Children with multiple disabilities those who experience a concurrent combination of physical, sensory, cognitive, or behavioral impairments present some of the most complex and meaningful challenges in education today.
In this paper, we identify AI or ML-powered inclusive education tools and technologies, explore the factors required for developing personalized learning plans using AI, and propose a real-time personalized learning framework.
Such details provide a deeper understanding and appreciation for Personalized Multiple Intellectual Difficulties Learning.
To support, parent, or educate a child with multiple disabilities, its important to know: how each disability can affect learning and daily living. The different disabilities will also have a combined impact.
Such details provide a deeper understanding and appreciation for Personalized Multiple Intellectual Difficulties Learning.
In this article, we briefly summarize the findings in our search for the talents of students labeled learning disabled, evidence of their abilities, implications of these for the schools, and a beginning set of practical recommendations.
In the article of implementation studies across various educational contexts, we explore how AI-powered applications create personalized learning experiences through adaptive algorithms, cognitive assessment capabilities, and data-driven content customization.
Guided by the Cognitive Learning Processes Adaptation Model (CLPAM), this meta-analysis provides a theory-driven synthesis of how AI-based educational interventions support core cognitive learning processes in students with disabilities.
