This exploratory study titled Student and AI responses to physics problems investigates the comparative effectiveness of human and AI-generated solutions in physics education. It emphasizes sensemaking and mechanistic reasoning and concludes that while AI’s well-structured responses depict formal aspects of physics, student responses reflect practical applications. Key results are:

• Comparative insights into cognitive processes
• AI’s potential in STEM education
• Human-student advantages in iterative refinement

Opinion: The findings are important for teachers to understand how AI can complement physics instruction. The distinctions between AI and student problem-solving approaches can inform the design of instructional materials and the integration of AI in STEM education.