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class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 37</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: chatgpt</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">37</span> ChatGPT</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Solaf%20Badahman">Solaf Badahman</a>, <a href="https://publications.waset.org/abstracts/search?q=Wala%20Alasbahi"> Wala Alasbahi</a>, <a href="https://publications.waset.org/abstracts/search?q=Wajan%20Bamehraz"> Wajan Bamehraz</a>, <a href="https://publications.waset.org/abstracts/search?q=Hiba%20Nawwab"> Hiba Nawwab</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research delves into ChatGPT, OpenAI’s leading conversational AI, exploring its journey from early language models to the cutting-edge GPT-4. A survey of 35 users highlights ChatGPT’s strengths in creative writing, summarization, and user engagement while revealing areas for enhancement, particularly in technical tasks. Through scenario-based testing and direct feedback, this study uncovers ChatGPT’s real-world impact, examining its accuracy, privacy, and versatility. Positioned in a competitive landscape, ChatGPT emerges as a powerful, evolving tool for education, creativity, and problem-solving. This research offers a concise snapshot of AI’s growing role in shaping the future of human-AI interaction. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=AI" title="AI">AI</a>, <a href="https://publications.waset.org/abstracts/search?q=NLP" title=" NLP"> NLP</a>, <a href="https://publications.waset.org/abstracts/search?q=ChatGPT" title=" ChatGPT"> ChatGPT</a>, <a href="https://publications.waset.org/abstracts/search?q=conversational%20AI" title=" conversational AI"> conversational AI</a>, <a href="https://publications.waset.org/abstracts/search?q=human%E2%80%93AI%20interaction" title=" human–AI interaction"> human–AI interaction</a> </p> <a href="https://publications.waset.org/abstracts/196270/chatgpt" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/196270.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">18</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">36</span> Integrating ChatGPT into World Language Instruction: Educators' Practices and Perceptions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mimi%20Li">Mimi Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Gouda%20Taha"> Gouda Taha</a>, <a href="https://publications.waset.org/abstracts/search?q=Flavia%20Belpoliti"> Flavia Belpoliti</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This qualitative study examines world language teachers’ practices and perceptions of integrating ChatGPT into their language instructions. The participants were enrolled in the graduate-level Applied Linguistics or Spanish program at a public southern university in the USA. They received intensive training on ChatGPT-integrated language instruction and subsequently implemented AI-driven activities in their teaching. This study addresses two research questions: 1) How do world language teachers leverage ChatGPT for world language teaching and learning? 2) What are their perceptions of ChatGPT-supported instructions? The analyses of interview transcripts and weekly reports revealed that the world language teachers referred to ChatGPT for their task designs, used ChatGPT to enhance students' writing, reading, and speaking skills, and applied ChatGPT for feedback provision and classroom-based assessments. Also, this study reported multiple advantages (e.g., conversational nature, timely problem solving, constructive feedback, knowledge co-construction) and a few challenges (e.g., false information, ethical issues) pertaining to the use of ChatGPT that the world language teachers perceived. This study provides valuable pedagogical insights on leveraging ChatGPT in L2 classes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ChatGPT" title="ChatGPT">ChatGPT</a>, <a href="https://publications.waset.org/abstracts/search?q=world%20language%20teaching" title=" world language teaching"> world language teaching</a>, <a href="https://publications.waset.org/abstracts/search?q=teacher%20perception" title=" teacher perception"> teacher perception</a>, <a href="https://publications.waset.org/abstracts/search?q=case%20study" title=" case study"> case study</a> </p> <a href="https://publications.waset.org/abstracts/199160/integrating-chatgpt-into-world-language-instruction-educators-practices-and-perceptions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/199160.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">35</span> Accuracy Analysis of the American Society of Anesthesiologists Classification Using ChatGPT</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jae%20Ni%20Jang">Jae Ni Jang</a>, <a href="https://publications.waset.org/abstracts/search?q=Young%20Uk%20Kim"> Young Uk Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Chat Generative Pre-training Transformer-3 (ChatGPT; San Francisco, California, Open Artificial Intelligence) is an artificial intelligence chatbot based on a large language model designed to generate human-like text. As the usage of ChatGPT is increasing among less knowledgeable patients, medical students, and anesthesia and pain medicine residents or trainees, we aimed to evaluate the accuracy of ChatGPT-3 responses to questions about the American Society of Anesthesiologists (ASA) classification based on patients’ underlying diseases and assess the quality of the generated responses. Methods: A total of 47 questions were submitted to ChatGPT using textual prompts. The questions were designed for ChatGPT-3 to provide answers regarding ASA classification in response to common underlying diseases frequently observed in adult patients. In addition, we created 18 questions regarding the ASA classification for pediatric patients and pregnant women. The accuracy of ChatGPT’s responses was evaluated by cross-referencing with Miller’s Anesthesia, Morgan & Mikhail’s Clinical Anesthesiology, and the American Society of Anesthesiologists’ ASA Physical Status Classification System (2020). Results: Out of the 47 questions pertaining to adults, ChatGPT -3 provided correct answers for only 23, resulting in an accuracy rate of 48.9%. Furthermore, the responses provided by ChatGPT-3 regarding children and pregnant women were mostly inaccurate, as indicated by a 28% accuracy rate (5 out of 18). Conclusions: ChatGPT provided correct responses to questions relevant to the daily clinical routine of anesthesiologists in approximately half of the cases, while the remaining responses contained errors. Therefore, caution is advised when using ChatGPT to retrieve anesthesia-related information. Although ChatGPT may not yet be suitable for clinical settings, we anticipate significant improvements in ChatGPT and other large language models in the near future. Regular assessments of ChatGPT's ASA classification accuracy are essential due to the evolving nature of ChatGPT as an artificial intelligence entity. This is especially important because ChatGPT has a clinically unacceptable rate of error and hallucination, particularly in pediatric patients and pregnant women. The methodology established in this study may be used to continue evaluating ChatGPT. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=American%20Society%20of%20Anesthesiologists" title="American Society of Anesthesiologists">American Society of Anesthesiologists</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title=" artificial intelligence"> artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=Chat%20Generative%20Pre-training%20Transformer-3" title=" Chat Generative Pre-training Transformer-3"> Chat Generative Pre-training Transformer-3</a>, <a href="https://publications.waset.org/abstracts/search?q=ChatGPT" title=" ChatGPT"> ChatGPT</a> </p> <a href="https://publications.waset.org/abstracts/186368/accuracy-analysis-of-the-american-society-of-anesthesiologists-classification-using-chatgpt" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186368.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">55</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">34</span> Testing Chat-GPT: An AI Application</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jana%20Ismail">Jana Ismail</a>, <a href="https://publications.waset.org/abstracts/search?q=Layla%20Fallatah"> Layla Fallatah</a>, <a href="https://publications.waset.org/abstracts/search?q=Maha%20Alshmaisi"> Maha Alshmaisi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> ChatGPT, a cutting-edge language model built on the GPT-3.5 architecture, has garnered attention for its profound natural language processing capabilities, holding promise for transformative applications in customer service and content creation. This study delves into ChatGPT's architecture, aiming to comprehensively understand its strengths and potential limitations. Through systematic experiments across diverse domains, such as general knowledge and creative writing, we evaluated the model's coherence, context retention, and task-specific accuracy. While ChatGPT excels in generating human-like responses and demonstrates adaptability, occasional inaccuracies and sensitivity to input phrasing were observed. The study emphasizes the impact of prompt design on output quality, providing valuable insights for the nuanced deployment of ChatGPT in conversational AI and contributing to the ongoing discourse on the evolving landscape of natural language processing in artificial intelligence. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20Inelegance" title="artificial Inelegance">artificial Inelegance</a>, <a href="https://publications.waset.org/abstracts/search?q=chatGPT" title=" chatGPT"> chatGPT</a>, <a href="https://publications.waset.org/abstracts/search?q=open%20AI" title=" open AI"> open AI</a>, <a href="https://publications.waset.org/abstracts/search?q=NLP" title=" NLP"> NLP</a> </p> <a href="https://publications.waset.org/abstracts/179027/testing-chat-gpt-an-ai-application" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/179027.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">81</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">33</span> ChatGPT as a “Foreign Language Teacher”: Attitudes of Tunisian English Language Learners</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Leila%20Najeh%20Bel%27Kiry">Leila Najeh Bel'Kiry</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Artificial intelligence (AI) brought about many language robots, with ChatGPT being the most sophisticated thanks to its human-like linguistic capabilities. This aspect raises the idea of using ChatGPT in learning foreign languages. Starting from the premise that positions ChatGPT as a mediator between the language and the leaner, functioning as a “ghost teacher" offering a peaceful and secure learning space, this study aims to explore the attitudes of Tunisian students of English towards ChatGPT as a “Foreign Language Teacher” . Forty-five students, in their third year of fundamental English at Tunisian universities and high institutes, completed a Likert scale questionnaire consisting of thirty-two items and covering various aspects of language (phonology, morphology, syntax, semantics, and pragmatics). A scale ranging from 'Strongly Disagree,' 'Disagree,' 'Undecided,' 'Agree,' to 'Strongly Agree.' is used to assess the attitudes of the participants towards the integration of ChaGPTin learning a foreign language. Results indicate generally positive attitudes towards the reliance on ChatGPT in learning foreign languages, particularly some compounds of language like syntax, phonology, and morphology. However, learners show insecurity towards ChatGPT when it comes to pragmatics and semantics, where the artificial model may fail when dealing with deeper contextual and nuanced language levels. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20language%20model" title="artificial language model">artificial language model</a>, <a href="https://publications.waset.org/abstracts/search?q=attitudes" title=" attitudes"> attitudes</a>, <a href="https://publications.waset.org/abstracts/search?q=foreign%20language%20learning" title=" foreign language learning"> foreign language learning</a>, <a href="https://publications.waset.org/abstracts/search?q=ChatGPT" title=" ChatGPT"> ChatGPT</a>, <a href="https://publications.waset.org/abstracts/search?q=linguistic%20capabilities" title=" linguistic capabilities"> linguistic capabilities</a>, <a href="https://publications.waset.org/abstracts/search?q=Tunisian%20English%20language%20learners" title=" Tunisian English language learners"> Tunisian English language learners</a> </p> <a href="https://publications.waset.org/abstracts/183529/chatgpt-as-a-foreign-language-teacher-attitudes-of-tunisian-english-language-learners" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/183529.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">69</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32</span> An Overview and Analysis of ChatGPT 3.5/4.0</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sarah%20Mohammed">Sarah Mohammed</a>, <a href="https://publications.waset.org/abstracts/search?q=Huda%20Allagany"> Huda Allagany</a>, <a href="https://publications.waset.org/abstracts/search?q=Ayah%20Barakat"> Ayah Barakat</a>, <a href="https://publications.waset.org/abstracts/search?q=Muna%20Elyas"> Muna Elyas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper delves into the history and development of ChatGPT, tracing its evolution from its inception by OpenAI to its current state, and emphasizing its design improvements and strategic partnerships. It also explores the performance and applicability of ChatGPT versions 3.5 and 4 in various contexts, examining its capabilities and limitations in producing accurate and relevant responses. Utilizing a quantitative approach, user satisfaction, speed of response, learning capabilities, and overall utility in academic performance were assessed through surveys and analysis tools. Findings indicate that while ChatGPT generally delivers high accuracy and speed in responses, the need for clarification and more specific user instructions persists. The study highlights the tool's increasing integration across different sectors, showcasing its potential in educational and professional settings. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=chat%20GPT" title=" chat GPT"> chat GPT</a>, <a href="https://publications.waset.org/abstracts/search?q=analysis" title=" analysis"> analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=education" title=" education"> education</a> </p> <a href="https://publications.waset.org/abstracts/186389/an-overview-and-analysis-of-chatgpt-3540" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186389.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">57</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">31</span> Optimizing the Readability of Orthopaedic Trauma Patient Education Materials Using ChatGPT-4</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Oscar%20Covarrubias">Oscar Covarrubias</a>, <a href="https://publications.waset.org/abstracts/search?q=Diane%20Ghanem"> Diane Ghanem</a>, <a href="https://publications.waset.org/abstracts/search?q=Christopher%20Murdock"> Christopher Murdock</a>, <a href="https://publications.waset.org/abstracts/search?q=Babar%20Shafiq"> Babar Shafiq</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: ChatGPT is an advanced language AI tool designed to understand and generate human-like text. The aim of this study is to assess the ability of ChatGPT-4 to re-write orthopaedic trauma patient education materials at the recommended 6th-grade level. Methods: Two independent reviewers accessed ChatGPT-4 (chat.openai.com) and gave identical instructions to simplify the readability of provided text to a 6th-grade level. All trauma-related articles by the Orthopaedic Trauma Association (OTA) and American Academy of Orthopaedic Surgeons (AAOS) were sequentially provided. The academic grade level was determined using the Flesh-Kincaid Grade Level (FKGL) and Flesch Reading Ease (FRE). Paired t-tests and Wilcox-rank sum tests were used to compare the FKGL and FRE between the ChatGPT-4 revised and original text. Inter-rater correlation coefficient (ICC) was used to assess variability in ChatGPT-4 generated text between the two reviewers. Results: ChatGPT-4 significantly reduced FKGL and increased FRE scores in the OTA (FKGL: 5.7±0.5 compared to the original 8.2±1.1, FRE: 76.4±5.7 compared to the original 65.5±6.6, p < 0.001) and AAOS articles (FKGL: 5.8±0.8 compared to the original 8.9±0.8, FRE: 76±5.5 compared to the original 56.7±5.9, p < 0.001). On average, 14.6% of OTA and 28.6% of AAOS articles required at least two revisions by ChatGPT-4 to achieve a 6th-grade reading level. ICC demonstrated poor reliability for FKGL (OTA 0.24, AAOS 0.45) and moderate reliability for FRE (OTA 0.61, AAOS 0.73). Conclusion: This study provides a novel, simple and efficient method using language AI to optimize the readability of patient education content which may only require the surgeon’s final proofreading. This method would likely be as effective for other medical specialties. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=AI" title=" AI"> AI</a>, <a href="https://publications.waset.org/abstracts/search?q=chatGPT" title=" chatGPT"> chatGPT</a>, <a href="https://publications.waset.org/abstracts/search?q=patient%20education" title=" patient education"> patient education</a>, <a href="https://publications.waset.org/abstracts/search?q=readability" title=" readability"> readability</a>, <a href="https://publications.waset.org/abstracts/search?q=trauma%20education" title=" trauma education"> trauma education</a> </p> <a href="https://publications.waset.org/abstracts/171278/optimizing-the-readability-of-orthopaedic-trauma-patient-education-materials-using-chatgpt-4" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/171278.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">77</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30</span> The Role of ChatGPT in Enhancing ENT Surgical Training</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Laura%20Brennan">Laura Brennan</a>, <a href="https://publications.waset.org/abstracts/search?q=Ram%20Balakumar"> Ram Balakumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> ChatGPT has been developed by Open AI (Nov 2022) as a powerful artificial intelligence (AI) language model which has been designed to produce human-like text from user written prompts. To gain the most from the system, user written prompts must give context specific information. This article aims to give guidance on how to optimise the ChatGPT system in the context of education for otolaryngology. Otolaryngology is a specialist field which sees little time dedicated to providing education to both medical students and doctors. Additionally, otolaryngology trainees have seen a reduction in learning opportunities since the COVID-19 pandemic. In this article we look at these various barriers to medical education in Otolaryngology training and suggest ways that ChatGPT can overcome them and assist in simulation-based training. Examples provide how this can be achieved using the Authors’ experience to further highlight the practicalities. What this article has found is that while ChatGPT cannot replace traditional mentorship and practical surgical experience, it can serve as an invaluable supplementary resource to simulation based medical education in Otolaryngology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=otolaryngology" title=" otolaryngology"> otolaryngology</a>, <a href="https://publications.waset.org/abstracts/search?q=surgical%20training" title=" surgical training"> surgical training</a>, <a href="https://publications.waset.org/abstracts/search?q=medical%20education" title=" medical education"> medical education</a> </p> <a href="https://publications.waset.org/abstracts/166069/the-role-of-chatgpt-in-enhancing-ent-surgical-training" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/166069.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">166</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">29</span> Forecasting the Future Implications of ChatGPT Usage in Education Based on AI Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yakubu%20Bala%20Mohammed">Yakubu Bala Mohammed</a>, <a href="https://publications.waset.org/abstracts/search?q=Nadire%20Chavus"> Nadire Chavus</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Bulama"> Mohammed Bulama</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Generative Pre-trained Transformer (ChatGPT) represents an artificial intelligence (AI) tool capable of swiftly generating comprehensive responses to prompts and follow-up inquiries. This emerging AI tool was introduced in November 2022 by OpenAI firm, an American AI research laboratory, utilizing substantial language models. This present study aims to delve into the potential future consequences of ChatGPT usage in education using AI-based algorithms. The paper will bring forth the likely potential risks of ChatGBT utilization, such as academic integrity concerns, unfair learning assessments, excessive reliance on AI, and dissemination of inaccurate information using four machine learning algorithms: eXtreme-Gradient Boosting (XGBoost), Support vector machine (SVM), Emotional artificial neural network (EANN), and Random forest (RF) would be used to analyze the study collected data due to their robustness. Finally, the findings of the study will assist education stakeholders in understanding the future implications of ChatGPT usage in education and propose solutions and directions for upcoming studies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title="machine learning">machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=ChatGPT" title=" ChatGPT"> ChatGPT</a>, <a href="https://publications.waset.org/abstracts/search?q=education" title=" education"> education</a>, <a href="https://publications.waset.org/abstracts/search?q=learning" title=" learning"> learning</a>, <a href="https://publications.waset.org/abstracts/search?q=implications" title=" implications"> implications</a> </p> <a href="https://publications.waset.org/abstracts/174244/forecasting-the-future-implications-of-chatgpt-usage-in-education-based-on-ai-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/174244.