Overview
Discover how to enhance your feedback process with AI tools while maintaining authenticity, learning practical approaches for performance reviews, personalization techniques, and impact measurement.
Syllabus
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- Introduction to Generative AI in Feedback
-- Understanding Generative AI
-- Key Benefits for Feedback Processes
-- Course Objectives and Overview
- Building a Practical Feedback Approach
-- Types of Feedback in Professional Settings
-- Identifying Opportunities for AI Assistance
-- Integrating AI with Human Insight
- Crafting Feedback with AI Tools
-- AI Tools Overview and Selection Criteria
-- Creating Drafts: Balancing AI Input and Human Voice
-- Case Studies: Successful AI-Enhanced Feedback
- Personalizing AI-Generated Content
-- Techniques for Personalization and Contextualization
-- Ensuring Authenticity in AI-Generated Feedback
-- Avoiding Common Pitfalls and Errors
- Best Practices for Feedback Implementation
-- Timing and Frequency: When to Use AI
-- Stakeholder Engagement and Communication
-- Aligning Feedback with Organizational Goals
- Measuring Impact and Effectiveness
-- Metrics for Evaluating Feedback Success
-- Tools and Methods for Tracking Performance
-- Iterative Improvement: Refining the AI Feedback Loop
- Ethical Considerations and Limitations
-- Addressing Privacy and Consent in AI Feedback
-- Understanding AI Limitations and Biases
-- Maintaining a Human-Centric Approach
- Conclusion and Next Steps
-- Recap of Key Learnings
-- Resources for Further Exploration
-- Personalized Action Plan for Implementing AI-Enhanced Feedback
- Course Wrap-Up
-- Participant Q&A Session
-- Course Feedback and Reflection
-- Certification and Further Learning Opportunities
Taught by
Tags
On-Demand