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Journal articles on the topic 'Generative Artificial Intelligence (Gen AI)'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Furey, Pippa. "Generative artificial intelligence 6: simulation." Journal of Paramedic Practice 17, no. 6 (2025): 1–7. https://doi.org/10.12968/jpar.2025.17.6.cpd1.

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Simulation-based education plays a critical role in paramedic education by enabling learners to develop both clinical and non-technical skills in a safe, realistic environment. This article concludes a continuing professional development series on generative artificial intelligence (Gen AI), focusing on how this technology can support and enhance simulation design. It explores how prompt engineering can reduce facilitator workload, improve scenario consistency and support reflective practice through augmented debriefing. Practical examples of Gen AI-generated simulation prompts are presented a

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Furey, Pippa. "Generative artificial intelligence 4: training companion." Journal of Paramedic Practice 17, no. 4 (2025): 1–7. https://doi.org/10.12968/jpar.2025.17.4.cpd1.

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Generative artificial intelligence (Gen AI) has gained the spotlight within education since large language models became publicly available. Gen AI has demonstrated its ability to generate high-quality academic content and even pass medical exams and these concerns have, at times, overshadowed its potential benefits. This paper explores Gen AI as a training companion in paramedic education and continuing professional development (CPD), highlighting how it can enhance learning, improve accessibility and address individual learner needs while acknowledging potential problems.

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Kalota, Faisal. "A Primer on Generative Artificial Intelligence." Education Sciences 14, no. 2 (2024): 172. http://dx.doi.org/10.3390/educsci14020172.

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Many educators and professionals in different industries may need to become more familiar with the basic concepts of artificial intelligence (AI) and generative artificial intelligence (Gen-AI). Therefore, this paper aims to introduce some of the basic concepts of AI and Gen-AI. The approach of this explanatory paper is first to introduce some of the underlying concepts, such as artificial intelligence, machine learning, deep learning, artificial neural networks, and large language models (LLMs), that would allow the reader to better understand generative AI. The paper also discusses some of t

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Mrs., Jyotsana Suhas Patil, and Vaibhavi Bhushan Karade Mrs. "Gen AI." International Journal of Advance and Applied Research S6, no. 22 (2025): 530–34. https://doi.org/10.5281/zenodo.15502291.

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<em>Generative Artificial Intelligence (Gen AI) is a rapidly evolving branch of artificial intelligence that focuses on creating new content, data, or information that resembles human creativity. It leverages deep learning models, such as Generative Adversarial Networks (GANs) and Transformer-based models (like GPT and DALL·E), to generate text, images, music, code, and videos. Gen AI models are trained on massive datasets to understand patterns and produce original, high-quality outputs. This technology has revolutionized industries like content creation, healthcare, gaming, education,

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Xu Zaijuan, T. Ramayah, and Shi Yubo. "DETERMINANTS OF GENERATIVE ARTIFICIAL INTELLIGENCE ADOPTION IN INSURANCE COMPANIES." International Journal of Business and Society 26, no. 1 (2025): 272–91. https://doi.org/10.33736/ijbs.9562.2025.

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This study aims to investigate the factors that influence the adoption of Generative artificial intelligence (GEN-AI) in insurance companies by utilizing the technology-organization-environment (TOE) framework.This study employs the TOE framework to examine the factors that impact the GEN-AI adoption at organizational level and was conducted on 307 insurance company managers and analysed using partial least squares (PLS). The research offers insurance companies and policy maker insights and recommendations for GEN-AI adoption. The empirical results reveal that relative advantage (RA), perceive

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Nan Wang, Nan Wang, Suqi Li Nan Wang, Chenhui Wang Suqi Li, and Li Zhao Chenhui Wang. "Current Status and Emerging Trends of Generative Artificial Intelligence Technology: A Bibliometric Analysis." 網際網路技術學刊 25, no. 3 (2024): 477–85. http://dx.doi.org/10.53106/160792642024052503013.

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<>With the widespread application of ChatGPT (Chat Generative Pre-trained Transformer), its superordinate concept, generative artificial intelligence (Gen AI), has received increasing attention from researchers. The current study attempted to explore the current status and emerging trends of Gen AI technology research by visualizing the relevant published articles using the Biblioshiny tool. A total of 1,902 academic articles in the Web of Science (WOS) database published between 2014-2022 were analyzed. Annual publications, most productive journals and countries, co-authors, co-occurrin

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Holcombe, Daniel. "Generative Artificial Intelligence (Gen-AI) in Undergraduate Literature Courses." Hispania 108, no. 1 (2025): 39–58. https://doi.org/10.1353/hpn.2025.a953555.

