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Is AI Cheating Your Students Out of Learning? Flip Your Class! - Episode 39

Season #4

Are your students secretly using AI to complete their homework? In an age where ChatGPT can solve complex problems in seconds, how can educators ensure that genuine learning is still happening?

Join us for a critical discussion with veteran educator Jon Bergmann, who initially embraced AI as a revolutionary tool but quickly discovered its pitfalls. He shares a pivotal moment watching a top student shortcut her learning with AI and realized that the "hard stuff" can no longer be sent home.

In this episode, Jon argues that Flipped Learning is the essential strategy for the AI era. Discover how to shift the cognitively demanding work back into the classroom, freeing up class time for deep thinking, problem-solving, and authentic assessment. Learn why productive struggle is crucial for developing students' brains and how to use AI as a tool without sacrificing critical thinking. This is a must-listen for any educator navigating the disruptive new landscape of artificial intelligence.

Key Takeaways from This Episode:

  • The AI Dilemma: Why a tech-savvy teacher grew concerned about AI's impact on student learning and critical thinking.

  • The Problem with "Hard" Homework: How AI makes it nearly impossible to assign complex tasks for students to complete at home.

  • What is Flipped Learning? A clear explanation of the Flipped Learning model (flipping Bloom's Taxonomy) and why it's more relevant than ever.

  • In-Class is the New Homework: Practical strategies for bringing the "hard stuff"—like writing essays, solving physics problems, and language practice—back into the classroom.

  • The Power of Productive Struggle: Understand the neuroscience behind why students need to struggle to learn effectively and build their own "neural networks."

  • A Balanced Approach to AI: How to use AI tools like AI tutors in a controlled, effective way that enhances, rather than replaces, learning.

  • The Memory Paradox: A discussion of new research on why foundational knowledge is still essential in the age of AI.

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