arXiv：cs.AI· Mikael Gorsky, Ilya Levin·· 16 小时前
AI 如何重塑教育：情感、创造与协作学习的七大领域
Cognifying Education: Mapping AI's transformative role in emotional, creative, and collaborative learning
AI 导读
一篇 arXiv 论文整合 Eric Schmidt 等所著《Genesis》《CoIntelligence》《The Inevitable》等书籍的观点与 Anthropic 公开发布内容，考察 AI 在情感支持、创造力、情境理解、学生参与、问题解决、伦理道德和协作七个教育领域的能力与最佳实践。
正文
Abstract:Artificial intelligence (AI) is rapidly reshaping educational practice, challenging long held assumptions about teaching and learning. This article integrates conceptual perspectives from recent books (Genesis by Eric Schmidt, Henry Kissinger and Craig Mundie, CoIntelligence by Ethan Mollick, and The Inevitable by Kevin Kelly) with empirical insights from popular AI podcasts and Anthropic public releases. We examine seven key domains: emotional support, creativity, contextual understanding, student engagement, problem solving, ethics and morality, and collaboration. For each domain, we explore AI capabilities, opportunities for transformative change, and emerging best practices, drawing equally from theoretical analysis and real world observations. Overall, we find that AI, when used thoughtfully, can complement and enhance human educators in fostering richer learning experiences across cognitive, social, and emotional dimensions. We emphasize an optimistic yet responsible outlook: educators and students should actively shape AI integration to amplify human potential in creativity, ethical reasoning, collaboration, and beyond, while maintaining a focus on human centric values.
| Comments: | Presented at the 13th Higher Education Institutions Conference (HEIC) in Dubrovnik (September 2025): AI and Digital Transformation in Higher Education |
| Subjects: | Computers and Society (cs.CY); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2509.25266 [cs.CY] |
| (or arXiv:2509.25266v2 [cs.CY] for this version) | |
| https://doi.org/10.48550/arXiv.2509.25266 arXiv-issued DOI via DataCite |
Submission history
From: Mikael Gorsky [view email]
[v1]
Sun, 28 Sep 2025 07:32:10 UTC (504 KB)
[v2]
Sat, 10 Oct 2026 20:13:28 UTC (378 KB)
来源：arXiv：cs.AI · arxiv.org