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Abstract: Accompanying the recent rise in cautious popularity surrounding Generative Artificial Intelligence (Gen-AI), some language educators are exploring innovative linguistic interactions with Gen-AI. Seeking to add a literature approximation to such criticism, this article explores two activities that feature Gen-AI in undergraduate literature courses. Both activities seek to offer forward-thinking Gen-AI engagement models for instructors of any literary work. Using Miguel de Cervantes’s Don Quixote (1605/15) as a referent, preparatory activities lead students through reading, note-taking

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Furey, Pippa. "Generative artificial intelligence 5: reflective practice." Journal of Paramedic Practice 17, no. 5 (2025): 1–7. https://doi.org/10.12968/jpar.2025.0040.

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Reflective practice is a foundational element of paramedicine, introduced during education and reinforced through professional standards set by the Health and Care Professions Council (HCPC). Generative artificial intelligence (Gen AI) presents a novel tool to support reflective practice in both formal CPD activities and informal self-reflection. Through prompt engineering, users can deepen the quality and insight of their reflection, while critically analysing the tool's output can enhance understanding of professional value, decision-making and personal growth. This article explores establis

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DeCotis, Paul A. "The Generative Artificial Intelligence Utility." Climate and Energy 40, no. 5 (2023): 21–26. http://dx.doi.org/10.1002/gas.22378.

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Generative Artificial Intelligence (Gen AI) is still in its infancy, yet it has started to transform the way people live, work, and play. The cutting‐edge technological innovation of Gen AI has unbounded potential and its contributions to the economy and society are still mostly hypothetical. In the short run we might overestimate its transformative impact and in the long run we might underestimate its impact. In either case, unprecedented change is upon us. Think of the changes to the ways in which we live, work, and play as technology evolved from wall‐mounted landline telephones to car phon

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Suhana, Suhana, Dina Hikmayanti, Lisania Cahya Agustin, and Zhanubha Cinta Aurelline. "GENERATIVE ARTIFICIAL INTELLIGENCE (AI) NEW VALUE PROPOSITION IN COLLEGE." Jurnal Abdisci 2, no. 4 (2025): 154–65. https://doi.org/10.62885/abdisci.v2i4.612.

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Background. Learning technology has changed drastically. Lecturers who were previously a source of knowledge changed their role to become mentors for students. Aims. Such rapid development of AI has replaced human functions with limited memory. AI stores data indefinitely. All university lecturers and students need to know this progress, so there is a socialization event regarding the new value proposition of generative artificial intelligence on campus. Method. The method used is a presentation from the students, by students, and for students whom lecturers accompany. Result. In this presenta

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Furey, Pippa. "Generative artificial intelligence 3: language translation." Journal of Paramedic Practice 17, no. 3 (2025): 1–8. https://doi.org/10.12968/jpar.2025.17.3.cpd1.

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This paper explores the evolving role of generative artificial intelligence (Gen AI) in addressing digital inequality – particularly in healthcare settings. While technology holds significant potential to bridge communication gaps, disparities in access to digital resources and limitations in training data currently constrain the effectiveness of translation tools. Key challenges such as the underrepresentation of low-resourced language groups, accuracy issues, and artificial intelligence (AI) hallucination are discussed. Ongoing trials and innovations within healthcare language translation ar

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Furey, Pippa. "Generative artificial intelligence 2: goal-setting." Journal of Paramedic Practice 17, no. 2 (2025): 1–7. https://doi.org/10.12968/jpar.2025.17.2.cpd1.

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The integration of generative artificial intelligence (Gen AI) into paramedic practice proposes a unique opportunity to enhance professional development and patient care. In this second instalment within the series, we offer a structured approach to continuous professional development (CPD) and performance improvement by exploring the use of SMART (specific, measurable, achievable, realistic, time-bound) targets in goal-setting. This article builds on the theme of ethical considerations, including data privacy, bias mitigation, and compliance with healthcare regulations. Practical examples and

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Breznau, Nate, and Hung H. V. Nguyen. "An Introduction to Generative Artificial Intelligence for Academics." F1000Research 14 (July 4, 2025): 655. https://doi.org/10.12688/f1000research.166513.1.

