Hui Zhao,Zhaolian Ye

In the context of the simultaneous advancement of the "Dual Carbon" strategy and the digitalization of education, informationization and smart teaching have become key drivers for enhancing the quality and efficiency of environmental courses in higher education. As a core course in environmental science, "Environmental Impact Assessment" (EIA) is characterized by strong interdisciplinary knowledge, complex practical scenarios, and rapid policy updates. The traditional "lecture + case study" model is increasingly inadequate in meeting the personalized development of students and industry demands. Based on a systematic review of domestic and international research and practices in smart teaching, this paper identifies four key challenges faced by universities in China regarding this course in terms of resource development, classroom structure, faculty teams, and evaluation methods: fragmentation of resources, superficial interaction, homogenization of faculty, and delayed evaluation. In response, this paper proposes four optimization strategies: "platform intelligence, cross-disciplinary resource integration, composite faculty, and dynamic evaluation", and offers actionable paths and tools. The goal is to provide replicable and scalable models for the smart upgrading of environmental courses.

Smart Teaching; Educational Informationization; Personalized Learning; Virtual Simulation; Teaching Reform

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