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Using Learning Outcome Measures to assess Doctoral Nursing Education
Published on: June 21, 2010
AI-generated vs. student-crafted assignments and implications for evaluating student work in nursing: an exploratory
Kateryna Metersky1, Kaveenaa Chandrasekaran1, Rezwana Rahman1
1Daphne Cockwell School of Nursing, Toronto Metropolitan University, Toronto, ON, Canada.
Nursing educators can identify AI-generated content by recognizing outdated references and a lack of depth in ChatGPT-3.5 assignments. Understanding AI capabilities is crucial for maintaining academic integrity in nursing education.
Area of Science:
- Artificial Intelligence in Education
- Academic Integrity in Nursing
Background:
- The emergence of advanced AI language models like ChatGPT (Chat Generative Pre-Trained Transformer) presents challenges to academic integrity in nursing education.
- Students may utilize AI tools to generate assignment content, necessitating methods for detection.
Purpose of the Study:
- To explore and identify effective strategies for nursing educators to distinguish between AI-generated and student-written academic submissions.
- To address concerns regarding the use of AI in nursing education and its impact on learning.
Main Methods:
- Four nursing students were instructed to produce two versions of a Letter to the Editor assignment.
- One version was student-written, while the other was exclusively generated by ChatGPT-3.5.
Main Results:
- AI-generated assignments exhibited strong grammar but often contained outdated, inaccurate, or fabricated scholarly references.
- Submissions generated by ChatGPT-3.5 generally lacked the expected level of detail and depth compared to student work.
Conclusions:
- Nursing educators require a foundational understanding of AI technologies like ChatGPT to foster student knowledge development.
- Implementing strategies to identify AI-generated content is essential for upholding academic integrity in nursing programs.
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