This paper presents a comprehensive examination of how multimodal artificial intelligence (AI) approaches are paving the way towards the realization of Artificial General Intelligence (AGI) in educational contexts. It scrutinizes the evolution and integration of AI in educational systems, emphasizing the crucial role of multimodality, which encompasses auditory, visual, kinesthetic, and linguistic modes of learning. This research delves deeply into the key facets of AGI, including cognitive frameworks, advanced knowledge representation, adaptive learning mechanisms, strategic planning, sophisticated language processing, and the integration of diverse multimodal data sources. It critically assesses AGI's transformative potential in reshaping educational paradigms, focusing on enhancing teaching and learning effectiveness, filling gaps in existing methodologies, and addressing ethical considerations and responsible usage of AGI in educational settings. The paper also discusses the implications of multimodal AI's role in education, offering insights into future directions and challenges in AGI development. This exploration aims to provide a nuanced understanding of the intersection between AI, multimodality, and education, setting a foundation for future research and development in AGI.

翻译：本文全面审视了多模态人工智能方法如何在教育场景中为通用人工智能的实现铺平道路。文章深入探讨了人工智能在教育系统中的演进与整合，着重强调涵盖听觉、视觉、动觉及语言学习模式的多模态性所发挥的关键作用。本研究细致探究了通用人工智能的核心要素，包括认知框架、高级知识表征、自适应学习机制、战略规划、复杂语言处理以及多源多模态数据的整合。文章批判性地评估了通用人工智能在重塑教育范式方面的变革潜力，聚焦于提升教学成效、填补现有方法论的空白，并探讨了教育场景中通用人工智能应用的伦理考量与负责任使用。本文还讨论了多模态人工智能在教育领域的作用所蕴含的意义，为通用人工智能的未来发展方向与挑战提供了见解。本研究旨在提供对人工智能、多模态性与教育交叉领域的细致理解，为通用人工智能的未来研究与发展奠定基础。