Development of AI-assisted evidence-based nursing learning resource allocation and educational strategies for senior nursing students considering gender factors

The critical need for Evidence-Based Practice (EBP) competency among graduating nursing students is paramount for healthcare quality and patient safety. This study aims to develop a novel AI-assisted framework to optimize learning resource allocation and formulate educational strategies for senior nursing diploma students, with deliberate consideration of gender factors. The proposed model integrates adaptive learning theories with a hybrid AI engine, utilizing clustering and predictive analytics to create dynamic, personalized learning pathways. By operationalizing gender as a correlative analytic variable, the framework seeks to generate gender-sensitive strategies for educators, thereby promoting a more equitable and effective EBP education model. The outcomes include a comprehensive conceptual framework, a detailed technical blueprint, and a portfolio of intervention strategies, establishing a foundation for future empirical validation and implementation in nursing education.