Role of activity-based learning and ChatGPT on students' performance in education

Computers and Education Artificial Intelligence, Год журнала: 2024, Номер 6, С. 100219 - 100219

Опубликована: Апрель 3, 2024

This study investigates the impact of activity-based learning and utilization ChatGPT on students' academic performance within educational framework. The aims to assess effectiveness in comparison traditional methods, while also evaluating potential benefits drawbacks integrating as an tool. employs a comparative approach, analyzing outcomes students exposed versus those using conventional methods. Additionally, examines usage education through surveys trials determine its contribution personalized feedback, interactive learning, innovative teaching findings reveal that enhances engagement, motivation, critical thinking skills. Students participating demonstrate improved achievement, which is attributed their active involvement practical application knowledge. Similarly, integration offers novel avenues for individualized assistance, fostering understanding exploration complex concepts. In conclusion, proves be student-centered approach by participation engagement. showcases enhance experiences conversations methodologies, despite considerations regarding limitations ethical implications.

Язык: Английский

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The application of Chat Generative Pre-trained Transformer in nursing education

Nursing Outlook, Год журнала: 2023, Номер 71(6), С. 102064 - 102064

Опубликована: Окт. 23, 2023

Язык: Английский

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Comparative review of big data analytics and GIS in healthcare decision-making

World Journal of Advanced Research and Reviews, Год журнала: 2023, Номер 20(3), С. 1293 - 1302

Опубликована: Дек. 22, 2023

This research explores the confluence of big data analytics and Geographic information systems (GIS) in healthcare decision-making. The comparative review delineates unique strengths each technology, showcasing potential synergies. Big harnesses advanced for predictive modeling clinical decision support, while GIS introduces a spatial context health analysis. Future trends suggest integrations with artificial intelligence, real-time analytics, wearable technology. However, challenges encompass privacy, biases, interdisciplinary collaboration. Ethical considerations emphasize transparency, informed consent, responsible use patient data. As these technologies evolve, their seamless integration holds promise precision health, community-oriented interventions, proactive pandemic response, reshaping landscape

Язык: Английский

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Reviewing the role of AI in environmental monitoring and conservation: A data-driven revolution for our planet

World Journal of Advanced Research and Reviews, Год журнала: 2024, Номер 21(1), С. 161 - 171

Опубликована: Янв. 4, 2024

The rapid increase in human activities is causing significant damage to our planet's ecosystems, necessitating innovative solutions preserve biodiversity and counteract ecological threats. Artificial Intelligence (AI) has emerged as a transformative force, providing unparalleled capabilities for environmental monitoring conservation. This research paper explores the applications of AI ecosystem management, including wildlife tracking, habitat assessment, analysis, natural disaster prediction. AI's role conservation includes resource conservation, species identification. algorithms analyze camera trap footage, drone imagery, GPS data identify estimate population sizes, leading improved anti-poaching efforts enhanced protection diverse species. Habitat assessment involve AI-powered image which aids assessing forest health, detecting deforestation, identifying areas need restoration. Biodiversity analysis identification are achieved through that acoustic recordings, DNA (eDNA), footage. These innovations different species, assess levels, even discover new or endangered flood prediction systems provide early warnings, empowering communities with better preparedness evacuation efforts. Challenges, such quality availability, algorithmic bias, infrastructure limitations, acknowledged opportunities growth improvement. In policy regulation, advocates clear frameworks prioritizing privacy security, transparency, equitable access. Responsible development ethical use emphasized foundational pillars, ensuring integration into aligns principles fairness, societal benefit.

Язык: Английский

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Large language models streamline automated machine learning for clinical studies

Nature Communications, Год журнала: 2024, Номер 15(1)

Опубликована: Фев. 21, 2024

A knowledge gap persists between machine learning (ML) developers (e.g., data scientists) and practitioners clinicians), hampering the full utilization of ML for clinical analysis. We investigated potential ChatGPT Advanced Data Analysis (ADA), an extension GPT-4, to bridge this perform analyses efficiently. Real-world datasets study details from large trials across various medical specialties were presented ADA without specific guidance. autonomously developed state-of-the-art models based on original study's training predict outcomes such as cancer development, progression, disease complications, or biomarkers pathogenic gene sequences. Following re-implementation optimization published models, head-to-head comparison ADA-crafted their respective manually crafted counterparts revealed no significant differences in traditional performance metrics (p ≥ 0.072). Strikingly, often outperformed counterparts. In conclusion, offers a promising avenue democratize medicine by simplifying complex analyses, yet should enhance, not replace, specialized resources, promote broader applications research practice.

