ ویژه نامه انگلیسی ۴ (پیاپی ۱۲۵) 583 - 608

کلیدواژه‌ها: Artificial Intelligence Network Security Autonomous Threat Response Machine Learning Cybersecurity deep learning Anomaly Detection Threat Mitigation Real-Time Security AI-Driven Systems (AI)

حوزه‌های تخصصی:
تعداد بازدید : ۴۶ تعداد دانلود : ۳۵
Cyber threats are changing constantly and these days more than 560,000 new malware varieties are launched daily, which means that rudimentary measures of protecting networks from attacks cannot be of much help in handling real time threats. Single-static security control and manual intervention are insufficient to address APTs, Zero Day, and high-volume DDoS attacks. This is where the application of AI in network security lays its foundation, where real time threat response programs become possible where they are trained to automatically identify, categorize, and mitigate highly complex attacks without requiring massive amount of time and effort. The changing role of AI in network security is examined in this work since it can contribute to the improvement of threat detection, decrease response time, and minimize reliance on human factors. This research reviews more than 150 AI-based security frameworks, and 25 case studies of different industries including finance, healthcare, telecommunications, to assess the efficiency of machine learning and deep learning algorithms for autonomous threat response. The insights show that in challenging contexts, AI-based solutions provide anomaly detection scores of up to 97%, which are far higher than those obtained by conventional systems with average scores of 80%. The response time increased up to 75% as the AI systems responded under 3 seconds during the large scale cyberattack simulation operations. Significant achievement of scalability was across networks with number of nodes more than ten thousand nodes at 90% reliability in different threat scenarios. These findings underscore the importance of AI as the cornerstone of today’s cybersecurity: delivering accurate and timely threat coverage and demonstrating high resilience to threat evolution. However, issues like, algorithm bias, ethical concerns, and resistance to adversarial perturbation calls the need for research to develop effective measures towards the longevity of banking security systems integrated with AI. This study emphasizes the importance of search for new strategies to strengthen current digital environments against the increasing number of threats.
۷۴.

Artificial Intelligence in Network Security with Autonomous Threat Response Systems(مقاله علمی وزارت علوم)

نویسنده:
منبع: پژوهشنامه پردازش و مدیریت اطلاعات دوره ۴۰ تابستان ۱۴۰۴ ویژه نامه انگلیسی ۴ (پیاپی ۱۲۵) 1469 - 1503

کلیدواژه‌ها: Artificial Intelligence Network Security Autonomous Systems Machine Learning (ML) Deep Learning (DL) Threat Detection cyberattacks Threat Mitigation Response time DDoS

حوزه‌های تخصصی:
تعداد بازدید : ۴۸ تعداد دانلود : ۳۶
Background: With the continued advance in cyber threats, traditional network security systems offer little returns to organizations. AI has turned out to be a useful technology in improving network security because it proactively identifies and responds to threats in a short time. Objective: This article seeks to discuss the role played by AI self-defending mechanisms in autonomous network security given their effectiveness in threat detection, response time, and the overall harm that can be caused to networks by cyber criminals. Methods: Three separate studies were made, including conventional security systems, and analytically compared them with the AI-driven system across 100 different network environments. Machine learning (ML), deep learning (DL), and other forms of AI were applied to identify and counteract distinct threats like viruses, phishing, and even DDoS attacks. Detecting accuracy, response time and ability to mitigate attacks where among some of the other factors that were examined. Results: Automated threat intelligence systems have a 92% accuracy while legacy systems only have 78%. Mean response time was also decreasing by 65% from 45 seconds to 15 seconds. A significant increase to attack mitigation rates was noted with fifty percent effectiveness of the AI programs averting 85 percent of the threats in the first 30 seconds of identification. Conclusion: Autonomous threat response systems substantiate AI, which function as a radically superior replacement to conventional network security structures, minimizing threat response time and boosting the overall threat neutralization outcome. Incorporation of these types of secure mechanisms into contemporary security landscapes is important as a means of counteraction against new forms of cyber threats.
۷۵.