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General overview of artificial intelligence (AI) designed for academic students, workers, researchers, and teachers. A less technical introduction for those not familiar with computer science. It focuses primarily on generative AI (Gen AI), as this is the tool rapidly transforming every aspect of academic work. This primer covers four areas: 1. How does AI know what it knows? – An overview of artificial neural networks, large language models and “knowledge” ; 2. Ethics and best practices – Use cases, legal aspects and oversight; 3. Sources and tools - Support for the research process; 4. Promp

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Ramdani, Dani, Kahfi Heryandi Suradiradja, Muhamad Nurdin, and Muchtar Ali Anwar. "Workshop Pemanfaatan Generative Artificial Intelligence Di Azura Islamic Boarding School." Attamkiim: Jurnal Pengabdian Masyarakat 2, no. 1 (2025): 33–38. https://doi.org/10.62070/attamkiim.v2i1.241.

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Mengingat kemajuan teknologi digital saat ini, pemahaman dan penerapan kecerdasan buatan generatif atau Generative Artificial Intelligence (Gen-AI) dalam pendidikan menjadi semakin penting. Keunggulan Gen-AI berkontribusi secara signifikan untuk mempercepat pembelajaran siswa dan meningkatkan kualitas pendidikan secara keseluruhan dengan mendorong keterlibatan siswa dengan perangkat digital kontemporer. Di Azura Islamic Boarding School, kegiatan pengabdian masyarakat dilakukan melalui serangkaian tahapan, dimulai dengan tahap persiapan, yang meliputi penilaian kebutuhan dan penyiapan perangkat

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Furey, Pippa. "Generative artificial intelligence part 1: exploring ethical considerations." Journal of Paramedic Practice 17, no. 1 (2025): 1–7. https://doi.org/10.12968/jpar.2025.17.1.cpd1.

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This series surrounding generative artificial intelligence (Gen AI) explores its potential applications for paramedics across various aspects of their work. It begins by addressing the ethical considerations of this rapidly evolving technology. While artificial intelligence encompasses many forms, the focus here is on the generative subset – specifically free, publicly available Gen AI models. By reflecting current capabilities and limitations, this CPD series provides paramedics with insights into the practical and ethical use of this growing technology.

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Su, Jinlong, Yang Mo, and Swee Leong Sing. "Generative artificial intelligence in lattice structure design for additive manufacturing: A critical review." Engineering Science in Additive Manufacturing 1, no. 1 (2025): 025110006. https://doi.org/10.36922/esam025110006.

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Lattice structures, characterized by their lightweight yet high-strength properties, energy absorption capabilities, and superior thermal management, have become integral in advanced additive manufacturing (AM) applications. However, designing optimized lattice structures that balance mechanical performance, manufacturability, and functional requirements remains a complex and computationally intensive challenge. Recently, generative artificial intelligence (Gen-AI) has emerged as a transformative approach, offering automated and efficient solutions for lattice structure design. This review exp

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Ben-Daniel, D. O. "Impact of Generative Artificial Intelligence on The Global Entertainment Industry & Its Legal Dynamics." American Journal of Society and Law 4, no. 1 (2025): 46–54. https://doi.org/10.54536/ajsl.v4i1.4566.

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The emergence of Artificial Intelligence (AI) has given rise to unprecedented and momentous consequences across humanity. There is no doubt that AI, most especially, Generative (Gen) AI portents massive consequences within the entertainment industry. This article attempts to contribute to the overall discuss of gen AI within the entertainment industry, and covers the proper understanding of gen AI and how AI models are trained; the entertainment industry; the impact of gen AI on the entertainment industry globally; the advantages and disadvantages of deploying gen AI within the entertainment i

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Thi Hien, LUONG, and LE Phuong Nga. "CURRENT STATUS AND MEASURES TO DEVELOP CRITICAL THINKING FOR PEDAGOGICAL STUDENTS IN USING GENERATIVE ARTIFICIAL INTELLIGENCE." Vinh University Journal of Science 53, Special Issue 2 (2024): 341–50. http://dx.doi.org/10.56824/vujs.2024.htkhgd180.

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From the results of a survey of students at universities in Vietnam on the use of generative artificial intelligence (Gen AI), the paper proposes three groups of measures to develop critical thinking. Students need to be aware of the benefits and potential risks of Gen AI, practice critical thinking operations such as information verification, questioning skills, comprehensive information analysis and evaluation, comparing sources, self-assessment, and decision-making. Instructors should employ active teaching methods and appropriate assessment techniques when integrating Gen AI in the classro

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Saeliang, Sukan, and Pinanta Chatwattana. "The Project-Based Learning Model via Generative Artificial Intelligence to Promote Programming Skills for Vocational Students." International Education Studies 18, no. 3 (2025): 1. https://doi.org/10.5539/ies.v18n3p1.

