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Starts 25 June 2025 06:38

Ends 25 June 2025

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Generative AI for Improving Feedback

Unlock the potential of generative AI to transform your feedback process. This comprehensive course, offered by Pluralsight, dives into the integration of artificial intelligence tools to enhance feedback mechanisms, ensuring they remain genuine and effective. You'll explore practical approaches to conducting performance reviews, delve into p.
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Overview

Make your feedback process better and more efficient while keeping the human touch. Designed for busy leaders and professionals, this practical course shows you how to use AI tools effectively in your daily feedback tasks.

In this course, Generative AI for Improving Feedback, you'll learn to use AI tools to create better feedback drafts while keeping your personal voice, understanding which situations work best with AI, and seeing what mistakes to avoid. First, you’ll build a practical approach to all types of feedback, from performance reviews to team communications.

Next, you’ll discover how to adjust AI content to make it personal and meaningful. Finally, you’ll learn how to track if your feedback is working, helping you improve both speed and impact.

When you’re finished with this course, you’ll have the skills and knowledge of AI-generated feedback needed to use AI in your feedback process, scale your feedback while keeping it personal, and measure your success.

Syllabus

  • 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

Doru Catana


Subjects

Computer Science