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">242</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28</span> Exploring the Impact of ChatGPT on the English Writing Skills of a Group of International EFL Uzbek Students: A Qualitative Case Study Conducted at a Private University College in Malaysia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Uranus%20Saadat">Uranus Saadat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> ChatGPT, as one of the well-known artificial intelligence (AI) tools, has recently been integrated into English language education and has had several impacts on learners. Accordingly, concerns regarding the overuse of this tool among EFL/ESL learners are rising, which could lead to several disadvantages in their writing skills development. The use of ChatGPT in facilitating writing skills is a novel concept that demands further studies in different contexts and learners. In this study, a qualitative case study is applied to investigate the impact of ChatGPT on the writing skills of a group of EFL bachelor’s students from Uzbekistan studying Teaching English as the Second Language (TESL) at a private university in Malaysia. The data was collected through the triangulation of document analysis, semi-structured interviews, classroom observations, and focus group discussions. Subsequently, the data was analyzed by using thematic analysis. Some of the emerging themes indicated that ChatGPT is helpful in engaging students by reducing their anxiety in class and providing them with constructive feedback and support. Conversely, certain emerging themes revealed excessive reliance on ChatGPT, resulting in a decrease in students’ creativity and critical thinking skills, memory span, and tolerance for ambiguity. The study suggests a number of strategies to alleviate its negative impacts, such as peer review activities, workshops for familiarizing students with AI, and gradual withdrawal of AI support activities. This study emphasizes the need for cautious AI integration into English language education to cultivate independent learners with higher-order thinking skills. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ChatGPT" title="ChatGPT">ChatGPT</a>, <a href="https://publications.waset.org/abstracts/search?q=EFL%2FESL%20learners" title=" EFL/ESL learners"> EFL/ESL learners</a>, <a href="https://publications.waset.org/abstracts/search?q=English%20writing%20skills" title=" English writing skills"> English writing skills</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence%20tools" title=" artificial intelligence tools"> artificial intelligence tools</a>, <a href="https://publications.waset.org/abstracts/search?q=critical%20thinking%20skills" title=" critical thinking skills"> critical thinking skills</a> </p> <a href="https://publications.waset.org/abstracts/192637/exploring-the-impact-of-chatgpt-on-the-english-writing-skills-of-a-group-of-international-efl-uzbek-students-a-qualitative-case-study-conducted-at-a-private-university-college-in-malaysia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/192637.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">39</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">27</span> ChatGPT Performs at the Level of a Third-Year Orthopaedic Surgery Resident on the Orthopaedic In-training Examination</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Diane%20Ghanem">Diane Ghanem</a>, <a href="https://publications.waset.org/abstracts/search?q=Oscar%20Covarrubias"> Oscar Covarrubias</a>, <a href="https://publications.waset.org/abstracts/search?q=Michael%20Raad"> Michael Raad</a>, <a href="https://publications.waset.org/abstracts/search?q=Dawn%20LaPorte"> Dawn LaPorte</a>, <a href="https://publications.waset.org/abstracts/search?q=Babar%20Shafiq"> Babar Shafiq</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Standardized exams have long been considered a cornerstone in measuring cognitive competency and academic achievement. Their fixed nature and predetermined scoring methods offer a consistent yardstick for gauging intellectual acumen across diverse demographics. Consequently, the performance of artificial intelligence (AI) in this context presents a rich, yet unexplored terrain for quantifying AI's understanding of complex cognitive tasks and simulating human-like problem-solving skills. Publicly available AI language models such as ChatGPT have demonstrated utility in text generation and even problem-solving when provided with clear instructions. Amidst this transformative shift, the aim of this study is to assess ChatGPT’s performance on the orthopaedic surgery in-training examination (OITE). Methods: All 213 OITE 2021 web-based questions were retrieved from the AAOS-ResStudy website. Two independent reviewers copied and pasted the questions and response options into ChatGPT Plus (version 4.0) and recorded the generated answers. All media-containing questions were flagged and carefully examined. Twelve OITE media-containing questions that relied purely on images (clinical pictures, radiographs, MRIs, CT scans) and could not be rationalized from the clinical presentation were excluded. Cohen’s Kappa coefficient was used to examine the agreement of ChatGPT-generated responses between reviewers. Descriptive statistics were used to summarize the performance (% correct) of ChatGPT Plus. The 2021 norm table was used to compare ChatGPT Plus’ performance on the OITE to national orthopaedic surgery residents in that same year. Results: A total of 201 were evaluated by ChatGPT Plus. Excellent agreement was observed between raters for the 201 ChatGPT-generated responses, with a Cohen’s Kappa coefficient of 0.947. 45.8% (92/201) were media-containing questions. ChatGPT had an average overall score of 61.2% (123/201). Its score was 64.2% (70/109) on non-media questions. When compared to the performance of all national orthopaedic surgery residents in 2021, ChatGPT Plus performed at the level of an average PGY3. Discussion: ChatGPT Plus is able to pass the OITE with a satisfactory overall score of 61.2%, ranking at the level of third-year orthopaedic surgery residents. More importantly, it provided logical reasoning and justifications that may help residents grasp evidence-based information and improve their understanding of OITE cases and general orthopaedic principles. With further improvements, AI language models, such as ChatGPT, may become valuable interactive learning tools in resident education, although further studies are still needed to examine their efficacy and impact on long-term learning and OITE/ABOS performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=ChatGPT" title=" ChatGPT"> ChatGPT</a>, <a href="https://publications.waset.org/abstracts/search?q=orthopaedic%20in-training%20examination" title=" orthopaedic in-training examination"> orthopaedic in-training examination</a>, <a href="https://publications.waset.org/abstracts/search?q=OITE" title=" OITE"> OITE</a>, <a href="https://publications.waset.org/abstracts/search?q=orthopedic%20surgery" title=" orthopedic surgery"> orthopedic surgery</a>, <a href="https://publications.waset.org/abstracts/search?q=standardized%20testing" title=" standardized testing"> standardized testing</a> </p> <a href="https://publications.waset.org/abstracts/171275/chatgpt-performs-at-the-level-of-a-third-year-orthopaedic-surgery-resident-on-the-orthopaedic-in-training-examination" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/171275.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">103</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">26</span> Addressing Time Constraints and Subjectivity in Writing Assessment: The Transformative Role of ChatGPT in Higher Education</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Swathi%20Mulinti">Swathi Mulinti</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Artificial Intelligence (AI) tools, such as ChatGPT, address critical challenges in higher education, particularly the issues of time constraints and subjectivity in writing assessments. In a fast-paced academic environment, educators often face limited time to provide detailed feedback and consistently evaluate students' work. This paper explores how integrating ChatGPT as a pedagogical tool can alleviate these challenges by enhancing and streamlining teaching and assessment processes. First, we examine how ChatGPT supports students in developing critical writing competencies through instant feedback on grammar, coherence, and argumentation. By offering personalized prompts and real-time suggestions, the tool fosters an iterative writing process, encouraging students to refine their drafts and build confidence in their skills. Second, this study investigates ChatGPT's potential to reduce subjectivity in writing assessment. The study utilizes the IELTS Writing Band Descriptors as the rubric for assessing student writing and evaluating parameters such as task achievement, coherence and cohesion, lexical resource, and grammatical accuracy. This standardized and globally recognized rubric ensures consistency in evaluation while aligning the study with academic and professional benchmarks. The findings highlight how ChatGPT leverages the descriptors to provide precise and actionable feedback, further validating the rubric's applicability for assessing academic writing in diverse higher education contexts. This systematic approach mitigates inconsistencies in grading, providing educators with a reliable and efficient alternative to traditional methods. Through a mixed-methods study, this research analyzes performance data, student surveys, and educator feedback to assess the effectiveness of ChatGPT in improving writing outcomes and reducing workload. The findings highlight how integrating ChatGPT into the curriculum enhances learner autonomy and promotes equitable and data-driven assessment practices. By addressing time constraints and subjectivity, this study underscores the transformative role of AI in advancing educational practices in the digital age. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=writing%20assessment" title="writing assessment">writing assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=ChatGPT" title=" ChatGPT"> ChatGPT</a>, <a href="https://publications.waset.org/abstracts/search?q=critical%20writing%20competencies" title=" critical writing competencies"> critical writing competencies</a>, <a href="https://publications.waset.org/abstracts/search?q=rubric-based%20analysis" title=" rubric-based analysis"> rubric-based analysis</a> </p> <a href="https://publications.waset.org/abstracts/196847/addressing-time-constraints-and-subjectivity-in-writing-assessment-the-transformative-role-of-chatgpt-in-higher-education" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/196847.