【作 者】：
武法提， 夏志文， 高姝睿
【关 键 词 】：
智慧学习环境； 生成式人工智能； 要素改进； 生态重构； 理论模型
【栏 目】：
学习环境与资源
【中文摘要】：
智慧学习环境作为教育数字化转型的重要支撑，在建设过程中涌现出数据孤岛、模型局限、资源定型、工具繁杂、服务僵硬、场景割裂等问题。生成式人工智能作为人工智能技术发展的新形态，给智慧学习环境的升级与变革带了新的机遇。研究以生成式人工智能为动力引擎升级了三层六要素的智慧学习环境理论模型，认为智慧学习环境中的数据要素由低质化转向高效化、模型要素由判别式转向生成式、资源要素由表象化转向语义化、工具要素由分布式转向集成化、服务要素由预定义转向自适应、场景要素由边缘化转向中心化。在此基础上，研究进一步明晰了生成式人工智能可通过重构人才培养理念、知识与课程观、教学模式与学习方式、教育评价体系及教育治理模式变革智慧学习环境生态。研究深入剖析了智慧学习环境的内部要素改进与外部生态重构，为塑造智慧学习环境新形态提供理论研究支撑与实践探索方向。
【英文摘要】：
As a crucial pillar of educational digital transformation, smart learning environments have encountered issues such as data silos, model limitations, resource rigidity, tool complexity, inflexible services, and fragmented scenarios during their development. Generative artificial intelligence (GAI), as an emerging form in AI technology, presents new opportunities for the upgrading and transformation of smart learning environments. The study upgrades the three-layer and six-factor theoretical model of smart learning environment with generative AI as the power engine. It is argued that within this framework, the data element has shifted from low quality to high efficiency, the model element from the discriminative to the generative, the resource element from the superficial to the semantic, the tool element from the distributed to the integrated, the service element from the predefined to the adaptive, and the scenario element has moved from the marginalized to the centralized. On this basis, the study further clarifies that GAI can restructure the ecosystem of smart learning environments by transforming the ideas of talent cultivation, the concepts of knowledge and curricula, teaching modes and learning styles, educational evaluation systems, and educational governance models. The study analyzes the improvement of internal elements and the reconstruction of the external ecosystem of smart learning environments, providing theoretical research support and practical exploration direction for shaping new forms of smart learning environments.