Addressing Challenges of L2 Grammar Learning with a Focus on English Relative Clauses: AI-supported Language Learning(مقاله علمی وزارت علوم)

نویسنده:
منبع: Applied Research on English Language, V. ۱۴, N. ۳ , ۲۰۲۵ 53 - 76

کلیدواژه‌ها: Artificial Intelligence syntax relative clauses AI-Assisted Language Learning

حوزه‌های تخصصی:
تعداد بازدید : ۲۸ تعداد دانلود : ۱۸
The present study investigates the challenges of learning English grammar with a focus on the syntactic analysis of relative clauses (RCs) in Persian in contrast to English to identify the most common errors made by Persian learners of English. In addition, it aims to enhance L2 grammar learning and overcome challenges using AI-assisted tools such as Wordtune, Instatext, and ChatGPT in classroom activities. The quantitative data were collected through the RC tests adapted from the models used by Izumi (2003), comprising three test types: sentence combination, interpretation, and grammaticality judgment. These tests were administered before and after the implementation of AI-powered strategies. The result of the tests in intermediate learners revealed that the most recurrent interlingual error was “the use of object pronouns” instead of gaps, while the challenges in “RC reduction” were among the most common intralingual errors. The findings highlight not only the major differences in RC structures between the two languages but also present an innovative approach that uses AI to address these challenges, offering insights for teachers and instructors. Addressing such errors and utilizing technological advances can pave the way for learners and teachers to have more effective learning and teaching strategies.
۷۶.

Artificial Intelligence Implementation in Teaching English as a Foreign Language: A Qualitative Research Synthesis(مقاله علمی وزارت علوم)

نویسنده:
منبع: Applied Research on English Language, V. ۱۴, N. ۳ , ۲۰۲۵ 77 - 122

کلیدواژه‌ها: Artificial Intelligence Digital Language Instruction Emerging technologies mobile-assisted language learning Qualitative Synthesis

حوزه‌های تخصصی:
تعداد بازدید : ۲۷ تعداد دانلود : ۳۱
The rapidly growing influence of artificial intelligence (AI) is poised to fundamentally transform the realm of English as a Foreign Language (EFL) instruction. This research studied this emerging trend through a qualitative research synthesis of 24 peer-reviewed articles published between 2021 and 2024. It examined them to highlight the diverse applications, challenges, and teaching practices associated with AI in EFL education. Methodological rigor was ensured through established inclusion and exclusion criteria for selecting the articles. The qualitative synthesis and thematic analysis revealed five prominent themes that illuminate the current landscape of AI in EFL instruction: 1) conceptualizations of AI within EFL settings; 2) factors influencing its adoption; 3) challenges faced when integrating AI into EFL settings; 4) limitations of AI-based tools and methods; and 5) potential avenues for future investigation. Although integrating AI into EFL pedagogy is still in its early stages and presents various challenges, the findings provide valuable insights and practical recommendations for effectively using AI in EFL education, enhancing teaching methods, and improving student learning outcomes. Educators can make informed decisions regarding its implementation while navigating the evolving EFL instruction landscape by cultivating an understanding of AI's potential benefits and inherent limitations.
۷۷.

A Financial Management Maturity Model in Sports Organizations: A Novel Approach Using Artificial Intelligence(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of New Studies in Sport Management, Volume ۶, Issue ۳, August ۲۰۲۵ 100 - 114

کلیدواژه‌ها: Financial Management Financial transparency Sports organizations Artificial Intelligence Big Language Model

حوزه‌های تخصصی:
تعداد بازدید : ۳۵ تعداد دانلود : ۲۸
This paper deals with the development of a financial management maturity model for sports organizations based on artificial intelligence. We jointly consider enhancing financial transparency, oversight and control, risk management, and using advanced technologies in sports organizations. The proposed scheme relies on a constructivist grounded theory approach. The research process involved data collection through in-depth interviews with five AI language models, ChatGPT, Claude, Google Gemini, Mistral, and LLaMA. In addition, these models were utilized as an alternative to traditional experts. Finally, extensive simulations were conducted to validate that 209 initial codes were identified, which were then refined to 44 codes and eventually consolidated into 11 key themes. These themes include financial transparency, oversight and control, budget planning, risk management, and the use of advanced technologies. Numerical results show the efficiency that these themes are interlinked in a chain-like manner and contribute to enhancing the financial efficiency of sports organizations.
۷۸.