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">12</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25</span> The Impact of ChatGPT on the Healthcare Domain: Perspectives from Healthcare Majors</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Su%20Yen%20Chen">Su Yen Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> ChatGPT has shown both strengths and limitations in clinical, educational, and research settings, raising important concerns about accuracy, transparency, and ethical use. Despite an improved understanding of user acceptance and satisfaction, there is still a gap in how general AI perceptions translate into practical applications within healthcare. This study focuses on examining the perceptions of ChatGPT's impact among 266 healthcare majors in Taiwan, exploring its implications for their career development, as well as its utility in clinical practice, medical education, and research. By employing a structured survey with precisely defined subscales, this research aims to probe the breadth of ChatGPT's applications within healthcare, assessing both the perceived benefits and the challenges it presents. Additionally, to further enhance the comprehensiveness of our methodology, we have incorporated qualitative data collection methods, which provide complementary insights to the quantitative findings. The findings from the survey reveal that perceptions and usage of ChatGPT among healthcare majors vary significantly, influenced by factors such as its perceived utility, risk, novelty, and trustworthiness. Graduate students and those who perceive ChatGPT as more beneficial and less risky are particularly inclined to use it more frequently. This increased usage is closely linked to significant impacts on personal career development. Furthermore, ChatGPT's perceived usefulness and novelty contribute to its broader impact within the healthcare domain, suggesting that both innovation and practical utility are key drivers of acceptance and perceived effectiveness in professional healthcare settings. Trust emerges as an important factor, especially in clinical settings where the stakes are high. The trust that healthcare professionals place in ChatGPT significantly affects its integration into clinical practice and influences outcomes in medical education and research. The reliability and practical value of ChatGPT are thus critical for its successful adoption in these areas. However, an interesting paradox arises with regard to the ease of use. While making ChatGPT more user-friendly is generally seen as beneficial, it also raises concerns among users who have lower levels of trust and perceive higher risks associated with its use. This complex interplay between ease of use and safety concerns necessitates a careful balance, highlighting the need for robust security measures and clear, transparent communication about how AI systems work and their limitations. The study suggests several strategic approaches to enhance the adoption and integration of AI in healthcare. These include targeted training programs for healthcare professionals to increase familiarity with AI technologies, reduce perceived risks, and build trust. Ensuring transparency and conducting rigorous testing are also vital to foster trust and reliability. Moreover, comprehensive policy frameworks are needed to guide the implementation of AI technologies, ensuring high standards of patient safety, privacy, and ethical use. These measures are crucial for fostering broader acceptance of AI in healthcare, as the study contributes to enriching the discourse on AI's role by detailing how various factors affect its adoption and impact. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ChatGPT" title="ChatGPT">ChatGPT</a>, <a href="https://publications.waset.org/abstracts/search?q=healthcare" title=" healthcare"> healthcare</a>, <a href="https://publications.waset.org/abstracts/search?q=survey%20study" title=" survey study"> survey study</a>, <a href="https://publications.waset.org/abstracts/search?q=IT%20adoption" title=" IT adoption"> IT adoption</a>, <a href="https://publications.waset.org/abstracts/search?q=behaviour" title=" behaviour"> behaviour</a>, <a href="https://publications.waset.org/abstracts/search?q=applcation" title=" applcation"> applcation</a>, <a href="https://publications.waset.org/abstracts/search?q=concerns" title=" concerns"> concerns</a> </p> <a href="https://publications.waset.org/abstracts/187420/the-impact-of-chatgpt-on-the-healthcare-domain-perspectives-from-healthcare-majors" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/187420.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">39</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">24</span> Dogmatic Analysis of Legal Risks of Using Artificial Intelligence: The European Union and Polish Perspective</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Marianna%20Iaroslavska">Marianna Iaroslavska</a> </p> <p class="card-text"><strong>Abstract:</strong></p> ChatGPT is becoming commonplace. However, only a few people think about the legal risks of using Large Language Model in their daily work. The main dilemmas concern the following areas: who owns the copyright to what somebody creates through ChatGPT; what can OpenAI do with the prompt you enter; can you accidentally infringe on another creator's rights through ChatGPT; what about the protection of the data somebody enters into the chat. This paper will present these and other legal risks of using large language models at work using dogmatic methods and case studies. The paper will present a legal analysis of AI risks against the background of European Union law and Polish law. This analysis will answer questions about how to protect data, how to make sure you do not violate copyright, and what is at stake with the AI Act, which recently came into force in the EU. If your work is related to the EU area, and you use AI in your work, this paper will be a real goldmine for you. The copyright law in force in Poland does not protect your rights to a work that is created with the help of AI. So if you start selling such a work, you may face two main problems. First, someone may steal your work, and you will not be entitled to any protection because work created with AI does not have any legal protection. Second, the AI may have created the work by infringing on another person's copyright, so they will be able to claim damages from you. In addition, the EU's current AI Act imposes a number of additional obligations related to the use of large language models. The AI Act divides artificial intelligence into four risk levels and imposes different requirements depending on the level of risk. The EU regulation is aimed primarily at those developing and marketing artificial intelligence systems in the EU market. In addition to the above obstacles, personal data protection comes into play, which is very strictly regulated in the EU. If you violate personal data by entering information into ChatGPT, you will be liable for violations. When using AI within the EU or in cooperation with entities located in the EU, you have to take into account a lot of risks. This paper will highlight such risks and explain how they can be avoided. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=EU" title="EU">EU</a>, <a href="https://publications.waset.org/abstracts/search?q=AI%20act" title=" AI act"> AI act</a>, <a href="https://publications.waset.org/abstracts/search?q=copyright" title=" copyright"> copyright</a>, <a href="https://publications.waset.org/abstracts/search?q=polish%20law" title=" polish law"> polish law</a>, <a href="https://publications.waset.org/abstracts/search?q=LLM" title=" LLM"> LLM</a> </p> <a href="https://publications.waset.org/abstracts/191311/dogmatic-analysis-of-legal-risks-of-using-artificial-intelligence-the-european-union-and-polish-perspective" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191311.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">28</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">23</span> ChatGPT 4.0 Demonstrates Strong Performance in Standardised Medical Licensing Examinations: Insights and Implications for Medical Educators</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=K.%20O%27Malley">K. O'Malley</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: The emergence and rapid evolution of large language models (LLMs) (i.e., models of generative artificial intelligence, or AI) has been unprecedented. ChatGPT is one of the most widely used LLM platforms. Using natural language processing technology, it generates customized responses to user prompts, enabling it to mimic human conversation. Responses are generated using predictive modeling of vast internet text and data swathes and are further refined and reinforced through user feedback. The popularity of LLMs is increasing, with a growing number of students utilizing these platforms for study and revision purposes. Notwithstanding its many novel applications, LLM technology is inherently susceptible to bias and error. This poses a significant challenge in the educational setting, where academic integrity may be undermined. This study aims to evaluate the performance of the latest iteration of ChatGPT (ChatGPT4.0) in standardized state medical licensing examinations. Methods: A considered search strategy was used to interrogate the PubMed electronic database. The keywords ‘ChatGPT’ AND ‘medical education’ OR ‘medical school’ OR ‘medical licensing exam’ were used to identify relevant literature. The search included all peer-reviewed literature published in the past five years. The search was limited to publications in the English language only. Eligibility was ascertained based on the study title and abstract and confirmed by consulting the full-text document. Data was extracted into a Microsoft Excel document for analysis. Results: The search yielded 345 publications that were screened. 225 original articles were identified, of which 11 met the pre-determined criteria for inclusion in a narrative synthesis. These studies included performance assessments in national medical licensing examinations from the United States, United Kingdom, Saudi Arabia, Poland, Taiwan, Japan and Germany. ChatGPT 4.0 achieved scores ranging from 67.1 to 88.6 percent. The mean score across all studies was 82.49 percent (SD= 5.95). In all studies, ChatGPT exceeded the threshold for a passing grade in the corresponding exam. Conclusion: The capabilities of ChatGPT in standardized academic assessment in medicine are robust. While this technology can potentially revolutionize higher education, it also presents several challenges with which educators have not had to contend before. The overall strong performance of ChatGPT, as outlined above, may lend itself to unfair use (such as the plagiarism of deliverable coursework) and pose unforeseen ethical challenges (arising from algorithmic bias). Conversely, it highlights potential pitfalls if users assume LLM-generated content to be entirely accurate. In the aforementioned studies, ChatGPT exhibits a margin of error between 11.4 and 32.9 percent, which resonates strongly with concerns regarding the quality and veracity of LLM-generated content. It is imperative to highlight these limitations, particularly to students in the early stages of their education who are less likely to possess the requisite insight or knowledge to recognize errors, inaccuracies or false information. Educators must inform themselves of these emerging challenges to effectively address them and mitigate potential disruption in academic fora. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=ChatGPT" title=" ChatGPT"> ChatGPT</a>, <a href="https://publications.waset.org/abstracts/search?q=generative%20ai" title=" generative ai"> generative ai</a>, <a href="https://publications.waset.org/abstracts/search?q=large%20language%20models" title=" large language models"> large language models</a>, <a href="https://publications.waset.org/abstracts/search?q=licensing%20exam" title=" licensing exam"> licensing exam</a>, <a href="https://publications.waset.org/abstracts/search?q=medical%20education" title=" medical education"> medical education</a>, <a href="https://publications.waset.org/abstracts/search?q=medicine" title=" medicine"> medicine</a>, <a href="https://publications.waset.org/abstracts/search?q=university" title=" university"> university</a> </p> <a href="https://publications.waset.org/abstracts/188392/chatgpt-40-demonstrates-strong-performance-in-standardised-medical-licensing-examinations-insights-and-implications-for-medical-educators" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/188392.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">40</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22</span> Identifying Confirmed Resemblances in Problem-Solving Engineering, Both in the Past and Present</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Colin%20Schmidt">Colin Schmidt</a>, <a href="https://publications.waset.org/abstracts/search?q=Adrien%20Lecossier"> Adrien Lecossier</a>, <a href="https://publications.waset.org/abstracts/search?q=Pascal%20Crubleau"> Pascal Crubleau</a>, <a href="https://publications.waset.org/abstracts/search?q=Philippe%20Blanchard"> Philippe Blanchard</a>, <a href="https://publications.waset.org/abstracts/search?q=Simon%20Richir"> Simon Richir</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction:The widespread availability of artificial intelligence, exemplified by Generative Pre-trained Transformers (GPT) relying on large language models (LLM), has caused a seismic shift in the realm of knowledge. Everyone now has the capacity to swiftly learn how these models can either serve them well or not. Today, conversational AI like ChatGPT is grounded in neural transformer models, a significant advance in natural language processing facilitated by the emergence of renowned LLMs constructed using neural transformer architecture. Inventiveness of an LLM : OpenAI's GPT-3 stands as a premier LLM, capable of handling a broad spectrum of natural language processing tasks without requiring fine-tuning, reliably producing text that reads as if authored by humans. However, even with an understanding of how LLMs respond to questions asked, there may be lurking behind OpenAI’s seemingly endless responses an inventive model yet to be uncovered. There may be some unforeseen reasoning emerging from the interconnection of neural networks here. Just as a Soviet researcher in the 1940s questioned the existence of Common factors in inventions, enabling an Under standing of how and according to what principles humans create them, it is equally legitimate today to explore whether solutions provided by LLMs to complex problems also share common denominators. Theory of Inventive Problem Solving (TRIZ) : We will revisit some fundamentals of TRIZ and how Genrich ALTSHULLER was inspired by the idea that inventions and innovations are essential means to solve societal problems. It's crucial to note that traditional problem-solving methods often fall short in discovering innovative solutions. The design team is frequently hampered by psychological barriers stemming from confinement within a highly specialized knowledge domain that is difficult to question. We presume ChatGPT Utilizes TRIZ 40. Hence, the objective of this research is to decipher the inventive model of LLMs, particularly that of ChatGPT, through a comparative study. This will enhance the efficiency of sustainable innovation processes and shed light on how the construction of a solution to a complex problem was devised. Description of the Experimental Protocol : To confirm or reject our main hypothesis that is to determine whether ChatGPT uses TRIZ, we will follow a stringent protocol that we will detail, drawing on insights from a panel of two TRIZ experts. Conclusion and Future Directions : In this endeavor, we sought to comprehend how an LLM like GPT addresses complex challenges. Our goal was to analyze the inventive model of responses provided by an LLM, specifically ChatGPT, by comparing it to an existing standard model: TRIZ 40. Of course, problem solving is our main focus in our endeavours. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=Triz" title=" Triz"> Triz</a>, <a href="https://publications.waset.org/abstracts/search?q=ChatGPT" title=" ChatGPT"> ChatGPT</a>, <a href="https://publications.waset.org/abstracts/search?q=inventiveness" title=" inventiveness"> inventiveness</a>, <a href="https://publications.waset.org/abstracts/search?q=problem-solving" title=" problem-solving"> problem-solving</a> </p> <a href="https://publications.waset.org/abstracts/176746/identifying-confirmed-resemblances-in-problem-solving-engineering-both-in-the-past-and-present" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/176746.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">81</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">21</span> Harnessing the Power of Large Language Models in Orthodontics: AI-Generated Insights on Class II and Class III Orthopedic Appliances: A Cross-Sectional Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Laiba%20Amin">Laiba Amin</a>, <a href="https://publications.waset.org/abstracts/search?q=Rashna%20H.%20Sukhia"> Rashna H. Sukhia</a>, <a href="https://publications.waset.org/abstracts/search?q=Mubassar%20Fida"> Mubassar Fida</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: This study evaluates the accuracy of responses from ChatGPT, Google Bard, and Microsoft Copilot regarding dentofacial orthopedic appliances. As artificial intelligence (AI) increasingly enhances various fields, including healthcare, understanding its reliability in specialized domains like orthodontics becomes crucial. By comparing the accuracy of different AI models, this study aims to shed light on their effectiveness and potential limitations in providing technical insights. Materials and Methods: A total of 110 questions focused on dentofacial orthopedic appliances were posed to each AI model. The responses were then evaluated by five experienced orthodontists using a modified 5-point Likert scale to ensure a thorough assessment of accuracy. This structured approach allowed for consistent and objective rating, facilitating a meaningful comparison between the AI systems. Results: The results revealed that Google Bard demonstrated the highest accuracy at 74%, followed by Microsoft Copilot, with an accuracy of 72.2%. In contrast, ChatGPT was found to be the least accurate, achieving only 52.2%. These results highlight significant differences in the performance of the AI models when addressing orthodontic queries. Conclusions: Our study highlights the need for caution in relying on AI for orthodontic insights. The overall accuracy of the three chatbots was 66%, with Google Bard performing best for removable Class II appliances. Microsoft Copilot was more accurate than ChatGPT, which, despite its popularity, was the least accurate. This variability emphasizes the importance of human expertise in interpreting AI-generated information. Further research is necessary to improve the reliability of AI models in specialized healthcare settings. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=large%20language%20models" title=" large language models"> large language models</a>, <a href="https://publications.waset.org/abstracts/search?q=orthodontics" title=" orthodontics"> orthodontics</a>, <a href="https://publications.waset.org/abstracts/search?q=dentofacial%20orthopaedic%20appliances" title=" dentofacial orthopaedic appliances"> dentofacial orthopaedic appliances</a>, <a href="https://publications.waset.org/abstracts/search?q=accuracy%20assessment." title=" accuracy assessment."> accuracy assessment.</a> </p> <a href="https://publications.waset.org/abstracts/194596/harnessing-the-power-of-large-language-models-in-orthodontics-ai-generated-insights-on-class-ii-and-class-iii-orthopedic-appliances-a-cross-sectional-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/194596.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">26</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20</span> TutorBot+: Automatic Programming Assistant with Positive Feedback based on LLMs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Claudia%20Mart%C3%ADnez-Araneda">Claudia Martínez-Araneda</a>, <a href="https://publications.waset.org/abstracts/search?q=Mariella%20Guti%C3%A9rrez"> Mariella Gutiérrez</a>, <a href="https://publications.waset.org/abstracts/search?q=Pedro%20G%C3%B3mez"> Pedro Gómez</a>, <a href="https://publications.waset.org/abstracts/search?q=Diego%20Maldonado"> Diego Maldonado</a>, <a href="https://publications.waset.org/abstracts/search?q=Alejandra%20Segura"> Alejandra Segura</a>, <a href="https://publications.waset.org/abstracts/search?q=Christian%20Vidal-Castro"> Christian Vidal-Castro</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of this document is to showcase the preliminary work in developing an EduChatbot-type tool and measuring the effects of its use aimed at providing effective feedback to students in programming courses. This bot, hereinafter referred to as tutorBot+, was constructed based on chatGPT and is tasked with assisting and delivering timely positive feedback to students in the field of computer science at the Universidad Católica de Concepción. The proposed working method consists of four stages: (1) Immersion in the domain of Large Language Models (LLMs), (2) Development of the tutorBot+ prototype and integration, (3) Experiment design, and (4) Intervention. The first stage involves a literature review on the use of artificial intelligence in education and the evaluation of intelligent tutors, as well as research on types of feedback for learning and the domain of chatGPT. The second stage encompasses the development of tutorBot+, and the final stage involves a quasi-experimental study with students from the Programming and Database labs, where the learning outcome involves the development of computational thinking skills, enabling the use and measurement of the tool's effects. The preliminary results of this work are promising, as a functional chatBot prototype has been developed in both conversational and non-conversational versions integrated into an open-source online judge and programming contest platform system. There is also an exploration of the possibility of generating a custom model based on a pre-trained one tailored to the domain of programming. This includes the integration of the created tool and the design of the experiment to measure its utility. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=assessment" title="assessment">assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=chatGPT" title=" chatGPT"> chatGPT</a>, <a href="https://publications.waset.org/abstracts/search?q=learning%20strategies" title=" learning strategies"> learning strategies</a>, <a href="https://publications.waset.org/abstracts/search?q=LLMs" title=" LLMs"> LLMs</a>, <a href="https://publications.waset.org/abstracts/search?q=timely%20feedback" title=" timely feedback"> timely feedback</a> </p> <a href="https://publications.waset.org/abstracts/172610/tutorbot-automatic-programming-assistant-with-positive-feedback-based-on-llms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/172610.