Other Titles
AI Chatbots as Innovative Teaching Tools to Prepare Nursing Students for Difficult Clinical Conversations [Title Slide]
Abstract
Background and Significance: Therapeutic communication is a core competency in nursing and a consistently prioritized workforce requirement (Broeckelman-Post et al., 2022; McGunagle & Zizka, 2020; AACN, 2021). As AI and digital learning technologies advance, nursing programs are exploring technology-enabled strategies to better prepare students for emotionally complex patient interactions. Although AI chatbots have shown value in clinical training and simulation (Chang et al., 2021; Srinivasan et al., 2024), limited evidence exists on their use to prepare students for difficult or sensitive conversations. Addressing this gap supports student resilience and prepares future nurses for communication-intensive roles.
Purpose and Aims: This study evaluates a tiered experiential learning model designed to prepare undergraduate and graduate nursing students for difficult conversations prior to standardized patient encounters. The project adapts and pilots an AI-supported communication tool that allows students to practice, reflect, and receive structured feedback.
Design and Methods: Approximately 80 students complete a two-phase sequence. In Phase 1, students conduct a difficult conversation with an AI chatbot simulating a patient or family member and receive immediate, behavior-specific feedback. In Phase 2, they engage in a live standardized patient encounter. Communication rubrics and post-activity surveys assess performance, usability, and perceived preparedness. Data are analyzed using descriptive statistics and thematic coding.
Analysis, Outcomes, and Nursing Implications: Forty-seven students (45 undergraduate, 2 graduate) completed the initial survey, with 46 providing full responses; eight completed a follow-up survey. Findings were strongly positive: 76.1% reported increased confidence, 89.1% valued the AI-generated feedback, 82.6% felt better prepared for real-world conversations, and 71.7% enjoyed the experience. Qualitative themes emphasized increased confidence, reduced anxiety, and appreciation for actionable feedback, with some concerns about conversational flexibility.
Based on these results, the chatbot was updated and expanded across the undergraduate curriculum. The revised tool was implemented with traditional and accelerated nursing students this fall. Additional outcome data from this broader rollout are being collected and will be reported at semester’s end to further evaluate impact, scalability, and integration into communication training.
Notes
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Funding Disclosure: Creighton Center for Undergraduate Research and Scholarship (CURAS) Magis! Investigatio Research Award (MIRA)
References:
Broeckelman-Post, M. A., & Mazer, J. P. (2022). Editors' introduction: Online teaching: challenge or opportunity for Communication Education scholars. Communication Education, 71(2), 145.
McGunagle, D., & Zizka, L. (2020). Employability skills for 21st-century STEM students: The employers' perspective. Higher Education, Skills and Work-Based Learning, 10(3), 591–606.
American Association of Colleges of Nursing. (2021). The Essentials: Competencies for Professional Nursing Education.
Chang, C., Hwang, G., & Gau, M. (2021). Promoting students’ learning achievement and self-efficacy: A mobile chatbot approach for nursing training. British Journal of Educational Technology, 53(1), 171–188. https://doi.org/10.1111/bjet.13158
Srinivasan, M., Venugopal, A., Venkatesan, L., & Kumar, R. (2023). Navigating the pedagogical landscape: Exploring the implications of AI and chatbots in nursing education. JMIR Nursing, 7, e52105. https://doi.org/10.2196/52105
Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589–597.
Sigma Membership
Iota Tau
Type
Presentation
Format Type
Text-based Document
Study Design/Type
Other
Research Approach
Mixed/Multi Method Research
Keywords:
Curriculum Development, Simulation, Hospice, Palliative, or End-of-Life Care, Nursing Students, Nursing Education, Chatbots, Conversation, Difficult Conversations
Recommended Citation
Iverson, Lindsay; Oliver, Tamara; Fernandes, Steven; Kirkpatrick, Mandy; Morgan, Kara; Guthrie, Lauren; Beiermann, Trisha; and Taylor, Melissa, "Innovative Teaching Strategies: AI Chatbots to Prepare Nursing Students for Difficult Conversations" (2026). International Nursing Research Congress (INRC). 270.
https://www.sigmarepository.org/inrc/2026/presentations_2026/270
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
2026-09-06
Innovative Teaching Strategies: AI Chatbots to Prepare Nursing Students for Difficult Conversations
Toronto, Ontario, Canada
Background and Significance: Therapeutic communication is a core competency in nursing and a consistently prioritized workforce requirement (Broeckelman-Post et al., 2022; McGunagle & Zizka, 2020; AACN, 2021). As AI and digital learning technologies advance, nursing programs are exploring technology-enabled strategies to better prepare students for emotionally complex patient interactions. Although AI chatbots have shown value in clinical training and simulation (Chang et al., 2021; Srinivasan et al., 2024), limited evidence exists on their use to prepare students for difficult or sensitive conversations. Addressing this gap supports student resilience and prepares future nurses for communication-intensive roles.
Purpose and Aims: This study evaluates a tiered experiential learning model designed to prepare undergraduate and graduate nursing students for difficult conversations prior to standardized patient encounters. The project adapts and pilots an AI-supported communication tool that allows students to practice, reflect, and receive structured feedback.
Design and Methods: Approximately 80 students complete a two-phase sequence. In Phase 1, students conduct a difficult conversation with an AI chatbot simulating a patient or family member and receive immediate, behavior-specific feedback. In Phase 2, they engage in a live standardized patient encounter. Communication rubrics and post-activity surveys assess performance, usability, and perceived preparedness. Data are analyzed using descriptive statistics and thematic coding.
Analysis, Outcomes, and Nursing Implications: Forty-seven students (45 undergraduate, 2 graduate) completed the initial survey, with 46 providing full responses; eight completed a follow-up survey. Findings were strongly positive: 76.1% reported increased confidence, 89.1% valued the AI-generated feedback, 82.6% felt better prepared for real-world conversations, and 71.7% enjoyed the experience. Qualitative themes emphasized increased confidence, reduced anxiety, and appreciation for actionable feedback, with some concerns about conversational flexibility.
Based on these results, the chatbot was updated and expanded across the undergraduate curriculum. The revised tool was implemented with traditional and accelerated nursing students this fall. Additional outcome data from this broader rollout are being collected and will be reported at semester’s end to further evaluate impact, scalability, and integration into communication training.
Description
This study evaluates a tiered learning model using an AI chatbot to help nursing students prepare for difficult conversations. Students first practice with the chatbot and receive real-time feedback, then engage in a standardized patient encounter. Early results show strong engagement and increased confidence. The updated tool was rolled out to traditional and accelerated students this fall, with additional data forthcoming.