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The project-based learning model via generative artificial intelligence, or PjBL model via Gen-AI, is a research tool that was initiated based on the concept of project-based learning management focusing mainly on self-directed learning, in which learners are able to learn and practice through the projects they are interested in as to their aptitudes and competencies with the aid of generative artificial intelligence technology. The learning model developed in this study can be employed as a guideline for the instruction management designated specifically to promote programming skills. This st

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Prasanna Kumar Natta. "Generative AI in enterprise systems: Moving beyond conversational AI." World Journal of Advanced Engineering Technology and Sciences 15, no. 1 (2025): 1695–701. https://doi.org/10.30574/wjaets.2025.15.1.0408.

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Generative Artificial Intelligence has evolved beyond conventional applications into a transformative enterprise technology that fundamentally reshapes organizational capabilities across multiple domains. This article explores how Gen AI transcends simplistic chatbot implementations to deliver substantive value through enterprise process automation, intelligent software development, and advanced predictive analytics. Integrating Gen AI into enterprise ecosystems creates profound operational efficiencies by optimizing development lifecycles, automating complex workflows, and enabling dynamic bu

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Dúo Terrón, Pablo. "Generative artificial intelligence: Educational reflections from an analysis of scientific production." Journal of Technology and Science Education 14, no. 3 (2024): 756. http://dx.doi.org/10.3926/jotse.2680.

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Generative Artificial Intelligence (AI-Gen) in education is a challenge for educational administrations due to the benefits and risks of its use. This research seeks to analyse the scientific production of AI-Gen in the educational field. The method used was a bibliometric analysis of descriptive and quantitative documents from the Web of Science database. The VOSviewer statistical programme was used to identify the keyword clusters and to create the network map. The results of this study ascertain that 2023 is the birth of AI-Gen research in education and has since produced a total of 178 pap

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Hsu, Hsiao-Ping. "Can Generative Artificial Intelligence Write an Academic Journal Article? Opportunities, Challenges, and Implications." Irish Journal of Technology Enhanced Learning 7, no. 2 (2023): 158–71. http://dx.doi.org/10.22554/ijtel.v7i2.152.

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This article offers an in-depth reflection on the author’s experiences with Generative Artificial Intelligence (Gen AI), ChatGPT 4.0. The author started the journey from their initial need for software for English proofreading and editing services to their interest in exploring pre-service teachers’ application of Gen AI in lesson planning. Based on prompt engineering techniques, an iterative three-stage manuscript generation process—brainstorming, refinement, and writing—with ChatGPT is detailed. A short paper generated by ChatGPT is presented. Although Gen AI is a valuable tool in providing

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Hassani, Hossein, and Emmanuel Sirimal Silva. "Predictions from Generative Artificial Intelligence Models: Towards a New Benchmark in Forecasting Practice." Information 15, no. 6 (2024): 291. http://dx.doi.org/10.3390/info15060291.

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This paper aims to determine whether there is a case for promoting a new benchmark for forecasting practice via the innovative application of generative artificial intelligence (Gen-AI) for predicting the future. Today, forecasts can be generated via Gen-AI models without the need for an in-depth understanding of forecasting theory, practice, or coding. Therefore, using three datasets, we present a comparative analysis of forecasts from Gen-AI models against forecasts from seven univariate and automated models from the forecast package in R, covering both parametric and non-parametric forecast

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Saúde, Sandra, João Paulo Barros, and Inês Almeida. "Impacts of Generative Artificial Intelligence in Higher Education: Research Trends and Students’ Perceptions." Social Sciences 13, no. 8 (2024): 410. http://dx.doi.org/10.3390/socsci13080410.

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In this paper, the effects of the rapid advancement of generative artificial intelligence (Gen AI) in higher education (HE) are discussed. A mixed exploratory research approach was employed to understand these impacts, combining analysis of current research trends and students’ perceptions of the effects of Gen AI tools in academia. Through bibliometric analysis and systematic literature review, 64 publications (indexed in the SCOPUS and Web of Science databases) were examined, highlighting Gen AI’s disruptive effect on the pedagogical aspects of HE. The impacts identified by the literature we

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Bera, Ashok Kumar. "Cash Flow Acceleration with Generative Artificial Intelligence (Gen AI)." International Journal of Computer Trends and Technology 72, no. 4 (2024): 111–15. http://dx.doi.org/10.14445/22312803/ijctt-v72i4p114.

