[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-427235-105":3,"detail-sidebar-cat-0-en-105":81,"doc-detail-427235-en":130},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","artificial-intelligence-aids-in-the-development-of-multidisciplinary-age-friendly-education-vol-9-s2-proceedings-style-report","ARTIFICIAL INTELLIGENCE AIDS IN THE DEVELOPMENT OF MULTIDISCIPLINARY AGE-FRIENDLY EDUCATION - Vol. 9 - S2 - Proceedings style report","","The work outlines a structured process for using Artificial Intelligence, specifically ChatGPT, to streamline and accelerate the creation of educational content while preserving accuracy and clinical best-practice alignment. The approach begins by prompting ChatGPT to generate a 15-minute e-learning module using goal-oriented outcomes and age-friendly care elements for healthcare professionals, then includes human expert review and refinement for instructional design compliance and real-world applicability. After review, ChatGPT generates knowledge assessments to evaluate learning, demonstrating how AI paired with oversight supports faster module production and competency-aligned evaluation.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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real-world healthcare settings.",{"name":70,"@type":61,"acceptedAnswer":71},"How are learning outcomes evaluated after module development?",{"text":72,"@type":64},"After the final review, ChatGPT is prompted to generate knowledge assessments that test key concepts, supporting evaluation of learning effectiveness.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},427235,1791025475,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,111,115,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & 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The process began by prompting ChatGPT to generate an e-learning module with specific instructional design elements based on goal-oriented outcomes while integrating age-friendly content into specialized geriatric modules for healthcare professionals. For example, the prompt for “Introducing the 4Ms of Age-Friendly Care” included: “Generate a structured 15-minute e-learning module introducing the 4Ms Framework to licensed and unlicensed healthcare professionals, 8th grade reading level, include an introductory paragraph, key sections with structured content, a conclusion paragraph, key takeaways, and a scenario-based application activity. Use content from the IHI website and the John A. Hartford Foundation only”. In seconds, ChatGPT generated the requested e-learning content. The output was reviewed and refined to ensure the desired competencies were appropriately addressed. Subject matter and educational experts conducted a final review to ensure accuracy, adherence to the desired instructional design parameters, and applicability to real-world healthcare settings. After the final review, ChatGPT was prompted to generate knowledge assessments to test key concepts. Key takeaways included: ChatGPT, when coupled with human expertise and oversight for educational content development, was a useful tool to streamline module creation, ensure alignment with instructional design principles, integrate age-friendly care elements, and generate knowledge assessments to evaluate learning.  \nAbstract citation ID: igaf122.2240  \nARTIFICIAL INTELLIGENCE AIDS IN THE  \nDEVELOPMENT OF MULTIDISCIPLINARY  \nAGE-FRIENDLY EDUCATION  \nSuzanne White1, Robin McAtee2, and Laura Spradley2,  \n1. College of Nursing-University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States, 2. University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States  \nThis work describes a structured approach to leveraging Artificial Intelligence (AI), specifically ChatGPT, a Large Language Model (LLM), to streamline and accelerate the development of educational content while maintaining accuracy and adherence to clinical best practices. Goals were developed to meet the learning objectives of the targeted learners and then AI was","cbCaifvKRako7EZ9","https://ap.wps.com/l/cbCaifvKRako7EZ9","pdf",47785,"English","# Structured AI-assisted e-learning development\n## Goal-oriented prompts and age-friendly content integration\n## Human expert review, refinement, and accuracy checks\n## Knowledge assessments for learning evaluation","[{\"question\":\"How does the document describe using ChatGPT to develop e-learning modules?\",\"answer\":\"It describes prompting ChatGPT to generate an e-learning module aligned to goal-oriented outcomes and age-friendly content for targeted healthcare professionals, then using human review to ensure instructional design compliance and accuracy.\"},{\"question\":\"What role do educational and subject matter experts play?\",\"answer\":\"Experts review and refine the AI output so competencies are appropriately addressed, content accuracy is maintained, and parameters match the intended instructional design and real-world healthcare settings.\"},{\"question\":\"How are learning outcomes evaluated after module development?\",\"answer\":\"After the final review, ChatGPT is prompted to generate knowledge assessments that test key concepts, supporting evaluation of learning effectiveness.\"}]","ARTIFICIAL INTELLIGENCE AIDS IN THE DEVELOPMENT OF MULTIDISCIPLINARY AGE-FRIENDLY EDUCATION - Vol. 9 - S2 - Proceedings style report | PDF",1790643280]