Enhancing Nursing Education Through AI-Driven Adaptive Learning Systems

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2025 | Volume : 15 | Issue : 02 | Page : 29 34
    By

    Ambali Pancholi,

  • Berlin Sara Thampy,

  1. Research Scholar, Department of Nursing Education and Administration Malwanchal University, Madhya Pradesh, India
  2. Research Supervisor, Department of Nursing Education and Administration Malwanchal University, Madhya Pradesh, India

Abstract

The integration of Artificial Intelligence (AI) in nursing education offers significant potential to enhance learning experiences by personalizing education, improving knowledge retention, and developing clinical competencies. This study evaluates the effectiveness of AI-driven adaptive learning systems compared to traditional lecture-based teaching methods in nursing education. A mixed-methods approach was used, with 200 nursing students participating in a quasi-experimental design. The intervention group (100 students) used AI-powered adaptive learning platforms for 12 weeks, while the control group (100 students) followed traditional learning methods. Data were collected through pre- and post-test assessments, surveys, interviews, and academic performance records. The results revealed that students in the AI group demonstrated significant improvements in both theoretical knowledge and clinical competency, with a 35% increase in post-test scores, compared to a 15% improvement in the control group. Additionally, the AI group showed a 30% increase in clinical decision-making abilities, while the control group had a 10% improvement. Engagement and motivation were notably higher in the AI group, with 85% of students reporting increased motivation, compared to 58% in the control group. Furthermore, the AI group experienced a 50% reduction in pre-clinical anxiety and a 40% increase in clinical confidence, while the control group showed less significant changes. These findings indicate that AI-driven adaptive learning systems can significantly improve nursing education by enhancing knowledge retention, clinical competencies, student engagement, and reducing anxiety. The study suggests that AI integration holds great promise for transforming nursing education and preparing students for the challenges of modern healthcare.

Keywords: AI, adaptive learning, nursing education, clinical competency, student engagement, knowledge retention

[This article belongs to Journal of Nursing Science & Practice ]

How to cite this article:
Ambali Pancholi, Berlin Sara Thampy. Enhancing Nursing Education Through AI-Driven Adaptive Learning Systems. Journal of Nursing Science & Practice. 2025; 15(02):29-34.
How to cite this URL:
Ambali Pancholi, Berlin Sara Thampy. Enhancing Nursing Education Through AI-Driven Adaptive Learning Systems. Journal of Nursing Science & Practice. 2025; 15(02):29-34. Available from: https://journals.stmjournals.com/jonsp/article=2025/view=208562


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Regular Issue Subscription Original Research
Volume 15
Issue 02
Received 12/04/2025
Accepted 01/06/2025
Published 19/06/2025
Publication Time 68 Days
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