In this episode, Priten speaks with Lorin Koch, an educator who has taught across high school, online, and college settings after starting his career in journalism. Koch brings perspective from multiple vantage points—as a classroom teacher navigating AI integration, an online instructor confronting assessment challenges, and a parent of soon-to-be teenagers. Together they explore what happens when students understand the difference between learning and shortcutting but choose the shortcut anyway, and whether responsibility can be taught when the incentive to take a quick way out has never been lower.

Key Takeaways:

• Understanding responsibility is not the same as practicing it. Students conceptually grasp that using AI to do their work for them is wrong, but when faced with pressure to get things done, they often choose the shortcut anyway—suggesting that knowing what you should do doesn't guarantee you'll do it.
• Self-paced, online environments create new accountability problems that have nothing to do with AI. The absence of in-person interaction makes it harder to detect cheating and easier to rationalize it, which means AI hasn't created the problem of student disengagement—it's simply made it more visible and more scalable.
• Your teaching intuition about whether something is AI-generated will become less reliable. As students grow up reading AI-generated text, their own writing will be shaped by those patterns, making it harder for teachers to distinguish between authentic voice and AI assistance based on stylistic markers alone.
• Presenting work through dialogue forces different stakes than submitting text alone. Requiring students to explain their thinking through presentations or discussion boards creates accountability that's harder to fake, even if the source material was AI-generated.
• The gap between high-achieving and struggling students will likely widen because of how students think about time. Students with short-term vision—those thinking about the next 24 hours rather than long-term consequences—are the most vulnerable to AI shortcuts, and they're also the ones who need human attention most.

Lorin Koch is an educator with 21 years experience teaching high school and 3 years as a college instructor of education. He holds an Ed.D. degree from the University of South Carolina. Lorin currently teaches online and in person from Washington state, where he works at Walla Walla University. He also writes and presents on Artificial Intelligence in education, focusing on integrating generative AI into the classroom.

In this episode, Priten speaks with Mary Shawn Newins, a computer science teacher in Greensboro, North Carolina, who arrived in the classroom at sixty with decades of corporate and sales experience but no coding background. Her unusual arc gives her permission to build AI literacy alongside her students rather than ahead of them. What emerges is a classroom culture where curiosity itself—not mastery or fear—becomes the pedagogical goal. She uses practical structures like a "quack" incentive and peer questioning to shift how students see AI: not as a shortcut to avoid, but as a tool that works best when you know what you actually want to learn.

Key Takeaways:

• Curiosity as a pedagogical aim changes everything about how students use AI. When learning for its own sake is the standard—not grades or compliance—AI becomes a catalyst for deeper exploration rather than a means of dodging work. A student asking AI about birds of prey out of genuine interest learns far more than one copying homework.
• Making AI use visible and gamified shifts students from hiding it to owning it. Mary's "quack quack" jar and peer accountability turn using AI into something worth discussing openly. Social transparency works where rules do not.
• Three non-negotiable standards replace prohibition: name the tool, share the prompt, explain the output in your own words. This mirrors citation practices students already know. It's not about policing—it's about maintaining the chain between question, resource, and understanding.
• Strict phones, generous computers reflects a deeper principle about attention and agency. Banning personal devices while enabling desktop computers creates a bounded space for learning. The boundary isn't about rejecting technology; it's about who controls the environment.
• Late-career teachers bring a rare asset: they remember how knowledge worked before AI. Mary's corporate background means she can model learning alongside students without needing to be the expert first. That permission ripples through the classroom.

Mary Shawn M. Newins is a Marketing and Computer Science educator at Southern Guilford High School in Greensboro, North Carolina. She has been a full-time faculty member since Spring 2023 and proudly serves as the school’s AI Champion, supporting innovative and responsible technology integration in the classroom. Mary holds a Bachelor of Science in Education from Bowling Green State University and is an Ambassador for the CodeMonkey High School curriculum, advocating for accessible and engaging computer science education for all students. Before transitioning into education, Mary spent 30 years in the business sector, working across business-to-business sales, retail, direct sales, and operations management. Outside the classroom, Mary is a wardrobe stylist at Chico’s Friendly Center, a denim upcycler, and a creative at heart who enjoys painting.

In this episode, Priten speaks with Alyssa Muhvic, a high school history teacher in Indiana navigating AI's reshaping of her classroom. With experience on her district's AI task force and deep expertise in both AI literacy and equity concerns, Alyssa demonstrates how educators can lead rather than resist technological change. She challenges the assumption that AI's presence signals either inevitable dependence or straightforward disruption, arguing instead that the work is fundamentally pedagogical: helping students develop the judgment to use these tools responsibly while still engaging with core historical thinking skills.

Key Takeaways:

• Treating AI as a search engine reframes citation, sourcing, and critical thinking as one unified practice. Students must learn to evaluate AI outputs with the same skepticism they'd apply to any source—examining bias, verifying claims, and contextualizing information. This makes digital literacy inseparable from historical literacy.
• The equity issue isn't access; it's reliability and responsibility at different price tiers. Paid AI plans produce output 20% more accurate than free versions. When affluent students get more reliable tools, the learning gap widens. Teaching responsible use becomes a justice issue.
• Academic dishonesty with AI reflects overwhelm, not moral failure. High-achieving students risk-taking for perfection; struggling students disengaging entirely. Neither group benefits from prohibition. Both need to understand why checking your work still matters.
• Transparency about your own AI use gives students permission to use it thoughtfully. When teachers hide their tool-use, students either view AI as forbidden or adopt it covertly. Showing your process—and its limits—normalizes critical engagement over sneaking.
• Districts need protected time, not more mandates, to equip teachers as active learners. Asking educators to master AI literacy while managing diploma rewrites, state standards shifts, and dual-credit pipelines is unsustainable. The bottleneck is time, not will.

Alyssa Muhvic is a Social Studies Teacher at Noblesville High School in Indiana, where she has been shaping young minds since 2021. She teaches United States History, Pre-AP World History, and Indiana Studies, and was the driving force behind launching the school's Ethnic Studies course — designing and implementing the curriculum from the ground up. Alyssa earned her degree in General History and Secondary Social Studies Education, with a minor in African American Studies, from Ball State University in 2021.