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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

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Undergraduate Nursing Students' Experiences With Artificial Intelligence in a Research and Evidence-based Practice

Amy Reed¹, Angela Andrews, Erica Frost

¹School of Nursing, Southern Illinois University Edwardsville, Edwardsville, IL.

Computers, Informatics, Nursing : CIN

|December 23, 2025

Summary

Senior nursing students showed increased comfort and trust with artificial intelligence (AI) tools after structured course integration. While interested in AI for academic tasks, they also raised concerns about ethical use and accuracy.

Keywords:

AI literacy artificial intelligence nursing education nursing research

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Published on: December 9, 2022

Area of Science:

Nursing Education
Artificial Intelligence in Healthcare
Technology Acceptance

Background:

Artificial intelligence (AI) tools are increasingly prevalent in healthcare and education.
Understanding nursing students' perspectives on AI is crucial for effective integration.
Existing frameworks like the Unified Theory of Acceptance and Use of Technology can guide AI adoption studies.

Purpose of the Study:

To explore senior nursing students' attitudes, experiences, and intentions regarding AI integration in a research and evidence-based practice course.
To assess the impact of structured AI activities on students' perceptions of AI usefulness, trust, and comfort.
To identify student concerns and interests related to AI in academic and clinical nursing settings.

Main Methods:

Utilized the Unified Theory of Acceptance and Use of Technology as a guiding framework.
Administered the General Attitudes Toward Artificial Intelligence Scale for quantitative data.
Collected qualitative data through open-ended reflection prompts following structured AI activities.
Compared pre- and post-intervention survey data to identify changes in student attitudes.

Main Results:

Students reported increased comfort, trust, and perceived usefulness of AI tools in academic and clinical contexts.
A statistically significant positive change was observed in students' views on the ethical use of AI in nursing (P < .05).
Students expressed interest in using AI for academic tasks but also voiced concerns regarding ethical use, accuracy, and over-reliance.

Conclusions:

Structured, faculty-supported AI integration in nursing education enhances student acceptance and engagement.
Addressing student concerns about ethics, accuracy, and reliance is vital for successful AI implementation.
Findings support the development of best practices for AI in nursing education to prepare future healthcare professionals.