ABSTRACT

Grading Graduate Nursing Students’ Original Written Work with AI Detection Introduction The integration of artificial intelligence (AI) into academic nursing graduate work has transformed how written assignments are produced and assessed. In graduate nursing education, ensuring the originality of scholarly writing is crucial for promoting professional integrity and academic excellence (Simms, R.C., 2025). Purpose: This project explores the application of AI detection tools in grading original written assignments of graduate nursing students, aiming to ensure academic integrity while enhancing assessment accuracy. Methods A sample of two terms of written assignments from an advanced writing course was evaluated using AI detection software Turnitin’s AI writing indicator. Faculty compared AI-generated Turnitin probability scores with traditional rubrics and plagiarism checks to determine alignment, flag potential misuse, and assess originality (Blomquist, J. 2025). Results: Preliminary findings revealed that approximately 18% of submissions showed over 60% of AI-assisted content. Faculty reported improved ability to identify unoriginal writing that was not flagged through conventional plagiarism tools. However, false positives were noted in non-native English speakers. Discussion: While AI detection tools offer valuable insights, their use must be coupled with faculty judgment and clear AI percentage limit guidelines. Transparency, communication, education on ethical writing practices, and formative student feedback are essential to maintaining fairness. Conclusion AI detection tools can enhance the evaluation process efficiency of graduate nursing writing by identifying patterns that suggest AI use. However, these tools should not replace faculty discernment. Continued research is needed to refine best practices for ethical integration in academic assessment.