Other Titles
The Future of Nursing Education: Discovering the Use of Al Avatars for Interactive Curriculum in Online Asynchronous Classes [Title Slide]
Other Titles
PechaKucha Presentation
Abstract
This project introduces an innovative telehealth simulation using artificial intelligence avatars in a graduate-level online informatics course to enhance student engagement and develop digital health competencies aligned with national nursing education standards. Nursing education has historically lagged in integrating interactive, competency-based digital health training, particularly in online environments, despite the growing role of technology in healthcare delivery (Kleib et al., 2024; El Arab et al., 2025). Traditional simulation approaches often fail to incorporate emerging technologies such as artificial intelligence (AI), leaving a gap in preparing nurses for technology-driven practice (Chan et al., 2025; Buchanan et al., 2021). The project intervention replaces a static written assignment to educate patients on digital tools for their chronic condition with an interactive telehealth simulation featuring AI avatars that replicate patient encounters and provide rubric-guided feedback. Students engage with diverse patient scenarios supported by tutorials and faculty trained on the AI avatars. The design follows a systems life cycle framework to ensure structured development and evaluation (McGonigle & Mastrian, 2022). Evaluation will use mixed methods. Quantitative data will be collected through validated usability and satisfaction measures, including the System Usability Scale and adapted telehealth evaluation items, complemented by open-ended questions for qualitative insights (Lewis, 2018; Phillips et al., 2020). Qualitative methods will include student and faculty Interviews to explore experiences. Analysis will include descriptive statistics and thematic analysis (Braun & Clarke, 2022). This innovation aligns with the American Association of Colleges of Nursing (AACN) Essentials, emphasizing technology-integrated education and informatics competencies (AACN, 2021). Future steps include refining the simulation based on student and faculty feedback, expanding implementation across courses, and conducting comparative studies with human-simulated patients. Broader research will explore scalability and integration into diverse learning contexts, positioning this approach as a transformative model for nursing education. Artificial intelligence-driven simulations represent a critical advancement in preparing nurses to deliver safe, high-quality care in digitally connected healthcare environments (Ronquillo et al., 2021; Labrague et al., 2025).
Notes
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References:
American Association of Colleges of Nursing. (2021). The essentials: Core competencies for professional nursing education. Washington, DC: AACN. https://www.aacnnursing.org/Essentials
Braun, V., & Clarke, V. (2022). Thematic analysis: A practical guide. Sage. https://us.sagepub.com/en-us/nam/thematic-analysis/book267148
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/10.2196/23933
Chan, M. M. K., Wan, A. W. H., Cheung, D. S. K., Choi, E. P. H., Chan, E. A., Yorke, J., & Wang, L. (2025). Integration of artificial intelligence in nursing simulation education: A scoping review. Nurse Educator. https://doi.org/10.1097/NNE.0000000000001851
El Arab, R. A., Al Moosa, O. A., Abuadas, F. H., & Somerville, J. (2025). The role of AI in nursing education and practice: Umbrella review. Journal of Medical Internet Research, 27, e69881. https://doi.org/10.2196/69881
Kleib, M., Arnaert, A., Nagle, L., Ali, S., Idrees, S., Costa, D. D., Kennedy, M., & Darko, E. M. (2024). Digital health education and training for undergraduate and graduate nursing students: Scoping review. JMIR Nursing, 7, e58170. https://doi.org/10.2196/58170
Labrague, L., Al Sabei, S., & Al Yahyaei, A. (2025). Artificial intelligence in nursing education: A review of AI-based teaching pedagogies. Teaching and Learning in Nursing. https://doi.org/10.1016/j.teln.2025.01.019
Lewis, J. R. (2018). The system usability scale: Past, present, and future. International Journal of Human–Computer Interaction, 34(7), 577–590. https://doi.org/10.1080/10447318.2018.1455307
Phillips, T. A., Munn, A. C., & George, T. P. (2020). Assessing the impact of telehealth objective structured clinical examinations in graduate nursing education. Nurse Educator, 45(3), 169–172. https://doi.org/10.1097/NNE.0000000000000729
Ronquillo, C. E., Peltonen, L. M., Pruinelli, L., Chu, C. H., Bakken, S., Beduschi, A., et al. (2021). Artificial intelligence in nursing: Priorities and opportunities. Journal of Advanced Nursing, 77(9), 3707–3717. https://doi.org/10.1111/jan.14855
Sigma Membership
Alpha Kappa at-Large
Type
Presentation
Format Type
Text-based Document
Study Design/Type
Other
Research Approach
Mixed/Multi Method Research
Keywords:
Teaching and Learning Strategies, Virtual Learning, Competence, Nursing Informatics, Nursing Informatics--Education, Digital Health, Clinical Competence, Telehealth, Simulations
Recommended Citation
Baker, Christina; Baik, Dawon; and Giarrizzo-Wilson, Sharon, "The Future of Nursing Education: Discovering Al Avatars for Interactive Online Asynchronous Classe" (2026). International Nursing Research Congress (INRC). 105.
https://www.sigmarepository.org/inrc/2026/presentations_2026/105
Conference Name
37th International Nursing Research Congress
Conference Host
Sigma Theta Tau International
Conference Location
Toronto, Ontario, Canada
Conference Year
2026
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
2026-07-30
The Future of Nursing Education: Discovering Al Avatars for Interactive Online Asynchronous Classe
Toronto, Ontario, Canada
This project introduces an innovative telehealth simulation using artificial intelligence avatars in a graduate-level online informatics course to enhance student engagement and develop digital health competencies aligned with national nursing education standards. Nursing education has historically lagged in integrating interactive, competency-based digital health training, particularly in online environments, despite the growing role of technology in healthcare delivery (Kleib et al., 2024; El Arab et al., 2025). Traditional simulation approaches often fail to incorporate emerging technologies such as artificial intelligence (AI), leaving a gap in preparing nurses for technology-driven practice (Chan et al., 2025; Buchanan et al., 2021). The project intervention replaces a static written assignment to educate patients on digital tools for their chronic condition with an interactive telehealth simulation featuring AI avatars that replicate patient encounters and provide rubric-guided feedback. Students engage with diverse patient scenarios supported by tutorials and faculty trained on the AI avatars. The design follows a systems life cycle framework to ensure structured development and evaluation (McGonigle & Mastrian, 2022). Evaluation will use mixed methods. Quantitative data will be collected through validated usability and satisfaction measures, including the System Usability Scale and adapted telehealth evaluation items, complemented by open-ended questions for qualitative insights (Lewis, 2018; Phillips et al., 2020). Qualitative methods will include student and faculty Interviews to explore experiences. Analysis will include descriptive statistics and thematic analysis (Braun & Clarke, 2022). This innovation aligns with the American Association of Colleges of Nursing (AACN) Essentials, emphasizing technology-integrated education and informatics competencies (AACN, 2021). Future steps include refining the simulation based on student and faculty feedback, expanding implementation across courses, and conducting comparative studies with human-simulated patients. Broader research will explore scalability and integration into diverse learning contexts, positioning this approach as a transformative model for nursing education. Artificial intelligence-driven simulations represent a critical advancement in preparing nurses to deliver safe, high-quality care in digitally connected healthcare environments (Ronquillo et al., 2021; Labrague et al., 2025).
Description
This project introduces interactive AI Avatar-driven telehealth simulations in graduate nursing education to enhance digital health competencies. Using a systems life cycle framework, the intervention replaces static assignments with interactive avatar encounters. Planned evaluation includes usability surveys, adapted telehealth measures, and thematic analysis of interviews. This innovation aligns with AACN Essentials and prepares nurses for technology-integrated practice.