Guide for Nursing Faculty: Implementing AI for Reflective Journaling and Digital Artifacts

Guide for Nursing Faculty: Implementing AI for Reflective Journaling and Digital Artifacts

This guide provides nursing faculty with recommendations on implementing AI in an undergraduate pre-licensure nursing course to encourage reflective journaling and the development of digital artifacts. It draws upon research and expert insights from the provided sources.

AI and Nursing Education: An Overview

AI is transforming healthcare and nursing practice, making it imperative to integrate AI education into nursing curricula (Buchanon et al., 2021). Nursing students must be prepared to work effectively and safely with AI health technologies (AIHTs) in clinical settings (Buchanon et al., 2021). This involves understanding:

• How AI is being used in healthcare, including examples such as clinical decision support systems, virtual avatar apps, and social robots (Buchanon et al., 2021).
• Key AI concepts like machine learning (ML) and predictive analytics (Buchanon et al., 2021).
• The ethical and privacy implications of using AIHTs in healthcare (Buchanon et al., 2021).

Nurse educators play a vital role in facilitating this integration, ensuring students develop the necessary competencies to thrive in AI-driven healthcare environments (Buchanon et al., 2021).

Reflective Journaling with AI

Reflective learning encourages healthcare professionals to apply evidence-based innovations to their clinical practice (Cohen et al., 2023). AI can be utilized to enhance this process. AI-driven digital platforms can provide a framework for reflective learning (Cohen et al., 2023).  Features of such platforms include:

• Contextual prompts: AI can generate prompts related to the educational content, encouraging students to reflect on key concepts (Cohen et al., 2023).
• Analysis of reflections: AI can be used to analyze student reflections, identifying trends and insights that can inform curriculum development and support student learning (Cohen et al., 2023).

Students can use AI tools to:

• Generate ideas for their reflections.
• Assist with writing and expressing their thoughts clearly.
• Gain instant feedback on their writing.

It is crucial to establish guidelines for responsible AI use, ensuring academic integrity and avoiding plagiarism (Lee et al., 2024).

This includes:

• Educating students on proper citation practices when using AI for writing.
• Implementing plagiarism-checking software.
• Having clear policies on the acceptable use of AI tools in coursework.

Developing Digital Artifacts with AI and the Humanities

Digital artifacts can be created to demonstrate student learning in innovative ways. The humanities can provide a rich context for these artifacts.

Examples of digital artifacts students could develop using AI:

• Interactive patient simulations: Using AI tools like ChatGPT, students could create interactive simulations of patient encounters, incorporating ethical and cultural considerations informed by humanities perspectives.
• Visual representations of complex concepts: AI can assist students in creating visual representations of complex nursing concepts, such as infographics or videos, that integrate humanistic themes like empathy and patient-centered care.
• Digital storytelling: Students could use AI tools to create digital stories based on their clinical experiences, incorporating ethical reflections and insights from literature, art, or history.

Connecting AI to Humanities: Encourage students to explore how humanistic concepts, like empathy, ethics, and cultural awareness, relate to AI applications in healthcare. Use examples from literature, film, or art to illustrate the human impact of AI in healthcare. Facilitate discussions on the ethical dilemmas that may arise from the use of AI in nursing practice.

Implementing AI in the Course

• Start with clear learning objectives: Define what you want students to achieve through AI-assisted reflective journaling and digital artifact development.
• Select appropriate AI tools: Choose tools that are user-friendly, accessible, and align with your learning objectives.
• Provide training and support: Offer students orientation sessions on using the chosen AI tools. Create resources like tutorials or FAQs.
• Foster a collaborative learning environment: Encourage students to share their experiences and learn from each other.
• Assess student learning: Develop assessment strategies that evaluate students’ understanding of AI concepts, their ability to use AI effectively, and the quality of their reflections and digital artifacts.
• Continuously evaluate and adapt: Regularly assess the effectiveness of the AI integration and make adjustments as needed.

Addressing Challenges and Concerns

• Privacy and security: Ensure that student data is protected and used responsibly. Choose AI platforms with strong privacy policies and inform students about data usage.
• Ethical considerations: Facilitate open discussions about the ethical implications of AI in healthcare. Develop guidelines for responsible AI use that promote fairness, transparency, and accountability.
• Resistance to adoption: Be prepared to address faculty concerns about AI integration. Provide clear communication, training, and support to alleviate anxieties and foster a positive attitude towards AI.

By implementing AI thoughtfully and ethically, nursing faculty can empower students to develop critical thinking skills, enhance their reflective practice, and create innovative digital artifacts that showcase their learning and prepare them for the future of nursing.

References:

Buchanan, C., Howitt, M. L., Wilson, R., Booth, R. G., Risling, T., & Bamford, M. (2021). Predicted influences of artificial intelligence on nursing education: Scoping review. JMIR Nursing, 4(1), e23933. https://doi.org/10.2196/239333

Cohen, B., DuBois, S., Lynch, P. A., Swami, N., Noftle, K., & Arensberg, M. B. (2023). Use of an artificial intelligence-driven digital platform for reflective learning to support continuing medical and professional education and opportunities for interprofessional education and equitable access. Education Sciences, 13(8), 760. https://doi.org/10.3390/educsci13080760

Lee, S., Yoon, J.Y. & Hwang, Y. (2024). Collaborative project-based learning in global health: Enhancing competencies and skills for undergraduate nursing students. BMC Nursing, 23, 437. https://doi.org/10.1186/s12912-024-02111-8

Other AI in Nursing Education EBP Resources for Faculty

Bozkurt, A., Karadeniz, A., Baneres, D., Guerrero-Roldán, A. E., & Rodríguez, M. E. (2021). Artificial intelligence and reflections from educational landscape: A review of AI studies in half a century. Sustainability, 13(1), 800. https://doi.org/10.3390/su13010800

De Gagne, J. C. (2023). The state of artificial intelligence in nursing education: Past, present, and future directions. International Journal of Environmental Research and Public Health, 20(6), 4884. https://www.mdpi.com/1660-4601/20/6/4884

Ronquillo, C. E., Peltonen, L.-M., Pruinelli, L., Chu, C. H., Beduschi, A., Cato, K., Hardiker, N., Junger, A., Michalowski, M., Nibber, R., Rahimi, S., Reed, D. N., Salanterä, S., Topaz, M., Walton, N., Weber, P., & Wiegand, T. (2021). Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative. Journal of Advanced Nursing, 77(7), 3707–3717. https://doi.org/10.1111/jan.148551