Los puntos clave no están disponibles para este artículo en este momento.
The goal of this study is to determine how artificial intelligence (AI) has been utilized to serve students with learning disabilities Processes (SWLDP). I have evaluated research and focused on dyslexia, dyscalculia, and the remaining on learning disorders generally. According to the study, just half of the research was done on school-age children. Adaptive learning, facial expression, chat-bots, three categories of AI technologies that were utilized to serve SWLDP. Among them, adaptive learning was the most popular. We discovered that AI has been used to support SWLDP in a variety of ways by applying the SAMR-LD (substitute, augment, modify, and redefine learning disability) paradigm. The results demonstrated AI's potential to support SWLDP; however, the paucity of empirical studies also suggests important gaps and the need for additional study on AI's capacity to support SWLDP in ways that go beyond simply detecting and diagnosing learning disabilities.
Lal et al. (Wed,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: