Incorporating Generative AI to Promote Inquiry-Based Learning: Comparing Elicit AI Research Assistant to PubMed and CINAHL Complete
Rachel Fenske, Jo Ann Otts
University of South Alabama
内容与影响
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.
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学术脉络
学科主题
计算机 / AISemantic Web and Ontologies
Biomedical Text Mining and Ontologies · Web Applications and Data Management
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