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Pardamean, B., Suparyanto, T., Cenggoro, T. W., Sudigyo, D., & Anugrahana, A. (2022). AI-Based Learning Style Prediction in Online Learning for Primary Education. IEEE Access, 10, 35725-35735.
https://doi.org/10.1109/access.2022.3160177

has been cited by the following article:

• TITLE: Artificial Intelligence in Nursing Education: Challenges and Opportunities in the Chinese Context

  AUTHORS: Yuan Jiang

  KEYWORDS: Artificial Intelligence, Nursing Education, Virtual Simulations, Personalized Learning, China, AI-Powered Assessments, Educational Equity, Technological Infrastructure, Data Privacy

  JOURNAL NAME: Open Journal of Social Sciences, Vol.12 No.11, November 7, 2024

  ABSTRACT: In China, where nursing education faces challenges such as unequal resource distribution, limited access to clinical training, and scalability issues, artificial intelligence (AI) has emerged as a transformative force. This study examines the integration of AI technologies, particularly virtual simulations and personalized learning systems, in Chinese nursing education. It explores how these advancements address educational inequities, improve teaching efficiency, and enhance student outcomes. Through case studies and performance evaluations, the benefits of AI tools in creating immersive and tailored learning experiences are highlighted. However, the study also acknowledges challenges, such as ethical concerns surrounding sensitive student data and the infrastructural disparities that may limit AI’s effectiveness in under-resourced areas. Finally, the global implications of China’s AI applications in nursing education are evaluated, offering recommendations for future research, including emotional intelligence algorithms and adaptive learning systems, to further enhance healthcare practice and decision-making.