JMIR Publications

ABSTRACT

Background:

The rapid integration of artificial intelligence (AI) in higher education has generated increasing interest in AI chatbots as virtual tutors in nursing education. These tools have the potential to provide personalized, on-demand support in asynchronous learning environments, where students often experience limited interaction and delayed feedback. Despite growing adoption, there is a lack of empirically grounded research on effective instructional design approaches and student learning experiences associated with AI chatbot integration in nursing education.

Objective:

This study aimed to examine undergraduate nursing students’ learning experiences with, and perceptions of, an AI chatbot designed as a virtual tutor in an asynchronous online course. A secondary objective was to explore the effectiveness of the PROSE (Persona, Rubric, Objective, Steps, Example) model as a framework for aligning chatbot interactions with course learning objectives.

Methods:

An institutional review board–approved mixed-methods pilot study was conducted with 66 undergraduate nursing students enrolled in an asynchronous online course at a large public university in the United States. The chatbot was integrated into course activities to provide formative feedback on writing assignments and support quiz preparation. Data collection included pre- and post-intervention surveys measuring perceptions, attitudes, and expectations of AI (30 Likert-scale items), as well as a post-activity survey with quantitative and open-ended qualitative responses. Quantitative data were analyzed using descriptive statistics, and qualitative data were analyzed using thematic analysis to identify patterns in student experiences.

Results:

Findings indicated consistent increases across all measured domains, including perceptions of AI in professional contexts, attitudes toward AI technology, and expectations for AI-supported feedback and mentorship. Students reported that the chatbot enhanced interactivity, reduced feelings of isolation, and supported self-directed learning and understanding of complex content. Qualitative findings highlighted key benefits such as immediate access to assistance, alternative explanations, and support for studying and assessment preparation. However, students also identified challenges related to accuracy, response specificity, technical performance, and concerns about reduced human interaction and potential overreliance on AI tools.

Conclusions:

AI chatbots designed with pedagogical alignment can serve as valuable supplemental tools in online nursing education by enhancing engagement and perceived learning support. However, effective implementation requires careful attention to accuracy, transparency, and the preservation of human instructor presence. These findings suggest that AI chatbots are most effective when positioned as complements to, rather than replacements for, human teaching, and when integrated through structured instructional design frameworks such as the PROSE model.