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">73</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19</span> Qualitative Analysis of User Experiences and Needs for Educational Chatbots in Higher Education</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Felix%20Golla">Felix Golla</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In an era where technology increasingly intersects with education, the potential of chatbots and ChatGPT agents in enhancing student learning experiences in higher education is both significant and timely. This study explores the integration of these AI-driven tools in educational settings, emphasizing their design and functionality to meet the specific needs of students. Recognizing the gap in literature concerning student-centered AI applications in education, this research offers valuable insights into the role and efficacy of chatbots and ChatGPT agents as educational tools. Employing qualitative research methodologies, the study involved conducting semi-structured interviews with university students. These interviews were designed to gather in-depth insights into the students' experiences and expectations regarding the use of AI in learning environments. The High-Performance Cycle Model, renowned for its focus on goal setting and motivation, served as the theoretical framework guiding the analysis. This model helped in systematically categorizing and interpreting the data, revealing the nuanced perceptions and preferences of students regarding AI tools in education. The major findings of the study indicate a strong preference among students for chatbots and ChatGPT agents that offer personalized interaction, adaptive learning support, and regular, constructive feedback. These features were deemed essential for enhancing student engagement, motivation, and overall learning outcomes. Furthermore, the study revealed that students perceive these AI tools not just as passive sources of information but as active facilitators in the learning process, capable of adapting to individual learning styles and needs. In conclusion, this study underscores the transformative potential of chatbots and ChatGPT agents in higher education. It highlights the need for these AI tools to be designed with a student-centered approach, ensuring their alignment with educational objectives and student preferences. The findings contribute to the evolving discourse on AI in education, suggesting a paradigm shift towards more interactive, responsive, and personalized learning experiences. This research not only informs educators and technologists about the desirable features of educational chatbots but also opens avenues for future studies to explore the long-term impact of AI integration in academic curricula. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chatbot%20design%20in%20education" title="chatbot design in education">chatbot design in education</a>, <a href="https://publications.waset.org/abstracts/search?q=high-performance%20cycle%20model%20application" title=" high-performance cycle model application"> high-performance cycle model application</a>, <a href="https://publications.waset.org/abstracts/search?q=qualitative%20research%20in%20AI" title=" qualitative research in AI"> qualitative research in AI</a>, <a href="https://publications.waset.org/abstracts/search?q=student-centered%20learning%20technologies" title=" student-centered learning technologies"> student-centered learning technologies</a> </p> <a href="https://publications.waset.org/abstracts/178903/qualitative-analysis-of-user-experiences-and-needs-for-educational-chatbots-in-higher-education" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/178903.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">73</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18</span> Investigating Best Strategies Towards Creating Alternative Assessment in Literature</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sandhya%20Rao%20Mehta">Sandhya Rao Mehta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As ChatGpt and other Artificial Intelligence (AI) forms are becoming part of our regular academic world, the consequences are being gradually discussed. The extent to which an essay written by a student is itself of any value if it has been downloaded by some form of AI is perhaps central to this discourse. A larger question is whether writing should be taught as an academic skill at all. In literature classrooms, this has major consequences as writing a traditional paper is still the single most preferred form of assessment. This study suggests that it is imperative to investigate alternative forms of assessment in literature, not only because the existing forms can be written by AI, but in a larger sense, students are increasingly skeptical of the purpose of such work. The extent to which an essay actually helps the students professionally is a question that academia has not yet answered. This paper suggests that using real-world tasks like creating podcasts, video tutorials, and websites is a far better way to evaluate students' critical thinking and application of ideas, as well as to develop digital skills which are important to their future careers. Using the example of a course in literature, this study will examine the possibilities and challenges of creating digital projects as a way of confronting the complexities of student evaluation in the future. The study is based on a specific university English as a Foreign Language (EFL) context. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=assessment" title="assessment">assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=literature" title=" literature"> literature</a>, <a href="https://publications.waset.org/abstracts/search?q=digital%20humanities" title=" digital humanities"> digital humanities</a>, <a href="https://publications.waset.org/abstracts/search?q=chatgpt" title=" chatgpt"> chatgpt</a> </p> <a href="https://publications.waset.org/abstracts/164237/investigating-best-strategies-towards-creating-alternative-assessment-in-literature" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164237.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">90</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17</span> Automation of AAA Game Development Using AI</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Branden%20Heng">Branden Heng</a>, <a href="https://publications.waset.org/abstracts/search?q=Harsheni%20Siddharthan"> Harsheni Siddharthan</a>, <a href="https://publications.waset.org/abstracts/search?q=Allison%20Tseng"> Allison Tseng</a>, <a href="https://publications.waset.org/abstracts/search?q=Paul%20Toprac"> Paul Toprac</a>, <a href="https://publications.waset.org/abstracts/search?q=Sarah%20Abraham"> Sarah Abraham</a>, <a href="https://publications.waset.org/abstracts/search?q=Etienne%20Vouga"> Etienne Vouga</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The goal of this project was to evaluate and document the capabilities and limitations of AI tools for empowering small teams to create high-budget, high-profile (AAA) 3D games typically developed by large studios. Two teams of novice game developers attempted to create two different games using AI and Unreal Engine 5.3. First, the teams evaluated 60 AI art, design, sound, and programming tools by considering their capability, ease of use, cost, and license restrictions. Then, the teams used a shortlist of 12 AI tools for game development. During this process, the following tools were found to be the most productive: (i) ChatGPT 4.0 for both game and narrative concepts and documentation; (ii) Dall-E 3 and OpenArt for concept art; (iii) Beatoven for music drafting; (iv) ChatGPT 4.0 and Github Copilot for generating simple code and to complement human-made tutorials as an additional learning resource. While current generative AI may appear impressive at first glance, the assets they produce fall short of AAA industry standards. Generative AI tools are helpful when brainstorming ideas such as concept art and basic storylines, but they still cannot replace human input or creativity at this time. Regarding programming, AI can only effectively generate simple code and act as an additional learning resource. Thus, generative AI tools are, at best, tools to enhance developer productivity rather than as a system to replace developers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=AAA%20games" title="AAA games">AAA games</a>, <a href="https://publications.waset.org/abstracts/search?q=AI" title=" AI"> AI</a>, <a href="https://publications.waset.org/abstracts/search?q=automation%20tools" title=" automation tools"> automation tools</a>, <a href="https://publications.waset.org/abstracts/search?q=game%20development" title=" game development"> game development</a> </p> <a href="https://publications.waset.org/abstracts/189316/automation-of-aaa-game-development-using-ai" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/189316.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">37</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">16</span> Automation of AAA Game Development using AI and Procedural Generation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Paul%20Toprac">Paul Toprac</a>, <a href="https://publications.waset.org/abstracts/search?q=Branden%20Heng"> Branden Heng</a>, <a href="https://publications.waset.org/abstracts/search?q=Harsheni%20Siddharthan"> Harsheni Siddharthan</a>, <a href="https://publications.waset.org/abstracts/search?q=Allison%20Tseng"> Allison Tseng</a>, <a href="https://publications.waset.org/abstracts/search?q=Sarah%20Abraham"> Sarah Abraham</a>, <a href="https://publications.waset.org/abstracts/search?q=Etienne%20Vouga"> Etienne Vouga</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The goal of this project was to evaluate and document the capabilities and limitations of AI tools for empowering small teams to create high budget, high profile (AAA) 3D games typically developed by large studios. Two teams of novice game developers attempted to create two different games using AI and Unreal Engine 5.3. First, the teams evaluated 60 AI art, design, sound, and programming tools by considering their capability, ease of use, cost, and license restrictions. Then, the teams used a shortlist of 13 AI tools for game development. During this process, the following tools were found to be the most productive: (1) ChatGPT 4.0 for both game and narrative concepting and documentation; (2) Dall-E 3 and OpenArt for concept art; (3) Beatoven for music drafting; (4) Epic PCG for level design; and (5) ChatGPT 4.0 and Github Copilot for generating simple code and to complement human-made tutorials as an additional learning resource. While current generative AI may appear impressive at first glance, the assets they produce fall short of AAA industry standards. Generative AI tools are helpful when brainstorming ideas such as concept art and basic storylines, but they still cannot replace human input or creativity at this time. Regarding programming, AI can only effectively generate simple code and act as an additional learning resource. Thus, generative AI tools are at best tools to enhance developer productivity rather than as a system to replace developers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=AAA%20games" title="AAA games">AAA games</a>, <a href="https://publications.waset.org/abstracts/search?q=AI" title=" AI"> AI</a>, <a href="https://publications.waset.org/abstracts/search?q=automation%20tools" title=" automation tools"> automation tools</a>, <a href="https://publications.waset.org/abstracts/search?q=game%20development" title=" game development"> game development</a> </p> <a href="https://publications.waset.org/abstracts/191089/automation-of-aaa-game-development-using-ai-and-procedural-generation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191089.