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Hsu, Hsiao-Ping, Janice Mak, Jennifer Werner, et al. "Preliminary Study on Pre-Service Teachers’ Applications and Perceptions of Generative Artificial Intelligence for Lesson Planning." Journal of Technology and Teacher Education 32, no. 3 (2024): 409–37. https://doi.org/10.70725/869859beoezu.

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As part of an international collaborative design-based research initiative, this study examines the applications and perceptions of generative artificial intelligence (Gen AI) among pre-service primary teachers within an Irish educational program. It focuses on how personal and academic uses of Gen AI influence their perceptions of using Gen AI for lesson planning. The findings highlight that while Gen AI is preliminarily used by pre-service primary teachers for personal and academic purposes, its integration into lesson planning is less frequent. Crucially, the study reveals no significant co

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Tambe, Ashwin. "Unlocking Financial Services with Generative AI and Converged Infrastructure." International Journal for Research in Applied Science and Engineering Technology 12, no. 11 (2024): 831–36. http://dx.doi.org/10.22214/ijraset.2024.65206.

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Generative Artificial Intelligence (Gen AI) is poised to revolutionize financial services by empowering institutions to unlock the true potential of their data, driving a wave of innovation in risk management, personalized customer experiences, improved financial analytics, secure AI model training, and optimized high-frequency trading. Unleashing this potential necessitates a converged infrastructure that integrates cloud and on-premise resources with high-performance computing (HPC).Given Gen AI's demanding nature, the immense computational power offered by HPC is critical. This paper explor

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Abubakari, Mussa Saidi. "Generative AI literacy and lifelong learning: A literature overview." Forum for Education Studies 3, no. 3 (2025): 2621. https://doi.org/10.59400/fes2621.

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As generative artificial intelligence (Gen-AI) becomes increasingly integrated into society, understanding how individuals can effectively use these technologies is essential. This paper examines the concept of Generative AI Literacy (Gen-AIL), focusing on the skills needed to navigate and apply Gen-AI tools in personal and professional contexts. Using a targeted literature review of recent studies from databases such as Google Scholar, Consensus.app, and Undermind.ai, the paper identifies key dimensions of Gen-AIL and explores its role in supporting lifelong and personalized learning. The stu

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Duran, Ali, and Uğur Ferhat Ermiş. "Integrating Generative AI in Education: Implications for School Leadership from Policy Documents Through Bolman and Deal's Four Frame Theory." Bartın University Journal of Faculty of Education 14, no. 2 (2025): 416–40. https://doi.org/10.14686/buefad.1435086.

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As generative artificial intelligence (Gen-AI) technologies continue to evolve, it becomes increasingly important for educators to effectively leverage their benefits within educational settings.The integration of artificial intelligence (Gen-AI) into educationrepresents a significant shift in teaching, learning, and administrative practices. This article examinesthe implications, particularly focusing on the roles and responsibilities of school leaders through Bolman and Deal's Four Frame Theory, including Structural, Human Resources, Political, and Symbolic frames.Adopting a qualitative rese

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Islam, Tasin, Alina Miron, Monomita Nandy, Jyoti Choudrie, Xiaohui Liu, and Yongmin Li. "Transforming Digital Marketing with Generative AI." Computers 13, no. 7 (2024): 168. http://dx.doi.org/10.3390/computers13070168.

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The current marketing landscape faces challenges in content creation and innovation, relying heavily on manually created content and traditional channels like social media and search engines. While effective, these methods often lack the creativity and uniqueness needed to stand out in a competitive market. To address this, we introduce MARK-GEN, a conceptual framework that utilises generative artificial intelligence (AI) models to transform marketing content creation. MARK-GEN provides a comprehensive, structured approach for businesses to employ generative AI in producing marketing materials

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Singh, C. "Finance, Financial Crime and Regulation: Can Generative AI (Artificial Intelligence) Help Face the Challenges?" Frontiers in Law 4 (February 17, 2025): 1–5. https://doi.org/10.6000/2817-2302.2025.04.01.

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Generative artificial intelligence (Gen AI) has helped change the trajectory of Banking (FinTech) and Law (Reg Tech/Law Tech). Technology innovates at an astounding rate. AI and Gen AI can not only simulate human intelligence (human thinking) but also perform tasks independently. It can develop intelligence based on its experiences, process detailed and complex information whilst continually learning and re-learning to be able to undertake complex, technical, and time-consuming tasks in real time. It can identify objects, patterns, people and voices(etc.) and look for problems far earlier – th

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Matthews, Blair. "Finding the human in an era of machine intelligence: A flat ontological analysis of generative AI and language learning." Technology in Language Teaching & Learning 6, no. 3 (2024): 1612. http://dx.doi.org/10.29140/tltl.v6n3.1612.

