高等教育中的生成式人工智能_现行做法与未来道路（英）-2025_40页_2mb

Generative AI in Higher Education: Analysis and Key Takeaways

1. Introduction & Motivation

• Generative AI represents a transformative shift in higher education, challenging traditional teaching, learning, and research paradigms.
• Universities face pressure to respond to AI while preserving educational integrity. Current approaches are often reactive and piecemeal.

2. Key Action Areas (CRAFT Framework)

The CRAFT framework provides a comprehensive approach to integrating generative AI responsibly:

• Rules: Beyond restriction, institutions must establish governance frameworks, assessment redesign, and ethical guidelines for AI use.
• Access: Ensure equitable access beyond tools to cover infrastructure, support, and opportunities, especially for marginalized communities.
• Familiarity: Systematically educate students, faculty, and staff on AI capabilities, limitations, and ethical implications.
• Trust: Build trust through transparency, collaboration, and demonstrated value; address concerns across user groups.
• Culture: Foster an environment where AI is viewed as a tool for enhancement, not replacement; balance technological innovation with human-centered values.

3. Immediate Priorities

• Form Collaborative Clusters: Universities should partner regionally or by focus area (e.g., assessment redesign, equity access) to share resources and expertise.
• Elevate Students as Partners: Engage students in co-designing AI tools, assessing policies, and sharing peer-to-peer knowledge.

4. Conclusion

• The goal is not to control AI but to shape its integration so it enhances, rather than diminishes, higher education’s core values.
• Rapid, coordinated action is vital to navigate the challenges and opportunities ahead.