Key Takeaways
Understanding AI's Role
- AI as learning companion and tool
- Balance of benefits and limitations
- Importance of guided implementation
Supporting Student Learning
- Multiple examples and explanations
- Addressing misconceptions
- Low-stakes practice opportunities
Course Design Strategies
- Authentic assessment approaches
- Constructive alignment principles
- Integration with learning outcomes
Working with AI
- Iterative refinement process
- Building on initial responses
- Continuous dialogue approach
- Progressive improvement
Implementation Support
- Clear guidelines and policies
- Student guidance frameworks
- Continuous improvement process
Research Foundation
This workshop draws from current research on AI in education:
Teaching Strategies & AI Integration
- Mollick & Mollick (2023) - Five evidence-based strategies for implementing AI in teaching, including multiple examples, varied explanations, and addressing misconceptions.
- Stöhr et al. (2024) - Study of student AI usage and attitudes across disciplines, highlighting adoption patterns and pedagogical implications.
Academic Integrity & Assessment
- Latest Insights Report (2024) - Current data on student and faculty perspectives, showing 45% student adoption vs 15% faculty adoption of AI tools.
- Dai et al. (2023) - Framework for reconceptualizing AI as student-driven innovation in higher education.
Next Steps
As you implement these ideas in your teaching:
Start Small
Choose one concept or assignment to redesign using these principles
Gather Feedback
Monitor student engagement and learning outcomes
Build Community
Share experiences and learn from colleagues implementing AI-enhanced teaching
Additional Resources
Teaching & Learning Centers
- Contact your institution's teaching center for specific support and workshops
- Join AI in Education communities of practice at your institution
Online Resources
- Access examples of AI-enhanced assignments in the shared repository
- Explore faculty development options for AI literacy