Suppr超能文献

将生成式人工智能融入以促进基于探究的学习:比较 Elicit AI 研究助手与 PubMed 和 CINAHL Complete。

Incorporating Generative AI to Promote Inquiry-Based Learning: Comparing Elicit AI Research Assistant to PubMed and CINAHL Complete.

机构信息

University of South Alabama, Mobile, Alabama, USA.

出版信息

Med Ref Serv Q. 2024 Oct-Dec;43(4):292-305. doi: 10.1080/02763869.2024.2403272. Epub 2024 Nov 4.

Abstract

Generative artificial intelligence (GenAI) is transforming education, and faculty can either incorporate GenAI in intentional course design to promote inquiry-based learning (IBL) or resist its use. This study identified an effective strategy to intentionally integrate GenAI in the course design to promote IBL. A descriptive study design was used for graduate nursing students to compare the effectiveness of a GenAI literature search tool, Elicit: The AI Research Assistant, to PubMed and CINAHL. A two-phase framework was utilized to organize complex information and justify a preference. A rubric was designed to promote and assess critical thinking through IBL in educating graduate nursing students on information literacy and structuring a literature search. Discovering a relationship between the search tools, students identified the strengths (pros) and weaknesses (cons) of each tool and determined which tool was more effective in terms of accuracy, relevance and efficiency.

摘要

生成式人工智能(GenAI)正在改变教育,教师可以在有目的的课程设计中融入 GenAI 以促进探究式学习(IBL),也可以抵制其使用。本研究确定了一种将 GenAI 有意整合到课程设计中以促进 IBL 的有效策略。采用描述性研究设计,对护理专业研究生进行了研究,比较了 GenAI 文献检索工具 Elicit:AI 研究助理与 PubMed 和 CINAHL 的检索效果。采用两阶段框架来组织复杂信息,并为偏好提供依据。设计了一个评分标准,通过 IBL 促进和评估批判性思维,教育护理专业研究生信息素养和构建文献检索。在发现搜索工具之间的关系后,学生确定了每个工具的优势(pros)和劣势(cons),并确定了在准确性、相关性和效率方面哪一个工具更有效。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验