AI赋能“以学生为中心”教学模式探索与实践——以高等教育数字化转型为视角

Exploration and Practice of AI-Empowered “Student-Centered” Teaching Model—From the Perspective of Digital Transformation in Higher Education

摘要: 随着生成式AI、多模态学习分析与知识图谱技术的发展，高等教育数字化转型正从基础设施迈向核心教学场景重构。传统以教师为中心的标准化模式，难以满足智能时代对创新型、批判性及个性化人才的需求。本文立足“以学生为中心”理念，探讨人工智能如何深度赋能高等教育教学，打破了课前、课中、课后的线性孤立状态，构建了数据流与智能算法驱动的全要素智慧教学模式：课前智能学情画像与自适应认知规划；课中人机协同深度探究与即时反馈；课后多维度形成性评价与精准辅导。另外，本文还剖析了算法黑箱、数据隐私、教师数字素养及“认知外包”等挑战，提出了完善治理框架、重构教师发展体系等对策。未来，人机共善、AI技术与人文深度融合的智慧教育新生态，将成为高等教育高质量发展的核心方向。

Abstract: With the development of generative AI, multimodal learning analytics, and knowledge graph technologies, the digital transformation of higher education is shifting from infrastructure construction to the restructuring of core teaching scenarios. The traditional teacher-centered standardized model can hardly meet the demand of the intelligent era for innovative, critical-thinking, and personalized talents. Grounded in the “student-centered” philosophy, this paper explores how artificial intelligence can deeply empower teaching and learning in higher education. Breaking the linear and isolated state of pre-class, in-class, and after-class stages, the study constructs a full-element smart teaching model driven by data streams and intelligent algorithms: pre-class intelligent learning profiling and adaptive cognitive planning; in-class human-machine collaborative deep inquiry and real-time feedback; after-class multi-dimensional formative evaluation and precise tutoring. The paper also analyzes challenges including algorithmic black boxes, data privacy, teachers’ digital literacy, and “cognitive outsourcing,” and proposes countermeasures such as improving the governance framework and reconstructing the teacher development system. Looking ahead, a new smart education ecosystem featuring human-machine co-goodness and deep integration of AI technology and humanities will become the core direction for high-quality development of higher education.