Transforming Education: A Comprehensive Review of Generative Artificial Intelligence in Educational Settings through Bibliometric and Content Analysis

Sustainability, Год журнала: 2023, Номер 15(17), С. 12983 - 12983

Опубликована: Авг. 29, 2023

In the ever-evolving era of technological advancements, generative artificial intelligence (GAI) emerges as a transformative force, revolutionizing education. This review paper, guided by PRISMA framework, presents comprehensive analysis GAI in education, synthesizing key insights from selection 207 research papers to identify gaps and future directions field. study begins with content that explores GAI’s impact specific educational domains, including medical education engineering The versatile applications encompass assessment, personalized learning support, intelligent tutoring systems. Ethical considerations, interdisciplinary collaboration, responsible technology use are highlighted, emphasizing need for transparent models addressing biases. Subsequently, bibliometric is conducted, examining prominent AI tools, focus, geographic distribution, collaboration. ChatGPT dominant tool, reveals significant exponential growth 2023. Moreover, this paper identifies promising directions, such GAI-enhanced curriculum design longitudinal studies tracking its long-term on outcomes. These findings provide understanding potential reshaping offer valuable researchers, educators, policymakers interested intersection

Язык: Английский

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Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions

JMIR Medical Education, Год журнала: 2023, Номер 9, С. e48291 - e48291

Опубликована: Май 17, 2023

The integration of large language models (LLMs), such as those in the Generative Pre-trained Transformers (GPT) series, into medical education has potential to transform learning experiences for students and elevate their knowledge, skills, competence. Drawing on a wealth professional academic experience, we propose that LLMs hold promise revolutionizing curriculum development, teaching methodologies, personalized study plans materials, student assessments, more. However, also critically examine challenges might pose by addressing issues algorithmic bias, overreliance, plagiarism, misinformation, inequity, privacy, copyright concerns education. As navigate shift from an information-driven educational paradigm artificial intelligence (AI)-driven paradigm, argue it is paramount understand both pitfalls This paper thus offers our perspective opportunities using this context. We believe insights gleaned analysis will serve foundation future recommendations best practices field, fostering responsible effective use AI technologies

Язык: Английский

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Role of AI chatbots in education: systematic literature review

International Journal of Educational Technology in Higher Education, Год журнала: 2023, Номер 20(1)

Опубликована: Окт. 31, 2023

Abstract AI chatbots shook the world not long ago with their potential to revolutionize education systems in a myriad of ways. can provide immediate support by answering questions, offering explanations, and providing additional resources. Chatbots also act as virtual teaching assistants, supporting educators through various means. In this paper, we try understand full benefits education, opportunities, challenges, limitations, concerns, prospects using educational settings. We conducted an extensive search across academic databases, after applying specific predefined criteria, selected final set 67 relevant studies for review. The research findings emphasize numerous integrating seen from both students' educators' perspectives. found that students primarily gain AI-powered three key areas: homework study assistance, personalized learning experience, development skills. For educators, main advantages are time-saving assistance improved pedagogy. However, our emphasizes significant challenges critical factors need handle diligently. These include concerns related applications such reliability, accuracy, ethical considerations.

Язык: Английский

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Opportunities, Challenges, and Future Directions of Generative Artificial Intelligence in Medical Education: Scoping Review

JMIR Medical Education, Год журнала: 2023, Номер 9, С. e48785 - e48785

Опубликована: Сен. 28, 2023

Generative artificial intelligence (AI) technologies are increasingly being utilized across various fields, with considerable interest and concern regarding their potential application in medical education. These technologies, such as Chat GPT Bard, can generate new content have a wide range of possible applications.

Язык: Английский

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ChatGPT in Healthcare: A Taxonomy and Systematic Review

medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown

Опубликована: Март 30, 2023

Abstract The recent release of ChatGPT, a chat bot research project / product natural language processing (NLP) by OpenAI, stirs up sensation among both the general public and medical professionals, amassing phenomenally large user base in short time. This is typical example ‘productization’ cutting-edge technologies, which allows without technical background to gain firsthand experience artificial intelligence (AI), similar AI hype created AlphaGo (DeepMind Technologies, UK) self-driving cars (Google, Tesla, etc.). However, it crucial, especially for healthcare researchers, remain prudent amidst hype. work provides systematic review existing publications on use ChatGPT healthcare, elucidating ‘status quo’ applications, readers, professionals as well NLP scientists. biomedical literature database PubMed used retrieve published works this topic using keyword ‘ChatGPT’. An inclusion criterion taxonomy are further proposed filter search results categorize selected publications, respectively. It found through that current has achieved only moderate or ‘passing’ performance variety tests, unreliable actual clinical deployment, since not intended applications design. We conclude specialized models trained (bio)medical datasets still represent right direction pursue critical applications.

Язык: Английский

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A scoping review of artificial intelligence in medical education: BEME Guide No. 84

Medical Teacher, Год журнала: 2024, Номер 46(4), С. 446 - 470

Опубликована: Фев. 29, 2024

Background Artificial Intelligence (AI) is rapidly transforming healthcare, and there a critical need for nuanced understanding of how AI reshaping teaching, learning, educational practice in medical education. This review aimed to map the literature regarding applications education, core areas findings, potential candidates formal systematic gaps future research.

