Скачать или смотреть Teaching with AI in Higher Ed with Dr. C. Edward Wilson

In this episode, host Mike Palmer welcomes back Dr. Eddie Watson to discuss the rapidly evolving landscape of AI in higher education. Following the release of the second edition of his book, ⁠Teaching with AI: A Practical Guide to a New Era of Human Learning⁠ (https://www.press.jhu.edu/books/title...) , Eddie shares insights from working with nearly 200 campus teams on transitioning from AI-resistant assignments to AI-integrated pedagogy. ⁠Here's the link to Eddie's first appearance⁠ (   • Teaching with AI with Author Eddie Watson  ) .



Key Takeaways:



Beyond Academic Integrity: While cheating remains a concern, the conversation is shifting toward AI literacy as an essential learning outcome to prepare students for an AI-integrated workforce.



The "Calculus" of Cheating: In high-stakes environments, students often feel a competitive disadvantage if they don't use AI.



Pedagogical Transparency: If faculty ban AI for specific assignments, they must explain the "why" (e.g., building foundational skills) to encourage student compliance



Backward Design: Eddie advocates for starting with the desired learning outcome and engineering assignments and instruction from there.



Learning to Write vs. Writing to Learn: AI’s role should differ based on whether the goal is mastering writing mechanics or using writing to process course content.



Durable Skills: While technical skills like prompt engineering may change quickly, mindsets like metacognition and critical thinking remain essential.



"Ground Truth" Bots: Using tools like NotebookLM or Small Language Models (SLMs) allows students to interrogate specific, vetted data sets like OER textbooks.



Efficiency vs Engagement: The episode concludes with a look at the "Efficiency vs. Engagement" binary. While institutions may use AI to automate grading and increase class sizes, the real opportunity lies in reinvesting saved time into "signature pedagogies"—mentoring and fostering a sense of student belonging, which are the greatest predictors of student success.



Quotes:



"The one who does the work is the one who does the learning. How do we make sure our students are doing the work, because that's where the learning occurs?" — Eddie Watson



Time Stamps:




•


00:00 - Introduction & Welcome Back




•


00:55 - The Innovation Cycle: Second Edition of "Teaching with AI"




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01:41 - Eddie Watson’s Background & Role at AAC&U




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03:32 - The Shift: From Academic Integrity to the World of Work




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05:10 - Complexity of Academic Integrity & Student Pressures




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07:42 - Evolving Assessment Strategies & Motivation to Cheat




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10:55 - Backward Design: Aligning AI with Learning Outcomes




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12:54 - Writing to Learn vs. Learning to Write




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14:43 - Agentic AI & Modernizing Assessments




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18:50 - Creating "AI-Resistant" vs. AI-Transparent Assignments




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24:43 - Developing a Meta AI Literacy Model




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28:00 - Durable Skills: Metacognition & Managing AI




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33:50 - Custom Chatbots, SLMs, and Ground Truths




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46:40 - The Future: Efficiency vs. Engagement




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49:00 - The Human Element: Mentorship & Student Belonging




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51:00 - Closing Remarks






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