[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2152":3},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"view_count":31,"doi":32,"paper":33,"created_at":51},2152,"STEM Education and AI Applications in Chemistry Teaching: From Pedagogical Ecosystems to the Self-Efficacy of Secondary School Teachers","https:\u002F\u002Fdoi.org\u002F10.12691\u002Fwjce-14-3-3","This study explores the integration of STEM education and artificial intelligence (AI) in chemistry teaching to foster a sustainable pedagogical ecosystem. Current secondary school practices reveal three critical operational gaps: a deficiency in interdisciplinary integration methodologies at the lower secondary level, intense high-stakes national examination pressures driving technological risk aversion at the upper secondary level, and pervasive administrative formalism in teacher professional development. To address these challenges, the research combines conceptual framework construction with an exemplary case study of a chemistry STEM project entitled \"Chemical Fertilizers and Smart Agriculture\". This project is structured across three progressive technical layers: direct soil pH and nutrient analysis using IoT sensors in field environments (Layer 1); the integration of large language models (such as ChatGPT) as personalized learning co-pilots alongside virtual laboratories to optimize learning trajectories (Layer 2); and the process-oriented evaluation of 21st-century competencies via a Digital Portfolio platform (Layer 3). Based on these empirical findings, the study proposes a bipolar set of breakthrough solutions: activating teachers' internal \"self-efficacy\" through digital self-directed learning, and reforming the \"transformative mission\" of teacher education institutions through the development of smart campus laboratories and professional learning networks. Finally, the study recommends institutionalizing Digital Portfolios parallel to traditional academic transcripts to alleviate high-stakes examination pressures and establish a genuine symbiotic connection between teacher education institutions and secondary schools in the AI era.","本研究探讨了STEM教育与人工智能（AI）在化学教学中的融合，以构建可持续的教学生态系统。当前中学实践暴露出三个关键的操作性缺口：初中阶段跨学科整合方法的缺失，高中阶段高利害全国性考试压力导致的技术风险规避，以及教师专业发展中普遍存在的行政形式主义。为应对这些挑战，本研究将概念框架构建与题为“化肥与智慧农业”的化学STEM项目案例研究相结合。该项目按三个递进的技术层次进行架构：在田间环境中利用物联网传感器进行直接的土壤pH和养分分析（第一层）；将大语言模型（如ChatGPT）作为个性化学习协 pilot，与虚拟实验室相结合以优化学习路径（第二层）；以及通过数字档案平台对21世纪能力进行过程性评价（第三层）。基于这些实证发现，本研究提出了一组两极突破性解决方案：通过数字化自主学习激活教师内在的“自我效能感”，以及通过建设智慧校园实验室和专业学习网络来变革教师教育机构的“转型使命”。最后，本研究建议将数字档案与传统学业成绩单并行制度化，以缓解高利害考试压力，并在AI时代建立教师教育机构与中学之间真正的共生联系。",null,"World journal of chemical education","2026-09-09T00:00:00Z","论文",10,false,62,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":17,"relevant":21,"comment":22},8,18,16,12,1,"以“化肥与智慧农业”项目为案例，探讨AI与物联网在化学教学中的融合路径，对农业信息化人才培养与教师数字素养建设有参考价值，但属教育研究范畴，产业影响有限。",[24],{"name":10,"url":6},[26,27,28,29,30],"智慧农业","农业人工智能","数字素养","物联网","STEM教育",0,"10.12691\u002Fwjce-14-3-3",{"doi":32,"openalex_id":34,"authors":35,"venue":10,"cited_by_count":31,"oa_url":42,"card":43,"direction":49,"ingested_from":50},"W7212041762",[36,39],{"name":37,"orcid":38},"Cao Thi Van Giang","https:\u002F\u002Forcid.org\u002F0009-0003-3483-9496",{"name":40,"orcid":41},"Cao Cự Giác","https:\u002F\u002Forcid.org\u002F0000-0003-4804-9009","https:\u002F\u002Fpubs.sciepub.com\u002Fwjce\u002F14\u002F3\u002F3\u002Fwjce-14-3-3.pdf",{"tldr":44,"method":45,"finding":46,"direction":47,"opportunity":48},"构建化学STEM教学框架，以“化肥与智慧农业”案例融合AI与物联网，提升教师自我效能。","概念框架+案例研究，用IoT传感器、ChatGPT、虚拟实验室和数字档案袋。","提出激活教师自我效能与改革师范教育的双极方案，建议数字档案袋制度化。","农业人工智能与决策模型","可实证检验AI+IoT农业项目对教师自我效能与学生21世纪能力的长效影响。","智慧农业 \u002F 农业物联网","openalex","2026-09-11T23:30:13.553449Z"]