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Amid the optimism of generative Artificial Intelligence (gen-AI) in language education, there remains a weak connection to learning practices. The emergence of gen-AI has preceded considerations of how it should be applied in teaching and learning. However, while gen-AI has been justified in terms of the possibilities to enhance learner agency by expanding opportunities to engage with language, such as through the generation of content or the translation of texts, it can also take power away from learners. How can learners be self-determining in light of how choices become increasingly guided

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Verma, Umika. "A journey from AI to Gen-AI." Spectrum of Emerging Sciences 4, no. 1 (2024): 74–78. http://dx.doi.org/10.55878/ses2024-4-1-14.

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The history of artificial intelligence (AI), from its conception to the creation of general AI (Gen-AI), is a fascinating story of human inventiveness, technical growth, and philosophical research. This article examines the historical milestones, major inventions, and transformational concepts that have influenced AI's trajectory. Beginning with early symbolic AI and rule-based systems, it investigates the shift to machine learning, highlighting discoveries in neural networks and deep learning that transformed disciplines such as computer vision and natural language processing. The introductio

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Bonde, Lossan. "A Conceptual Design of a Generative Artificial Intelligence System for Education." International Journal of Research and Innovation in Applied Science IX, no. IV (2024): 457–69. http://dx.doi.org/10.51584/ijrias.2024.904034.

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Artificial Intelligence (AI) and, more specifically, Generative Artificial Intelligence (GenAI) are among the most trending disruptive technologies, offering unprecedented possibilities for innovation in education by customising learning paths, fostering creativity, and bridging knowledge gaps. Gen AI is a subfield of AI which generates content (text, image, audio or video) that is comparable to human-generated content. It uses complex Machine Learning (ML) models and Neural Networks (NN) trained on large datasets. The launch of ChatGPT in November 2022 has significantly raised the standards f

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Yan, Wanxin, Taira Nakajima, and Ryo Sawada. "Benefits and Challenges of Collaboration between Students and Conversational Generative Artificial Intelligence in Programming Learning: An Empirical Case Study." Education Sciences 14, no. 4 (2024): 433. http://dx.doi.org/10.3390/educsci14040433.

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The utilization of conversational generative artificial intelligence (Gen AI) in learning is often seen as a double-edged sword that may lead to superficial learning. We designed and implemented a programming course focusing on collaboration between students and Gen AI. This study explores the dynamics of such collaboration, focusing on students’ communication strategies with Gen AI, perceived benefits, and challenges encountered. Data were collected from class observations, surveys, final reports, dialogues between students and Gen AI, and semi-structured in-depth interviews. The results show

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Vinichenko, Mikhail V., Galina Yu Nikiporets Takigawa, Aleksander A. Oseev, Marina V. Rybakova, and Sergey A. Makushkin. "Trust of the Generation Z in Artificial Intelligence in the Assessment of Historical Events." International Journal of Early Childhood Special Education 14, no. 1 (2022): 326–34. http://dx.doi.org/10.9756/int-jecse/v14i1.221040.

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The article considered the degree of trust of Russian and Slovak students of generation Z (Gen Z) in artificial intelligence (AI) in the assessment of historical events in the conditions of digital society. The basic empirical methods of the study were a sociological survey and focus group conducted in the context of the COVID 19 pandemic remotely using the resources of the online Google Form and cloud conference platform Zoom. The study found that the attitude of Gen Z to AI in the context of digitalization of society is ambiguous and contradictory, which affects the degree of trust in the as

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Researcher. "GEN AI IN DOCUMENT AUTOMATION IN RPA." International Journal of Artificial Intelligence & Machine Learning (IJAIML) 3, no. 2 (2024): 54–61. https://doi.org/10.5281/zenodo.13325883.

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This paper explores the integration of Generative Artificial Intelligence (Gen AI) in enhancing document automation within Robotic Process Automation (RPA). By leveraging technologies such as natural language processing (NLP) and machine learning (ML), Gen AI improves the automation of document processing, increasing efficiency, accuracy, and reducing costs. We analyze case studies across various industries and address challenges such as data privacy, implementation complexity, and the need for continuous model updates. The paper also outlines future trends and advancements in Gen AI-driven do

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KHAN, SAHIL. "Role of Generative AI in Digital Campaigns." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem50580.

