用AI助手帮学生理解日常行为对地球边界的影响,推动校园可持续行动。
Eco-Bee: A Personalised Multi-Modal Agent for Advancing Student Climate Awareness and Sustainable Behaviour in Campus Ecosystems

- 结合大模型与行星边界框架,将环保知识转化为可对话的个性化建议。
- 试点中96%学生支持推广,且普遍提升对行为与地球极限关联的认知。
- 适合关注气候变化教育、行为干预与校园可持续转型的研究者与实践者。
大学是城市生态系统的缩影,集中体现食物、交通、能源和产品使用的消费模式。这些环境不仅显著加剧可持续性压力,也提供了大规模推进可持续教育与行为改变的独特机遇。当前高校的数字可持续项目仍局限于碳排放计算,多以静态反馈为主,难以持续推动行为改变。为此,我们提出Eco-Bee,融合大语言模型、行星边界框架(化为Eco-Score)以及对话式代理,将个体选择与环境承载力关联。针对处于习惯养成关键期的学生,Eco-Bee提供可操作建议、同伴对比和游戏化挑战,以维持参与度并推动向边界内生活迈进。在多个校园网络的试点中(n=52),96%的学生支持全面推广,并表示更清楚日常行为如何共同影响地球极限。通过整合行星科学、行为强化与AI个性化,Eco-Bee为气候意识型大学及未来AI驱动的可持续基础设施建立了可扩展基础。
原文摘要 · Abstract (English)
Universities are microcosms of urban ecosystems, with concentrated consumption patterns in food, transport, energy, and product usage. These environments not only contribute substantially to sustainability pressures but also provide a unique opportunity to advance sustainability education and behavioural change at scale. As in most sectors, digital sustainability initiatives within universities remain narrowly focused on carbon calculations, typically providing static feedback that limits opportunities for sustained behavioural change. To address this gap, we propose Eco-Bee, integrating large language models, a translation of the Planetary Boundaries framework (as Eco-Score), and a conversational agent that connects individual choices to environmental limits. Tailored for students at the cusp of lifelong habits, Eco-Bee delivers actionable insights, peer benchmarking, and gamified challenges to sustain engagement and drive measurable progress toward boundary-aligned living. In a pilot tested across multiple campus networks (n=52), 96% of the student participants supported a campus-wide rollout and reported a clearer understanding of how daily behaviours collectively impact the planet's limits. By embedding planetary science, behavioural reinforcement, and AI-driven personalisation into a single platform, Eco-Bee establishes a scalable foundation for climate-conscious universities and future AI-mediated sustainability infrastructures.
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