Using AI to Enhance Health: A Global Perspective(مقاله علمی وزارت علوم)

نویسنده:
منبع: World Sociopolitical Studies, Volume ۹, Issue ۴, Autumn ۲۰۲۵ 693 - 736

کلیدواژه‌ها: AI Ethics Artificial Intelligence healthcare costs Health Innovation Socio-economic Equity

حوزه‌های تخصصی:
تعداد بازدید : ۳۴ تعداد دانلود : ۲۲
The increasing expense of healthcare creates substantial difficulties for individuals, especially those from disadvantaged economic backgrounds who frequently encounter obstacles in obtaining prompt and adequate medical treatment. This study investigates how artificial intelligence could revolutionize healthcare by reducing these disparities and controlling costs. AI-powered medical services—such as remote consultations, diagnostic aids, and customized health advice—possess the ability to make healthcare information more widely accessible and improve early detection of preventable diseases. These technologies offer scalable, cost-effective solutions to bridge gaps in healthcare delivery, especially in underserved communities. However, the paper also examines the potential downsides of AI health systems, such as privacy concerns, biases in AI algorithms, and the risk of over-reliance on automated systems at the expense of human oversight. Despite these challenges, we argue that the integration of AI into healthcare is not only inevitable, but essential for the future of global health. Rather than dismissing these innovations, efforts should focus on developing ethical frameworks, robust governance, and equitable distribution mechanisms to maximize their benefits.
۷۹.

From Silicon to Sovereignty: MBA Students’ Views on AI’s Disruption of Global Power Dynamic(مقاله علمی وزارت علوم)

نویسنده:
منبع: World Sociopolitical Studies, Volume ۹, Issue ۴, Autumn ۲۰۲۵ 737 - 775

کلیدواژه‌ها: Artificial Intelligence Geopolitical Disruption Global Power Dynamics MBA Students Technological Sovereignty Iran

حوزه‌های تخصصی:
تعداد بازدید : ۲۲ تعداد دانلود : ۲۱
This research explores how Iranian MBA students view artificial intelligence as a driver of change in global power structures. Using a mixed-methods design, it combines survey results from 394 respondents with thematic analysis of open-ended answers. The quantitative data indicate a widespread belief that AI will hasten the decline of established global powers, widen global disparities, and offer emerging economies chances for geopolitical advantage. Qualitative themes include AI as a soft power tool, concerns over technological dependence, entrepreneurial optimism, and regulatory inadequacy. The analysis situates participants’ views within broader theoretical frameworks articulated by Innis, McLuhan, Castells, and Toffler, emphasizing AI’s capacity to redefine sovereignty, governance, and economic competitiveness. Statistical tests highlight how demographic variables, such as employment sector and academic status, significantly influence attitudes toward AI’s disruptive potential. These results underline both the optimism and anxiety among future business leaders regarding Iran’s capacity to harness AI’s transformative possibilities amidst structural and regulatory challenges.
۸۰.

AI, Global Governance, and the Need for an Integrated Disaster Risk Management System(مقاله علمی وزارت علوم)

نویسنده:
منبع: World Sociopolitical Studies, Volume ۹, Issue ۴, Autumn ۲۰۲۵ 815 - 851

کلیدواژه‌ها: algorithmic ethics Artificial Intelligence Data Interoperability disaster risk management Global Governance institutional capacity

حوزه‌های تخصصی:
تعداد بازدید : ۳۲ تعداد دانلود : ۲۷
This study examines the intersection of artificial intelligence, global governance, and disaster risk management through a qualitative investigation of 92 Iranian experts across disciplines such as geoinformatics, emergency planning, and environmental engineering. While AI offers a significant promise for enhancing early warning systems, damage assessments, and real-time decision-making, its integration into DRM systems remains constrained by fragmented data infrastructures, institutional silos, and geopolitical exclusions. Participants underscored AI’s potential to improve response coordination and risk forecasting, but emphasized the need for robust data governance, algorithmic transparency, and capacity building. The study highlights critical ethical and political concerns—particularly in countries like Iran facing technological marginalization due to sanctions and limited access to global data ecosystems. Drawing on grounded theory and thematic analysis, the research identifies institutional fragmentation, interoperability barriers, and normative governance deficits as primary obstacles to AI-enabled DRM. It argues for a globally coordinated approach grounded in justice, inclusivity, and human-centered design.