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Abstract In an era where digital transformation is accelerating across industries, Generative Artificial Intelligence (Gen AI) has emerged as a revolutionary force in reshaping marketing practices. This study explores the evolving role of Gen AI in digital marketing campaigns within the Indian context, where technology adoption is on the rise amid a dynamic consumer landscape. Tools such as ChatGPT, DALL·E, Midjourney, and other large language and image models are being increasingly integrated into marketing workflows to streamline content creation, enhance personalization, and support strateg

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Dzhaparov, Plamen. "Generative Artificial Intelligence in Banking – Risks and Challenges." Izvestia Journal of the Union of Scientists - Varna Economic Sciences Series 13, no. 1 (2024): 231–41. https://doi.org/10.56065/ijusv-ess/2024.13.1.231.

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Generative artificial intelligence has since 2022 risen to the top of the agenda of banking executives around the world. However, this rapid “embrace” of innovation comes with certain threats and challenges. This paper aims to outline all these risks while suggesting ways for successful implementation of Gen AI in the banking value chain. The research showed that there is no universal approach for banks to take advantage of the potential of this new technology. Instead, they must work out their own strategies for such implementation, taking into account many of the specifics of their organizat

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Srikanth Vadlamani and (Dr) Punit Goel. "The Future of E-Commerce and Distributed Systems Through the Lens of Gen AI." Universal Research Reports 12, no. 1 (2025): 415–35. https://doi.org/10.36676/urr.v12.i1.1502.

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The convergence of Generative Artificial Intelligence (Gen AI) into the fields of e-commerce and distributed systems depicts an emerging landscape with immense potential. Although immense progress has been achieved within both fields, little is known about the long-term implications of AI-driven systems on e-commerce processes, scalability, and customer engagement. The aim of this research is to investigate how Gen AI can enhance and transform key aspects of e-commerce platforms, particularly in product recommendation systems, customer support, and dynamic pricing models. Although e-commerce h

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Radhika, Talekar. "Adoption of Artificial Intelligence (Gen AI) in teaching pedagogies in Higher Education: A Faculty Perspective." International Journal of Advance and Applied Research S6, no. 19 (2025): 159–68. https://doi.org/10.5281/zenodo.15101035.

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<em>The 21st century marks a transformative shift in education with the integration of Generative Artificial Intelligence (Gen AI) into teaching pedagogies. AI-driven tools are increasingly shaping instructional methods, curriculum design, and student engagement. However, while these technologies offer innovative solutions, they also present challenges related to adaptability, ethical considerations, and pedagogical effectiveness. This study explores faculty perspectives on the adoption of Gen AI in higher education, identifying commonly used AI tools, their perceived benefits, concerns, and t

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Antony, Ronald Reagan Panguraj. "Gen AI for Tailored Mental Health Interventions: Utilizing LLMs to Generate Personalized Coping Strategies, Therapy Plans, or Even Virtual Mental Health Support Systems Based on Individual User Data and Psychological Assessments." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 10, no. 5 (2022): 1–5. https://doi.org/10.5281/zenodo.14951390.

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Formerly, mental health interventions mainly involved a universal treatment plan but, with the aid of Generative AI (Gen AI) technology, there is hope to gain an individualized treatment plan. Employing Generative AI especially Large Language Models (LLMs), it is very much possible to scan through huge data from psychological tests, historical background, and behavioural trends to come up with personalized management solutions, therapeutic framework, and even artificial intelligence-based mental health care solutions. These AI systems can learn user’s learning needs and change the interv

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P, Jayavardhini. "AI Study Partner : Development of an LLM and Gen AI-Enhanced Study Assistant Tool." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 03 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem29626.

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In recent years, Generative AI has started to play a pivotal role in transforming the educational landscape, making learning more personalized, engaging, and accessible. Unlike traditional educational tools, Gen AI can adapt to each student's unique learning style and pace, offering customized support that can significantly enhance understanding and retention of information. It enables the creation of intelligent tutoring systems, interactive study aids, and personalized learning experiences that can assess and respond to individual needs in real time This paper introduces the AI Study Partner

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A M, Vandana Pranavi, and Dr Nagaraj G. Cholli. "Comprehensive Survey On Generative AI, Plethora Of Applications And Impacts." IOSR Journal of Computer Engineering 26, no. 5 (2024): 06–15. http://dx.doi.org/10.9790/0661-2605020615.

