WASHINGTON, Jan. 6, 2026 — As generative AI technologies like ChatGPT become increasingly embedded in everyday life, their role in education, particularly in physics, is under scrutiny. These AI tools, known for their rapid problem-solving abilities and conversational prowess, are now making their way into classrooms, often serving as both educational aids and shortcuts.
Amidst this technological integration, educators are voicing concerns over the potential impact on student learning. A recent article in The Physics Teacher, a journal co-published by AIP Publishing and the American Association of Physics Teachers, delves into these issues. Gerd Kortemeyer, a physics professor-turned-AI-researcher at ETH Zurich, examines how generative AI can both aid and hinder the learning of physical sciences.
The Boiling Frog Analogy
In his paper, Kortemeyer likens the growing capabilities of generative AI in physics education to the boiling frog fable. This metaphor suggests that a frog placed in gradually heated water will fail to perceive the danger until it’s too late. Kortemeyer warns that educators might similarly overlook the subtle yet significant changes AI is bringing to the educational landscape until it becomes too challenging to address.
“Generative AI can absolutely be a helper: for example, as a tool to quickly pull up definitions, explaining terms, drafting analysis programs, giving students immediate feedback on their explanations, or for translating physics concepts into different languages,” Kortemeyer said. “But these are supports for human sense-making and collaboration, not the main act.”
AI in the Classroom: A Double-Edged Sword
Surveys indicate a growing reliance on AI tools among students. Kortemeyer outlines scenarios where AI usage is beneficial and situations where it might undermine educational goals, suggesting that educators must sometimes “jump out of the pot” to avoid detrimental effects.
One significant concern is the use of AI in unsupervised online assignments, which can no longer serve as reliable indicators of student mastery. AI’s ability to solve problems from a mere image and the questionable accuracy of AI-detection tools complicate assessment methods. However, completely removing AI from educational settings could alienate students accustomed to these technologies.
“Change is hard. We have spent years of our lives perfecting our lecture notes and PowerPoint slides, and we have built up beautiful problem banks with neat little tricky scenarios,” said Kortemeyer. “I think as physics educators, we need to completely recalibrate — what do we really want to teach?”
Adapting to the AI Era
Kortemeyer advocates for integrating AI into the learning process in a way that encourages students to critically engage with these tools. By teaching students to cite and critique AI usage, educators can foster a deeper understanding of the material. This approach requires significant effort but promises to keep the metaphorical water from becoming too hot for students.
The responsibility for these changes, Kortemeyer notes, partly lies with physicists themselves, who have contributed to the development of AI’s foundational principles. Now, educators must navigate the consequences, which Kortemeyer argues is not necessarily negative.
“We have brought generative AI on ourselves — physicists played a large role in developing the underlying principles. Now we need to live with the consequences, but that is not necessarily a bad thing,” said Kortemeyer. “If we take it as an opportunity to focus on reasoning, collaboration, and genuine understanding rather than on speed and routine problem solving, we may finally be doing the right thing by our students.”
Looking Forward
As generative AI continues to evolve, its role in education will likely expand. The challenge for educators will be to adapt teaching methods to harness AI’s potential while maintaining the integrity of the learning process. This balance will be crucial in ensuring that students develop not only technical skills but also critical thinking and collaborative abilities.
The conversation around AI in education is just beginning, and as Kortemeyer’s work suggests, the coming years will be pivotal in shaping how these powerful tools are integrated into the classroom. The key will be to ensure that the educational environment remains conducive to learning, without allowing the technological “water” to become too overwhelming.
