Engineering classrooms are increasingly experimenting with generative AI (GenAI), but most uses remain confined to individual prompting and isolated assistance. This narrow framing risks reinforcing equity gaps and only rewarding the already privileged or motivated students. We argue instead for a shift toward collective intelligence (CI)-focused pedagogy, where GenAI acts as a catalyst for peer-to-peer learning. We implemented Generative CI (GCI) activities in two undergraduate engineering courses, engaging 140 students through thinking routines -- short, repeatable scaffolds developed by Harvard Project Zero to make thinking visible and support collaborative sense-making. Using routines such as Question Sorts and Peel the Fruit, combined with strategic AI consultation, we enabled students to externalize their reasoning, compare interpretations, and iteratively refine ideas. Our dual-pronged approach synthesizes literature from learning sciences, CI, embodied cognition, and philosophy of technology, while also empirically learning through student surveys and engagement observations. Results demonstrate that students value the combination of human collaboration with strategic AI support, recognizing risks of over-reliance while appreciating AI's role in expanding perspectives. Students identified that group work fosters deeper understanding and creative problem-solving than AI alone, with the timing of AI consultation significantly affecting learning outcomes. We offer practical implementation pathways for mainstreaming CI-focused pedagogy that cultivates deeper engagement, resilient problem-solving, and shared ownership of knowledge.

翻译：工程学课堂正日益尝试应用生成式人工智能（GenAI），但多数使用仍局限于个体提示和孤立辅助。这种狭隘的框架可能加剧教育公平差距，仅使已有优势或学习动机强的学生受益。我们主张转向以集体智能（CI）为核心的教学法，使GenAI成为同伴学习的催化剂。我们在两门本科工程课程中实施了生成式集体智能（GCI）活动，通过哈佛零点项目开发的思维常规——简短、可重复的支架式工具，使思维可视化并支持协作意义建构——吸引了140名学生参与。运用"问题分类"与"剥开果实"等思维常规，结合策略性AI咨询，我们帮助学生外化推理过程、比较不同解读并迭代完善观点。我们的双轨研究方法综合了学习科学、集体智能、具身认知与技术哲学等领域的文献，同时通过学生问卷与参与度观察进行实证研究。结果表明，学生重视人际协作与策略性AI支持的结合，既能认识到过度依赖AI的风险，又认可AI在拓展思维视野中的作用。学生指出小组合作比单独使用AI更能促进深度理解与创造性问题解决，且AI咨询的时机对学习成效具有显著影响。我们为以集体智能为核心的教学法主流化提供了实践路径，旨在培养深度参与、弹性问题解决能力及知识共享的集体所有权。