Generative Artificial Intelligence and the Development and Management of Educational Resources: Benefits, Challenges, and Solutions

The integration of generative AI (GenAI) in education presents critical opportunities for the development and management of educational resources, enhancing both the efficiency and effectiveness of teaching practices. However, this advancement is accompanied by several challenges, including concerns regarding content reliability, limited diversity in generated materials, inadequate customization for diverse learning needs, inherent data biases, and complexities in system integration. This research aims to critically analyze these challenges while proposing effective strategies to optimize the utilization of GenAI in educational contexts. Proposed solutions encompass the establishment of dedicated data frameworks, comprehensive manual content reviews, data diversification techniques, and the implementation of multidimensional algorithms that accommodate varied educational demands. Additionally, strategies such as user data integration, multimodal approaches, source tracking, bias detection mechanisms, and standardization practices are explored. Ultimately, this study underscores the transformative potential of GenAI in fostering innovative educational practices, suggesting that its thoughtful application can lead to substantial improvements in learning outcomes and greater accessibility of educational re-sources.