用生成式AI打通科学教育教、学、评的闭环
Science Literacy: Generative AI as Enabler of Coherence in the Teaching, Learning, and Assessment of Scientific Knowledge and Reasoning
- 构建AI驱动的科学教育架构，实现教学评一体化
- 提升学生科学思维与知识应用能力，适应AI时代需求
- 适合教育科技研发者与课程设计者参考
本文探讨生成式AI在K-16+教育阶段提升科学素养的潜力，分析其带来的机遇与挑战。首先界定人工智能时代科学素养的新内涵，强调未来公民需具备在职业与生活中应用AI的科学理解力。接着指出当前科学教育在教、学、评环节缺乏连贯性的根本问题。提出需构建一种AI赋能的系统性架构，以实现科学知识与推理能力在教学、学习与评估间的有机统一。文中结合具体AI工具与能力，说明该架构的设计与实施路径。最后总结已取得的认知成果，并指出仍需开展的研究与开发工作，以及该模式向其他学科领域迁移的可行性。
原文摘要 · Abstract (English)
This chapter examines the potential of generative AI in enhancing science literacy across the K-16+ grade span, including its benefits as well as the conceptual and practical challenges that doing so presents. It begins with a discussion of what defines science literacy in the era of AI, including how AI has changed science and the demand for future citizens to be scientifically literate when AI is applied in their careers and lives. The chapter further discusses why science literacy presents such a challenge in K-16+ educational settings. It then develops an argument for the type of architecture needed for AI to assist in solving the problem by bringing coherence to the teaching, learning, and assessment of science knowledge and reasoning. Components of this architecture are illustrated with respect to the AI tools and capabilities needed for design and implementation. The chapter concludes with a consideration of what has been learned regarding both science literacy and AI, as well as what remains to be learned, including the research and development (R&D) needed, and the generalizability of this science literacy case to other disciplinary learning and knowledge domains.
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