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Authors:
郭玉博
陈昕
宁敏静
余璇
郑小强
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Information:
西南石油大学,成都
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Keywords:
Generative AI; Project Low-Carbon Management; Dynamic case adaptation; Teaching reform
生成式AI; 项目低碳管理; 案例动态适配; 教学改革
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Abstract:
Against the background of the deep integration of the “dual carbon” goal and the educational digital transformation strategy, the “Project Low-Carbon Management” course, as a core carrier for cultivating compound low-carbon talents, faces prominent problems such as outdated practical cases, poor adaptability, and disconnection between teaching and industry needs. Generative AI, with its technical advantages of rapid content generation, intelligent scenario adaptation, and dynamic iterative optimization, provides an innovative path for the reform of practical teaching in the course. Based on the pain points of curriculum teaching, this paper constructs a generative AI-driven dynamic adaptation teaching system for practical cases, and carries out teaching design and practical exploration from four dimensions: case generation, hierarchical adaptation, teaching implementation, and multi-dimensional evaluation. It focuses on discussing the integration logic and operational path of AI technology and case teaching. Research shows that this teaching mode can effectively improve the pertinence of cases and the vitality of classroom teaching, help students build a systematic knowledge system of low-carbon project management, and cultivate digital application capabilities and green development literacy. It can provide reference for the digital transformation of similar low-carbon related courses.
在“双碳”目标与教育数字化战略深度融合的背景下,“项目低碳管理”课程作为培养复合型低碳人才的核心载体,面临实践案例时效性不足、适配性不强、教学与行业需求脱节等突出问题。生成式AI凭借快速内容生成、智能场景适配、动态迭代优化的技术特性,为课程实践教学改革提供了创新路径。本文立足课程教学痛点,构建了生成式AI驱动的实践案例动态适配教学体系,从案例生成、分层适配、教学实施、多元评价四个维度展开教学设计与实践探索,重点探讨AI技术与案例教学的融合逻辑及操作路径。研究表明,该教学模式能有效提升案例的针对性与课堂教学活力,助力学生构建系统的低碳项目管理知识体系,培育数字化应用能力与绿色发展素养,可为同类低碳相关课程的数字化转型提供参考。
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DOI:
https://doi.org/10.35534/es.0712256 (registering DOI)
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Cite:
郭玉博,陈昕,宁敏静,等.基于生成式AI的“项目低碳管理”课程实践案例动态适配设计与教改实践[J].教育研讨,2025,7(12):1367-1370.