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">34</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">15</span> The Design Method of Artificial Intelligence Learning Picture: A Case Study of DCAI's New Teaching</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Weichen%20Chang">Weichen Chang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To create a guided teaching method for AI generative drawing design, this paper develops a set of teaching models for AI generative drawing (DCAI), which combines learning modes such as problem-solving, thematic inquiry, phenomenon-based, task-oriented, and DFC . Through the information security AI picture book learning guided programs and content, the application of participatory action research (PAR) and interview methods to explore the dual knowledge of Context and ChatGPT (DCAI) for AI to guide the development of students' AI learning skills. In the interviews, the students highlighted five main learning outcomes (self-study, critical thinking, knowledge generation, cognitive development, and presentation of work) as well as the challenges of implementing the model. Through the use of DCAI, students will enhance their consensus awareness of generative mapping analysis and group cooperation, and they will have knowledge that can enhance AI capabilities in DCAI inquiry and future life. From this paper, it is found that the conclusions are (1) The good use of DCAI can assist students in exploring the value of their knowledge through the power of stories and finding the meaning of knowledge communication; (2) Analyze the transformation power of the integrity and coherence of the story through the context so as to achieve the tension of ‘starting and ending’; (3) Use ChatGPT to extract inspiration, arrange story compositions, and make prompts that can communicate with people and convey emotions. Therefore, new knowledge construction methods will be one of the effective methods for AI learning in the face of artificial intelligence, providing new thinking and new expressions for interdisciplinary design and design education practice. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=task-oriented" title=" task-oriented"> task-oriented</a>, <a href="https://publications.waset.org/abstracts/search?q=contextualization" title=" contextualization"> contextualization</a>, <a href="https://publications.waset.org/abstracts/search?q=design%20education" title=" design education"> design education</a> </p> <a href="https://publications.waset.org/abstracts/187456/the-design-method-of-artificial-intelligence-learning-picture-a-case-study-of-dcais-new-teaching" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/187456.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">39</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">14</span> Challenges beyond the Singapore Future-Ready School ‘LEADER’ Qualities</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zoe%20Boon%20Suan%20Loy">Zoe Boon Suan Loy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An exploratory research undertaken in 2000 at the beginning of the COVID-19 pandemic examined the changing roles of Singapore school leaders as they lead teachers in developing future-ready learners. While it is evident that ‘LEADER’ qualities epitomize the knowledge, competencies, and skills required, recent events in an increasing VUCA and BANI world characterized by massively disruptive Ukraine -Russian war, unabating tense US-Sino relations, issues related to sustainability, and rapid ageing will have an impact on school leadership. As an increasingly complex endeavour, this requires a relook as they lead teachers in nurturing holistically-developed future-ready students. Digitalisation, new technology, and the push for a green economy will be the key driving forces that will have an impact on job availability. Similarly, the rapid growth of artificial intelligence (AI) capabilities, including ChatGPT, will aggravate and add tremendous stress to the work of school leaders. This paper seeks to explore the key school leadership shifts required beyond the ‘LEADER’ qualities as school leaders respond to the changes, challenges, and opportunities in the 21st C new normal. The research findings for this paper are based on an exploratory qualitative study on the perceptions of 26 school leaders (vice-principals) who were attending a milestone educational leadership course at the National Institute of Education, Nanyang Technological University, Singapore. A structured questionnaire is designed to collect the data, which is then analysed using coding methodology. Broad themes on key competencies and skills of future-ready leaders in the Singapore education system are then identified. Key Findings: In undertaking their leadership roles as leaders of future-ready learners, school leaders need to demonstrate the ‘LEADER’ qualities. They need to have a long-term view, understand the educational imperatives, have a good awareness of self and the dispositions of a leader, be effective in optimizing external leverages and are clear about their role expectations. These ‘LEADER’ qualities are necessary and relevant in the post-Covid era. Beyond this, school leaders with ‘LEADER’ qualities are well supported by the Ministry of Education, which takes cognizance of emerging trends and continually review education policies to address related issues. Concluding Statement: Discussions within the education ecosystem and among other stakeholders on the implications of the use of artificial intelligence and ChatGPT on the school curriculum, including content knowledge, pedagogy, and assessment, are ongoing. This augurs well for school leaders as they undertake their responsibilities as leaders of future-ready learners. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Singapore%20education%20system" title="Singapore education system">Singapore education system</a>, <a href="https://publications.waset.org/abstracts/search?q=%E2%80%98LEADER%E2%80%99%20qualities" title=" ‘LEADER’ qualities"> ‘LEADER’ qualities</a>, <a href="https://publications.waset.org/abstracts/search?q=school%20leadership" title=" school leadership"> school leadership</a>, <a href="https://publications.waset.org/abstracts/search?q=future-ready%20leaders" title=" future-ready leaders"> future-ready leaders</a>, <a href="https://publications.waset.org/abstracts/search?q=future-ready%20learners" title=" future-ready learners"> future-ready learners</a> </p> <a href="https://publications.waset.org/abstracts/166791/challenges-beyond-the-singapore-future-ready-school-leader-qualities" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/166791.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">75</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">13</span> Generative AI in Higher Education: Pedagogical and Ethical Guidelines for Implementation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Judit%20Vilarmau">Judit Vilarmau</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Generative AI is emerging rapidly and transforming higher education in many ways, occasioning new challenges and disrupting traditional models and methods. The studies and authors explored remark on the impact on the ethics, curriculum, and pedagogical methods. Students are increasingly using generative AI for study, as a virtual tutor, and as a resource for generating works and doing assignments. This point is crucial for educators to make sure that students are using generative AI with ethical considerations. Generative AI also has relevant benefits for educators and can help them personalize learning experiences and promote self-regulation. Educators must seek and explore tools like ChatGPT to innovate without forgetting an ethical and pedagogical perspective. Eighteen studies were systematically reviewed, and the findings provide implementation guidelines with pedagogical and ethical considerations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ethics" title="ethics">ethics</a>, <a href="https://publications.waset.org/abstracts/search?q=generative%20artificial%20intelligence" title=" generative artificial intelligence"> generative artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=guidelines" title=" guidelines"> guidelines</a>, <a href="https://publications.waset.org/abstracts/search?q=higher%20education" title=" higher education"> higher education</a>, <a href="https://publications.waset.org/abstracts/search?q=pedagogy" title=" pedagogy"> pedagogy</a> </p> <a href="https://publications.waset.org/abstracts/179093/generative-ai-in-higher-education-pedagogical-and-ethical-guidelines-for-implementation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/179093.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">97</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">12</span> Artificial Intelligence and the Next Generation Journalistic Practice: Prospects, Issues and Challenges</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shola%20Abidemi%20Olabode">Shola Abidemi Olabode</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The technological revolution over the years has impacted journalistic practice. As a matter of fact, journalistic practice has evolved alongside technologies of every generation transforming news and reporting, entertainment, and politics. Alongside these developments, the emergence of new kinds of risks and harms associated with generative AI has become rife with implications for media and journalism. Despite their numerous benefits for research and development, generative AI technologies like ChatGPT introduce new practical, ethical, and regulatory complexities in the practice of media and journalism. This paper presents a preliminary overview of the new kinds of challenges and issues for journalism and media practice in the era of generative AI, the implications for Nigeria, and invites a consideration of methods to mitigate the evolving complexity. It draws mainly on desk-based research underscoring the literature in both developed and developing non-western contexts as a contribution to knowledge. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=AI" title="AI">AI</a>, <a href="https://publications.waset.org/abstracts/search?q=journalism" title=" journalism"> journalism</a>, <a href="https://publications.waset.org/abstracts/search?q=media" title=" media"> media</a>, <a href="https://publications.waset.org/abstracts/search?q=online%20harms" title=" online harms"> online harms</a> </p> <a href="https://publications.waset.org/abstracts/170414/artificial-intelligence-and-the-next-generation-journalistic-practice-prospects-issues-and-challenges" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/170414.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">94</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">11</span> A Comparative Analysis of Artificial Intelligence-Generated Educational Responses: Assessing Readability, Complexity, and Learning Effectiveness</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20W.