Язык: Английский

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La nueva realidad de la educación ante los avances de la inteligencia artificial generativa

RIED Revista Iberoamericana de Educación a Distancia, Год журнала: 2023, Номер 27(1), С. 9 - 39

Опубликована: Июль 7, 2023

Cada vez es más común interactuar con productos que parecen “inteligentes”, aunque quizás la etiqueta “inteligencia artificial” haya sido sustituida por otros eufemismos. Desde noviembre de 2022, aparición herramienta ChatGPT, ha habido un aumento exponencial en el uso inteligencia artificial todos los ámbitos. Aunque ChatGPT solo una las muchas tecnologías generativas artificial, su impacto procesos enseñanza y aprendizaje notable. Este artículo reflexiona sobre ventajas, inconvenientes, potencialidades, límites retos educación, objetivo evitar sesgos propios posiciones extremistas. Para ello, se llevado a cabo revisión sistemática tanto herramientas como producción científica surgido seis primeros meses desde ChatGPT. La generativa extremadamente potente mejora ritmo acelerado, pero basa lenguajes modelo gran tamaño base probabilística, lo significa no tienen capacidad razonamiento ni comprensión y, tanto, son susceptibles contener fallos necesitan ser contrastados. Por otro lado, muchos problemas asociados estas contextos educativos ya existían antes aparición, ahora, debido potencia, podemos ignorarlos queda asumir cuál será nuestra velocidad respuesta para analizar e incorporar práctica docente.

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Accuracy of ChatGPT‐Generated Information on Head and Neck and Oromaxillofacial Surgery: A Multicenter Collaborative Analysis

Otolaryngology, Год журнала: 2023, Номер 170(6), С. 1492 - 1503

Опубликована: Авг. 18, 2023

Abstract Objective To investigate the accuracy of Chat‐Based Generative Pre‐trained Transformer (ChatGPT) in answering questions and solving clinical scenarios head neck surgery. Study Design Observational valuative study. Setting Eighteen surgeons from 14 Italian surgery units. Methods A total 144 encompassing different subspecialities 15 comprehensive were developed. Questions inputted into ChatGPT4, resulting answers evaluated by researchers using (range 1‐6), completeness 1‐3), references' quality Likert scales. Results The overall median score open‐ended was 6 (interquartile range[IQR]: 5‐6) for 3 (IQR: 2‐3) completeness. Overall, reviewers rated answer as entirely or nearly correct 87.2% cases covering all aspects question 73% cases. artificial intelligence (AI) model achieved a response 84.7% closed‐ended (11 wrong answers). As scenarios, ChatGPT provided fully diagnosis 81.7% proposed diagnostic therapeutic procedure judged to be complete 56.7% bibliographic references poor, sources nonexistent 46.4% Conclusion results generally demonstrate good level AI's answers. ability resolve complex is promising, but it still falls short being considered reliable support decision‐making process specialists head‐neck

Язык: Английский

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Medical Teacher’s first ChatGPT’s referencing hallucinations: Lessons for editors, reviewers, and teachers

Medical Teacher, Год журнала: 2023, Номер 45(7), С. 673 - 675

Опубликована: Май 15, 2023

Students’ inappropriate use of ChatGPT is a concern. There also, however, the potential for academics to inappropriately. After explaining ChatGPT’s “hallucinations” regarding citing and referencing, this commentary illustrates problem by describing detection first known Medical Teacher submission using inappropriately, lessons that can be drawn from it journal editors, reviewers, teachers, then wider implications if left unchecked.

Язык: Английский

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Assessing ChatGPT’s Mastery of Bloom’s Taxonomy Using Psychosomatic Medicine Exam Questions: Mixed-Methods Study

Journal of Medical Internet Research, Год журнала: 2024, Номер 26, С. e52113 - e52113

Опубликована: Янв. 23, 2024

Background Large language models such as GPT-4 (Generative Pre-trained Transformer 4) are being increasingly used in medicine and medical education. However, these prone to “hallucinations” (ie, outputs that seem convincing while factually incorrect). It is currently unknown how errors by large relate the different cognitive levels defined Bloom’s taxonomy. Objective This study aims explore performs terms of taxonomy using psychosomatic exam questions. Methods We a data set multiple-choice questions (N=307) with real-world results derived from school exams. answered 2 distinct prompt versions: detailed short. The answers were analyzed quantitative approach qualitative approach. Focusing on incorrectly questions, we categorized reasoning according hierarchical framework Results GPT-4’s performance answering yielded high success rate: 93% (284/307) for 91% (278/307) short prompt. Questions correctly had statistically significant higher difficulty than (P=.002 P<.001 prompt). Independent prompt, lowest was 78.9% (15/19), thereby always surpassing “pass” threshold. Our analysis incorrect answers, based taxonomy, showed primarily “remember” (29/68) “understand” (23/68) levels; specific issues arose recalling details, understanding conceptual relationships, adhering standardized guidelines. Conclusions demonstrated remarkable rate when confronted aligning previous findings. When evaluated through our revealed occasionally ignored facts (remember), provided illogical (understand), or failed apply concepts new situation (apply). These errors, which confidently presented, could be attributed inherent model biases tendency generate maximize likelihood.

Язык: Английский

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