Using artificial intelligence to design adaptive educational systems for children with diverse learning styles

The integration of Artificial Intelligence (AI) in educational systems presents transformative potential for personalized learning experiences, particularly in adaptive educational systems designed for children with diverse learning styles. This study delves into the multifaceted role of AI in identifying, assessing, and addressing varying learning preferences, emphasizing the synergy between AI algorithms and educational psychology frameworks. By leveraging AI-driven data analytics, adaptive learning platforms can dynamically adjust content delivery based on auditory, visual, and kinesthetic learning modalities, thereby enhancing educational outcomes and engagement. The proposed model not only highlights the technical aspects of AI integration but also incorporates psychological principles to ensure that adaptive systems are developmentally appropriate and inclusive. Furthermore, the study includes a comprehensive review of existing literature, presenting key case studies that exemplify successful implementation of AI-enhanced learning systems in diverse educational settings. We also examine potential challenges related to data privacy, algorithmic bias, and the ethical implications of deploying AI for child-centered learning. The findings underscore the critical importance of aligning AI applications with established educational psychology theories to foster adaptive learning environments that are both effective and ethically responsible.

کلیدواژه ها:

Artificial Intelligence ، Adaptive Learning Systems ، Educational Psychology ، Learning Styles ، Personalized Education ، Child Development ، EdTech ، Learning Analytics