The AI Problem Teachers Can’t Always See

In this episode we explore what happens when students appear to be participating, but may actually be outsourcing their thinking to AI.We look at a recent UC Berkeley story about unusually high failure rates in introductory computer science courses, alongside reporting from The New York Times about students using tools like Gemini and ChatGPT during class discussion. Topics covered:How AI can create a gap between visible participation and actual thinkingWhat the UC Berkeley computer science failure-rate story may reveal about AI-assisted learningThe difference between completing work with AI and developing transferable skillWhy “cheating” may be too narrow a frame for what schools are seeingWhat classroom teachers can look for when students appear engagedThe risk of discovering learning gaps only when students sit for an assessmentSources:https://www.dailycal.org/news/campus/academics/failing-grades-soar-as-professors-see-greater-ai-usage-dwindling-math-skills-in-uc-berkeley/article_16fad0bf-02cb-4b8c-8d88-888ffd9f8608.htmlhttps://www.nytimes.com/2026/06/17/podcasts/the-daily/battle-over-ai-in-school.html