构建可协同决策的智能体系统,推动高校教与学的融合创新
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
- 设计多智能体协作框架,实现教学、学习与管理联动
- 强调包容性支持,适配特殊教育需求的学习者
- 面向未来教育生态,提出可扩展的人工智能平台构想
人工智能智能体在高等教育中的融合正重塑教学、学习与行政流程。尽管现有智能体能有效支持单一任务,其应用仍呈碎片化,难以应对教育机构的复杂性。本文提出一种前瞻性的智能体多智能体AI平台视角,由相互连接的自主、目标驱动智能体组成,协同支持学习、教学与机构运营。通过主题分析现有文献,识别出四大趋势:任务导向的零散工具、单智能体向多智能体演进、跨功能整合不足,以及对包容性与可访问性关注有限。研究揭示当前实践与全人本、以学习者为中心的教育生态系统需求之间的显著差距。论文综合挑战并展望可扩展、以人为本、包容性的智能体平台未来方向,核心贡献在于融入包容性学习视角,表明协调式多智能体系统可通过自适应、多模态干预支持多样化学习者。
原文摘要 · Abstract (English)
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.
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