%20Weible%202nd">M. W. Weible 2nd</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20Punyadilokpong"> C. Punyadilokpong</a>, <a href="https://publications.waset.org/abstracts/search?q=C.%20A.%20Love"> C. A. Love</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Artificial intelligence (AI) is reshaping education by offering adaptive tools that generate personalized, real-time responses to student inquiries. AI-driven tutoring systems can bridge knowledge gaps, enhance understanding, and simplify complex topics in technical and conceptually demanding subjects, such as those encountered in specialized fields. However, the overall effectiveness of these responses depends not only on their factual accuracy but also on their readability and clarity. Readability, measured through linguistic complexity metrics, is essential for ensuring that AI-generated content meets the diverse comprehension needs of learners. Despite AI’s growing presence in education, few studies have systematically evaluated the readability of responses from various AI platforms. Materials and Methods: In this study, we analyzed AI-generated responses from nine platforms: ChatGPT, Gemini, Otter AI, TutorOcean AI, Atlas AI, Studymonkey AI, Julius AI, Copilot (Microsoft AI), and Claude AI, to determine how effectively they address biochemistry-related questions. We employed the Flesch-Kincaid method to assess grade level, reading ease, sentence count, word count, average words per sentence, and average syllables per word. In addition, the Gunning Fog Index was calculated to further gauge textual difficulty. Results: Our analysis revealed an average Flesch-Kincaid Grade Level of approximately 13, suggesting that the content is generally suitable for late high school or early college readers while potentially challenging younger students or those with lower proficiency. Among the platforms, Atlas AI produced the most complex responses, whereas Studymonkey AI-generated content was the most readable and aligned more closely with lower high school reading levels. Notably, there was significant variation in sentence structure and response length: Studymonkey AI exhibited the longest sentences (averaging over 17 words), while ChatGPT provided nearly 30 sentences per response. TutorOcean AI produced the most extended responses, exceeding an average of 310 words per answer. The Gunning Fog Index scores ranged from 13.02 (Atlas AI) to 17.49 (Claude AI), with an overall mean of approximately 14—indicating that a college-level reading ability is generally required for full comprehension. Conclusion: The findings highlight considerable variability in the readability of AI-generated responses. Some platforms prioritize detailed explanations at the expense of accessibility, while others produce content that is easier to read but may be less comprehensive. These results underscore the importance of selecting AI tools that align with learners’ comprehension levels. Future developments in AI educational tools should focus on balancing accuracy, clarity, and linguistic complexity to enhance their overall effectiveness across diverse academic disciplines. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=AI" title="AI">AI</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20learning%20tools" title=" adaptive learning tools"> adaptive learning tools</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence%20in%20education" title=" artificial intelligence in education"> artificial intelligence in education</a>, <a href="https://publications.waset.org/abstracts/search?q=Flesch%E2%80%93Kincaid" title=" Flesch–Kincaid"> Flesch–Kincaid</a>, <a href="https://publications.waset.org/abstracts/search?q=gunning%20fog" title=" gunning fog"> gunning fog</a>, <a href="https://publications.waset.org/abstracts/search?q=readability%20metric" title=" readability metric"> readability metric</a> </p> <a href="https://publications.waset.org/abstracts/199046/a-comparative-analysis-of-artificial-intelligence-generated-educational-responses-assessing-readability-complexity-and-learning-effectiveness" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/199046.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10</span> User Intention Generation with Large Language Models Using Chain-of-Thought Prompting Title</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gangmin%20Li">Gangmin Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Fan%20Yang"> Fan Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behaviour data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=personalized%20recommendation" title="personalized recommendation">personalized recommendation</a>, <a href="https://publications.waset.org/abstracts/search?q=generative%20user%20modelling" title=" generative user modelling"> generative user modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=user%20intention%20identification" title=" user intention identification"> user intention identification</a>, <a href="https://publications.waset.org/abstracts/search?q=large%20language%20models" title=" large language models"> large language models</a>, <a href="https://publications.waset.org/abstracts/search?q=chain-of-thought%20prompting" title=" chain-of-thought prompting"> chain-of-thought prompting</a> </p> <a href="https://publications.waset.org/abstracts/185916/user-intention-generation-with-large-language-models-using-chain-of-thought-prompting-title" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185916.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">64</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">9</span> A Study on the Application of Generative AI Tools for Chinese Writing Feedback in Non-Fiction Writing Instruction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Stephanie%20Liu%20Lu">Stephanie Liu Lu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The course "University Chinese," an essential component of the curriculum in Hong Kong's higher education institutions, plays a crucial role in enhancing students' creative expression, narrative construction, argumentative prowess, and literary skills through its focus on non-fiction writing. Despite its significance, the comprehensive syllabus, coupled with limited classroom time, often restricts adequate practice opportunities and leads to delayed feedback, negatively impacting students' preparation for assessments. This paper investigates the potential of generative artificial intelligence (AI) tools, such as ChatGPT and POE, to provide personalized and immediate feedback for writing tasks. The primary goal of this research is to evaluate student receptiveness to AI-generated feedback and compare it to traditional feedback provided solely by human instructors. To achieve this, participants will be systematically divided into two groups: one receiving feedback from both instructors and AI tools, and a control group that receives feedback exclusively from instructors. The study will thoroughly analyze the revisions made to texts after receiving feedback, focusing particularly on enhancements in the quality of content and language proficiency across three dimensions: content/theme, language, and structural logic. This investigation aims to determine whether AI tools can enhance the efficiency of teaching practices, encourage autonomous learning, and significantly improve the overall quality of students' written work. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=AI-generated%20feedback" title="AI-generated feedback">AI-generated feedback</a>, <a href="https://publications.waset.org/abstracts/search?q=Chinese%20writing" title=" Chinese writing"> Chinese writing</a>, <a href="https://publications.waset.org/abstracts/search?q=non-fiction%20writing" title=" non-fiction writing"> non-fiction writing</a>, <a href="https://publications.waset.org/abstracts/search?q=student%20receptiveness" title=" student receptiveness"> student receptiveness</a> </p> <a href="https://publications.waset.org/abstracts/196624/a-study-on-the-application-of-generative-ai-tools-for-chinese-writing-feedback-in-non-fiction-writing-instruction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/196624.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">13</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8</span> Exploring the Impact of Artificial Intelligence (AI) in the Context of English as a Foreign Language (EFL): A Comprehensive Bibliometric Study</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kate%20Benedicta%20Amenador">Kate Benedicta Amenador</a>, <a href="https://publications.waset.org/abstracts/search?q=Dianjian%20Wang"> Dianjian Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Bright%20Nkrumah"> Bright Nkrumah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This extensive bibliometric study explores the dynamic influence of artificial intelligence in the field of English as a Foreign Language (EFL) between 2012 and 2024. The study, which examined 4,500 articles from Google Scholar, Modern Language Association Linguistics Abstracts, Web of Science, Scopus, Researchgate, and library genesis databases, indicates that AI integration in EFL is on the rise. This notable increase is ascribed to a variety of transformative events, including increased academic funding for higher education and the COVID-19 epidemic. The results of the study identify leading contributors, prominent authors, publishers and sources, with the United States, China and the United Kingdom emerging as key contributors. The co-occurrence analysis of key terms reveals five clusters highlighting patterns in AI-enhanced language instruction and learning, including evaluation strategies, educational technology, learning motivation, EFL teaching aspects, and learner feedback. The study also discusses the impact of various AIs in enhancing EFL writing skills with software such as Grammarly, Quilbot, and Chatgpt. The current study recognizes limitations in database selection and linguistic constraints. Nevertheless, the results provide useful insights for educators, researchers and policymakers, inspiring and guiding a cross-disciplinary collaboration and creative pedagogical techniques and approaches to teaching and learning in the future. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=bibliometrics%20study" title=" bibliometrics study"> bibliometrics study</a>, <a href="https://publications.waset.org/abstracts/search?q=VOSviewer%20visualization" title=" VOSviewer visualization"> VOSviewer visualization</a>, <a href="https://publications.waset.org/abstracts/search?q=English%20as%20a%20foreign%20language" title=" English as a foreign language"> English as a foreign language</a> </p> <a href="https://publications.waset.org/abstracts/190537/exploring-the-impact-of-artificial-intelligence-ai-in-the-context-of-english-as-a-foreign-language-efl-a-comprehensive-bibliometric-study" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/190537.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">42</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=chatgpt&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=chatgpt&page=2" rel="next">&rsaquo;</a></li> </ul> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> 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