A Generative AI Virtual Teaching Assistant for Graduate Nursing Informatics Education

Abstract

Nursing informatics and generative artificial intelligence are emerging as key enablers of competency-based education in nursing, supporting educators in delivering personalized support while maintaining quality, flexibility, and efficiency. The Joint Artificial Intelligence Model in Education, a custom generative pretrained transformer, was developed to assist doctoral nursing students with academic writing, assignment clarification, and practicum guidance. To ensure pedagogical and contextual relevance, its design was grounded in the Technological Pedagogical Content Knowledge framework and the Purpose, Integration, Curriculum/Replacement, Amplification, Transformation model, and aligned with the American Association of Colleges of Nursing Essentials. The tool was trained on course-specific resources, including rubrics, policies, and instructional materials, then piloted in a graduate nursing informatics course. Evaluation measures included data from the learning management system, student performance, and qualitative feedback. Findings indicated that the tool promoted learner autonomy and was used frequently outside business hours and on weekends; however, usage showed limited correlation with academic performance, underscoring its supplemental role. Faculty reported fewer frequently asked questions and an improvement in instructional efficiency. Students valued its accessibility, nonjudgmental tone, and 24/7 availability. This article strengthens the evidence base, demonstrates feasibility, and offers a replicable model for integrating artificial intelligence into nursing education.

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