Язык: Английский

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Revolutionizing generative pre-traineds: Insights and challenges in deploying ChatGPT and generative chatbots for FAQs

Expert Systems with Applications, Год журнала: 2024, Номер 246, С. 123224 - 123224

Опубликована: Янв. 19, 2024

Язык: Английский

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ChatGPT in finance: Applications, challenges, and solutions

Heliyon, Год журнала: 2024, Номер 10(2), С. e24890 - e24890

Опубликована: Янв. 1, 2024

The emergence of ChatGPT, a generative artificial intelligence tool, has sparked revolution in the finance industry, enabling individuals to interact with technology natural language. However, use ChatGPT presents profound array ethical considerations that demand careful scrutiny ensure its responsible and use. After concise exploration ChatGPT's applications finance, this policy article delves into challenges arising from including outcomes contaminated biases, incorporation fake information financial decisions, concerns surrounding privacy security, lack transparency accountability decision-making processes services, human job displacement, intricate web legal complexities. Our asserts institutions employing must proactively devise strategies confront these burgeoning challenges, mitigating their adverse effects on both society as whole. Additionally, we propose relevant policies tackle quandaries head-on. In essence, illuminates imperative need for meticulous framework, facilitating an informed realm safeguarding welfare society. While our work significantly contributes research practice also identify future avenues.

Язык: Английский

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Autonomous Vehicles: Evolution of Artificial Intelligence and the Current Industry Landscape

Big Data and Cognitive Computing, Год журнала: 2024, Номер 8(4), С. 42 - 42

Опубликована: Апрель 7, 2024

The advent of autonomous vehicles has heralded a transformative era in transportation, reshaping the landscape mobility through cutting-edge technologies. Central to this evolution is integration artificial intelligence (AI), propelling into realms unprecedented autonomy. Commencing with an overview current industry respect Operational Design Domain (ODD), paper delves fundamental role AI shaping decision-making capabilities vehicles. It elucidates steps involved AI-powered development life cycle vehicles, addressing various challenges such as safety, security, privacy, and ethical considerations AI-driven software for study presents statistical insights usage types algorithms over years, showcasing evolving research within automotive industry. Furthermore, highlights pivotal parameters refining both trucks cars, facilitating adapt, learn, improve performance time. concludes by outlining different levels autonomy, elucidating nuanced algorithms, discussing automation key tasks package size at each level. Overall, provides comprehensive analysis landscape, focusing on several critical aspects.

Язык: Английский

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Potential applications and implications of large language models in primary care

Family Medicine and Community Health, Год журнала: 2024, Номер 12(Suppl 1), С. e002602 - e002602

Опубликована: Янв. 1, 2024

The recent release of highly advanced generative artificial intelligence (AI) chatbots, including ChatGPT and Bard, which are powered by large language models (LLMs), has attracted growing mainstream interest over its diverse applications in clinical practice, health healthcare. potential LLM-based programmes the medical field range from assisting practitioners improving their decision-making streamlining administrative paperwork to empowering patients take charge own health. However, despite broad benefits, use such AI tools also comes with several limitations ethical concerns that warrant further consideration, encompassing issues related privacy, data bias, accuracy reliability information generated AI. focus prior research primarily centred on LLMs medicine. To author’s knowledge, this is, first article consolidates current pertinent literature examine primary care. objectives paper not only summarise risks challenges using care, but offer insights into considerations care clinicians should account when deciding adopt integrate technologies practice.

Язык: Английский

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A Preliminary Checklist (METRICS) to Standardize the Design and Reporting of Studies on Generative Artificial Intelligence–Based Models in Health Care Education and Practice: Development Study Involving a Literature Review

Interactive Journal of Medical Research, Год журнала: 2024, Номер 13, С. e54704 - e54704

Опубликована: Янв. 26, 2024

Background Adherence to evidence-based practice is indispensable in health care. Recently, the utility of generative artificial intelligence (AI) models care has been evaluated extensively. However, lack consensus guidelines on design and reporting findings these studies poses a challenge for interpretation synthesis evidence. Objective This study aimed develop preliminary checklist standardize AI-based education practice. Methods A literature review was conducted Scopus, PubMed, Google Scholar. Published records with “ChatGPT,” “Bing,” or “Bard” title were retrieved. Careful examination methodologies employed included identify common pertinent themes possible gaps reporting. panel discussion held establish unified thorough AI The finalized used evaluate by 2 independent raters. Cohen κ as method interrater reliability. Results final data set that formed basis theme identification analysis comprised total 34 records. 9 collectively referred METRICS (Model, Evaluation, Timing, Range/Randomization, Individual factors, Count, Specificity prompts language). Their details are follows: (1) Model its exact settings; (2) Evaluation approach generated content; (3) Timing testing model; (4) Transparency source; (5) Range tested topics; (6) Randomization selecting queries; (7) factors queries reliability; (8) Count executed test (9) language used. overall mean score 3.0 (SD 0.58). acceptable, range 0.558 0.962 (P<.001 items). With classification per item, highest average recorded “Model” followed “Specificity” while lowest scores “Randomization” item (classified suboptimal) “Individual factors” satisfactory). Conclusions can facilitate guiding researchers toward best practices results. highlight need standardized algorithms care, considering variability observed proposed could be helpful base universally accepted which swiftly evolving research topic.

Язык: Английский

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