Generative AI is transforming teaching and learning by creating new opportunities for course design, assessment, feedback, and student engagement. This Johns Hopkins resource provides faculty with practical guidance for using AI responsibly while addressing important considerations related to ethics, privacy, bias, and academic integrity.
Generative AI Tool Guidance brings together recommendations from teaching and learning experts across Johns Hopkins to help instructors explore AI thoughtfully and effectively in higher education. The resource continues to evolve as AI technologies and institutional best practices develop.
Faculty can explore guidance on topics including:
- Understanding how generative AI tools and large language models work
- Designing engaging course activities using generative AI
- Redesigning assessments in response to AI-enabled learning
- Using AI to provide meaningful assignment feedback
- FERPA, HIPAA, data ownership, and ethical considerations when using AI tools
- Example syllabus statements and guidance for communicating AI expectations to students
- Understanding the limitations of AI detection tools and alternative approaches
- Strategies for reducing bias and promoting responsible AI use in teaching
- Case studies, videos, and additional resources from across Johns Hopkins University
The resource also emphasizes key principles for responsible AI use, including using AI to augment not replace, human expertise, validating AI-generated content, recognizing potential bias, and maintaining critical human oversight throughout the teaching and learning process.
This resource is especially valuable for faculty, instructors, instructional designers, teaching assistants, and academic leaders seeking practical, institution-specific guidance on integrating generative AI into higher education.
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