Key result
Nursing students using the GoodNurse AI model achieved significantly higher grades in an ECG course compared to nonusers (95.1% vs 88.8%; P=0.0048).
Why the study?
ECG interpretation is a critical yet challenging skill for nurses, and generative AI offers potential for personalized, adaptive learning.
Does the use of domain-specific AI (GoodNurse) improve student performance and diagnostic accuracy in nursing ECG education?
Observational
Does the use of domain-specific AI (GoodNurse) improve student performance and diagnostic accuracy in nursing ECG education?
Domain-specific generative AI enhances ECG learning, diagnostic accuracy, and cost-efficiency in nursing education.
Answers are grounded in this paper and cite their sources.
Supports pilot integration of high-accuracy AI tools into nurse ECG curricula; leaves open validation in randomized educational trials.
Background: Electrocardiogram (ECG) interpretation is a critical yet challenging skill for nurses. Generative artificial intelligence (AI) offers potential for personalized, adaptive learning. Purpose: The aim was to evaluate the effectiveness, accuracy, and cost-efficiency of AI models in nursing ECG education. Methods: A 2-part study compared 4 AI models (GoodNurse, ChatGPT-5, Claude Sonnet 4, Microsoft Copilot) on an 88-item ECG exam and assessed cost-effectiveness. GoodNurse was then integrated into a 4-credit ECG course; AI usage, satisfaction, and grades were analyzed. Results: Accuracy varied ( P <.01): GoodNurse 85.3%, ChatGPT-5 83.1%, Copilot 80.9%, Sonnet 79.1%. GoodNurse had the fewest waveform errors and the best cost-per-accuracy ($8.06 per 1% gain). In the course, 43% of students used GoodNurse, achieving higher grades (95.1 ± 2.5%) than nonusers (88.8 ± 5.9%; P =.0048), with a $5.80 per 1% grade improvement. Conclusion: Domain-specific AI, such as GoodNurse, enhances ECG learning, diagnostic accuracy, and cost-efficiency, supporting its integration into nursing education.
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Dzikowicz et al. (2026) conducted an observational in ECG interpretation education. GoodNurse AI model vs. Nonusers (students) and other AI models (ChatGPT-5, Claude Sonnet 4, Microsoft Copilot) was evaluated on Student grades in a 4-credit ECG course (p=0.0048). Nursing students using the GoodNurse AI model achieved significantly higher grades in an ECG course compared to nonusers (95.1% vs 88.8%; P=0.0048).
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