Teaching, Building, Learning: AI in Nursing Education

The session is grounded in two guiding frameworks. The ADDIE instructional design model (Analysis, Design, Development, Implementation, Evaluation) structures how AI can be systematically integrated into teaching practice, from identifying learning needs to evaluating outcomes. The RISEN framework (Role, Input, Steps, Evaluation, Next) provides faculty with a structured method for developing effective AI prompts and maintaining academic rigor. Together, these frameworks highlight how AI can be embedded purposefully rather than opportunistically. Participants will leave with strategies for incorporating AI into their own courses, including techniques for building equitable group work, creating adaptable case studies, and designing assignments that encourage students to critically evaluate AI as a partner in knowledge generation. By the end of the session, attendees will be equipped with replicable models to responsibly and creatively integrate AI into teaching and learning.

Publication Details

Journal
Digital Scholarship - UNLV (University of Nevada Reno)
Published
2025-10-17
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
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article

Teaching, Building, Learning: AI in Nursing Education

Digital Scholarship - UNLV (University of Nevada Reno)
Artificial Intelligence in Healthcare and Education
article

Teaching, Building, Learning: AI in Nursing Education

article en

Abstract

The session is grounded in two guiding frameworks. The ADDIE instructional design model (Analysis, Design, Development, Implementation, Evaluation) structures how AI can be systematically integrated into teaching practice, from identifying learning needs to evaluating outcomes. The RISEN framework (Role, Input, Steps, Evaluation, Next) provides faculty with a structured method for developing effective AI prompts and maintaining academic rigor. Together, these frameworks highlight how AI can be embedded purposefully rather than opportunistically. Participants will leave with strategies for incorporating AI into their own courses, including techniques for building equitable group work, creating adaptable case studies, and designing assignments that encourage students to critically evaluate AI as a partner in knowledge generation. By the end of the session, attendees will be equipped with replicable models to responsibly and creatively integrate AI into teaching and learning.

Digital Scholarship - UNLV (University of Nevada Reno)
Openalex Percentile: Top 44%
Artificial Intelligence in Healthcare and Education
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