Other Titles
Empowering Nursing Education with AI: From Policy to Practice – Strategies for Faculty Success [Symposium Title]
Other Titles
Symposium Presentation
Abstract
As artificial intelligence (AI) tools become increasingly prevalent in higher education, nursing faculty face the complex task of developing comprehensive course policies that address both the opportunities and challenges these technologies present. This presentation provides guidance for crafting effective AI policies via course syllabi through faculty reflection on course content, pedagogy, and enhancing active learning.
Faculty will learn a structured practice for developing AI syllabi statements that align with course objectives while preserving essential nursing competencies. The practice framework addresses five critical elements: clear policy articulation, pedagogical rationale, specific usage guidelines, transparency requirements, and integration within existing academic integrity policies.1 Special attention will be given to discipline-specific considerations, including patient privacy, clinical documentation, and professional practice standards.
The presentation will also examine current AI detection software tools, their reliability, and limitations.2 Understanding these technological constraints is crucial for developing realistic policies and assessment strategies that uphold academic integrity while maintaining a student-focused relationship.3,4 Participants will receive practical examples of syllabus language, discussion prompts for engaging students in policy development, and strategies for updating policies as AI technology evolves.1
This guidance empowers nursing faculty to develop clear, pedagogically-sound AI policies that prepare students for contemporary professional practice without compromising academic integrity. Faculty will leave with ready-to-use strategies for developing and implementing AI policies that promote consistency across their programs while accommodating emerging technologies.
Notes
References:
1. Estrem, H., Blomquist, J., Long, L. (2024). A guide to teaching and learning with artificial intelligence. Idaho Pressbooks. https://idaho.pressbooks.pub/airesourceguide/
2. Chaka, C. (2024). Reviewing the performance of AI detection tools in differentiating between AI-generated and human-written texts: A literature and integrative hybrid review. Journal of Applied Learning & Teaching, 7(1). https://doi.org/10.37074/jalt.2024.7.1.14
3. Luo, J. (2024). How does GenAI affect trust in teacher-student relationships? Insights from students’ assessment experiences. Teaching in Higher Education, 1-16.
4. Walters, W. H. (2023). The effectiveness of software designed to detect AI-generated writing: A comparison of 16 AI text detectors. Open Information Science, 7(1), 20220158.
Sigma Membership
Mu Gamma at-Large
Type
Presentation
Format Type
Text-based Document
Study Design/Type
Other
Research Approach
Other
Keywords:
Faculty Development, Teaching and Learning Strategies, Nursing Education, Emerging Technologies, Artificial Intelligence, AI
Recommended Citation
Blomquist, Jason, "Reflecting on AI Use Through Syllabus Statement Development" (2025). Biennial Convention (CONV). 255.
https://www.sigmarepository.org/convention/2025/presentations_2025/255
Conference Name
48th Biennial Convention
Conference Host
Sigma Theta Tau International
Conference Location
Indianapolis, Indiana, USA
Conference Year
2025
Rights Holder
All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record. All permission requests should be directed accordingly and not to the Sigma Repository. All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.
Review Type
Abstract Review Only: Reviewed by Event Host
Acquisition
Proxy-submission
Date of Issue
2025-12-11
Reflecting on AI Use Through Syllabus Statement Development
Indianapolis, Indiana, USA
As artificial intelligence (AI) tools become increasingly prevalent in higher education, nursing faculty face the complex task of developing comprehensive course policies that address both the opportunities and challenges these technologies present. This presentation provides guidance for crafting effective AI policies via course syllabi through faculty reflection on course content, pedagogy, and enhancing active learning.
Faculty will learn a structured practice for developing AI syllabi statements that align with course objectives while preserving essential nursing competencies. The practice framework addresses five critical elements: clear policy articulation, pedagogical rationale, specific usage guidelines, transparency requirements, and integration within existing academic integrity policies.1 Special attention will be given to discipline-specific considerations, including patient privacy, clinical documentation, and professional practice standards.
The presentation will also examine current AI detection software tools, their reliability, and limitations.2 Understanding these technological constraints is crucial for developing realistic policies and assessment strategies that uphold academic integrity while maintaining a student-focused relationship.3,4 Participants will receive practical examples of syllabus language, discussion prompts for engaging students in policy development, and strategies for updating policies as AI technology evolves.1
This guidance empowers nursing faculty to develop clear, pedagogically-sound AI policies that prepare students for contemporary professional practice without compromising academic integrity. Faculty will leave with ready-to-use strategies for developing and implementing AI policies that promote consistency across their programs while accommodating emerging technologies.
Description
Overall Symposium Summary: Explore strategies to transform your nursing courses with practical and meaningful integration of AI tools and concepts. This interactive, hands-on symposium equips faculty with tools for crafting AI syllabus policies, enhancing literature searches, and developing competency-based assessments. Join colleagues in exploring how AI can enhance nursing education, student engagement, and assessment development while maintaining professional and academic standards.
Note: The attached slide deck is a combined symposium presentation containing the slides of all featured symposium speakers.
To locate the other presentations in this symposium, search the repository by the Symposium Title shown in the Other Title field of this item record.