高等教育中的代理AI生态系统：对AI代理在新兴包容性、代理多代理AI框架中学习、教学和机构智能的视角
Agentic AI Ecosystems in Higher Education: A Perspective on AI Agents to Emerging Inclusive, Agentic Multi-Agent AI Framework for Learning, Teaching and Institutional Intelligence
AI总结：
本文探讨高等教育中代理多代理AI平台的整合，旨在解决教育机构复杂性中的碎片化问题，强调包容性和适应性决策的重要性。
摘要：
将人工智能代理整合到高等教育中正在改变教学、学习和行政流程。尽管现有AI代理有效支持个体任务，但其实施仍碎片化且效率低下，无法处理教育机构的复杂性。这突显了显著的研究缺口：缺乏能够跨多个教育功能协调规划、推理和适应性决策的集成生态级代理多代理AI平台。本文提出了高等教育中代理多代理AI平台的前瞻性视角，由相互连接的自主、目标驱动的代理组成，支持学习、教学和机构运营。它回答了关键问题：代理AI能否成为高等教育的下一代智能系统？它们能否协同支持教学、学习和行政支持的无缝协调操作？此类系统能有多大程度上促进包容和公平的学习环境，以支持具有特殊教育需求的多样化学习者？为了支撑这一视角，对现有文献的专题分析识别出四个主导主题：任务特定的碎片化AI工具、从单代理到多代理系统的过渡、有限的跨功能整合以及对包容性和可访问性的不足关注。发现揭示了当前AI实施与全面、以学习者为中心的教育生态系统需求之间的明显差距。本文综合了挑战并概述了可扩展、人本和包容的代理AI平台的未来研究方向。重要贡献是纳入了包容性学习视角，强调协调的代理多代理平台如何通过适应性、多模态干预支持多样化学习者。
英文摘要：
Integration of artificial intelligent (AI) agents in higher education is transforming teaching, learning and administrative processes. Although existing AI agents effectively support individual tasks, their implementation remains fragmented and inefficient for handling the complexity of educational institutions. This highlights a significant research gap: the lack of integrated eco-system-level agentic multi-agent AI platform capable of coordinated planning, reasoning, and adaptive decision-making across multiple educational functions. This paper presents a forward-looking perspective on agentic multi-agent AI platform in higher education, consisting interconnected autonomous, goal driven agents that support learning, teaching, and institutional operations. It addresses timely and critical questions: Can agentic AI represent the next generation of intelligent systems in tertiary education? Can they collectively support seamless coordinated operations across teaching, learning and administrative support? To what extent can such systems foster inclusive and equitable learning for diverse learners with special educational needs? To ground this perspective, a thematic analysis of existing literature identifies four dominant themes: task-specific fragmented AI tools, the transition from single-agent to multi-agent systems, limited cross-functional integration, and insufficient focus on inclusivity and accessibility. Findings reveal a clear gap between current AI implementations and the needs of holistic, learner-centered educational ecosystem. The paper synthesizes challenges and outlines future research directions for scalable human-aligned, and inclusive agentic AI platform. The significant contribution is the incorporation of inclusive learning perspectives, highlighting how coordinated agentic multi-agent platform can support diverse learners through adaptive, multimodal interventions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
