Teaching Nursing Students Effective Artificial Intelligence Prompt Engineering: The CARE Framework
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Published on: December 15, 2023
Mary E Bester1, Kathryn Zeigler
1Author Affiliations: School of Nursing, Savannah, Georgia.
Background:
Effective artificial intelligence (AI) prompting is essential for students to use AI to enhance critical thinking and clinical decision-making skills.
Methods:
A framework for effective prompting, the CARE (Context, Action, Role, Expectation) Prompt Engineering Framework, was developed. This framework emphasizes the importance of maintaining the "human connection" in AI.
Results:
When students use AI, they use their skills to ask AI for information. Instructors should model responsible and effective AI-prompt engineering. Each CARE element is discussed with remedial prompting to ensure more effective output. AI outputs are verified and reviewed; the original context is revised with the desired changes; and follow-up actions are submitted.
Conclusions:
The CARE framework provides a systematic outline for nurse educators to use in teaching students clinical decision-making skills, while also capturing the role-modeling behavior of faculty members to ensure that effective AI prompts are used.
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