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The primary objective for the AI subfield of "generative artificial intelligence" is to develop systems that may produce new, novel and creative content including text, photos, audio, music, and movies. These models are able to generate fresh content that nearly mimics realistic content created by humans by utilizing deep learning techniques. These models of Gen AI have gained significant importance in research and have plethora of applications in wide varieties of fields. The impact of GenAI is not just on abled but also on disabled communities who are sometimes unnoticed. This survey provide

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Poolsombat, Phapawee, and Pinanta Chatwattana. "The Inquiry Based Learning Platform with Generative Artificial Intelligence to Promote Remembering and Understanding Skills for Dental Public Health Students." Journal of Education and Learning 14, no. 4 (2025): 35. https://doi.org/10.5539/jel.v14n4p35.

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The objective of this research is to develop the architecture of the inquiry based learning platform with Generative AI (IBL platform with Gen-AI) in order to promote remembering and understanding skills for dental public health students. The platform developed in this research is based mainly on the principles of inquiry based learning, which consists of five steps (i.e., engagement, exploration, explanation, elaboration, and evaluation), combined with the technology of Generative AI. Thus, the platform herein is capable of creating new and unprecedented contents by means of the learning styl

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Argi Rahmadi, Muhammad, Dimas Ujang Susilo, Retno Widyani, and Djohan Rochanda Wiradinata. "THE USE OF GENERATIVE ARTIFICIAL INTELLIGENCE (AI) FOR UNIVERSITY STUDENTS." Jurnal Abdisci 2, no. 4 (2025): 142–53. https://doi.org/10.62885/abdisci.v2i4.610.

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Background. The development of information technology has been very rapid lately. Aims. Artificial intelligence has replaced the function of the human brain in collecting and processing data. This is very useful in making it easier for students to compile scientific papers and complete the final project through reports and theses. Counseling has been carried out for students to understand the important role and obstacles that must be watched out for in using AI technology. Method. The method used is a PowerPoint presentation, which is done by the student group and accompanied by a lecturer as

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Sakirin, Tam, and Siddartha Kusuma. "A Survey of Generative Artificial Intelligence Techniques." Babylonian Journal of Artificial Intelligence 2023 (March 10, 2023): 10–14. http://dx.doi.org/10.58496/bjai/2023/003.

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Generative artificial intelligence (AI) refers to algorithms capable of creating novel, realistic digital content autonomously. Recently, generative models have attained groundbreaking results in domains like image and audio synthesis, spurring vast interest in the field. This paper surveys the landscape of modern techniques powering the rise of creative AI systems. We structurally examine predominant algorithmic approaches including generative adversarial networks (GANs), variational autoencoders (VAEs), and autoregressive models. Architectural innovations and illustrations of generated outpu

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A1, Kiruthika. "Exploring the Generation of Multimedia Teaching Aids Using Gen-AI." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem50931.

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This study investigates the expanding role of generative artificial intelligence (AI) in shaping modern multimedia teaching tools. Advanced models like GPT-4, DALL·E, and Stable Diffusion now facilitate the automated creation of diverse educational content such as text, images, audio, and video. These multimodal materials are designed to engage learners across multiple sensory modalities, thereby reducing cognitive overload in alignment with cognitive load theory. A prominent case examined in this work is the use of generative AI to produce situational videos for Chinese poetry, where abstract

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Întorsureanu, Iulian, Simona-Vasilica Oprea, Adela Bâra, and Dragoș Vespan. "Generative AI in Education: Perspectives Through an Academic Lens." Electronics 14, no. 5 (2025): 1053. https://doi.org/10.3390/electronics14051053.

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In this paper, we investigated the role of generative AI in education in academic publications extracted from Web of Science (3506 records; 2019–2024). The proposed methodology included three main streams: (1) Monthly analysis trends; top-ranking research areas, keywords and universities; frequency of keywords over time; a keyword co-occurrence map; collaboration networks; and a Sankey diagram illustrating the relationship between AI-related terms, publication years and research areas; (2) Sentiment analysis using a custom list of words, VADER and TextBlob; (3) Topic modeling using Latent Diri

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Khlaif, Zuheir N., Wejdan Awadallah Alkouk, Nisreen Salama, and Belal Abu Eideh. "Redesigning Assessments for AI-Enhanced Learning: A Framework for Educators in the Generative AI Era." Education Sciences 15, no. 2 (2025): 174. https://doi.org/10.3390/educsci15020174.

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The emergence of generative artificial intelligence (Gen AI) in education offers both opportunities and challenges, particularly in the context of student assessment. This study examines faculty members’ motivations to redesign assessments for their courses in the Gen AI era and introduces a framework for this purpose. A qualitative methodology was employed, gathering data through semi-structured interviews and focus groups, along with examples of redesigned assessments. Sixty-one faculty members participated in the study, and the data were analyzed using both deductive and inductive thematic

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