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The "Curse of Knowledge" Means Smarter AI Models Don't Understand Where Human Learners Struggle

A recent study highlights a fundamental blind spot in large language models: while they can solve exam questions that stump humans, they cannot identify why those questions are difficult. This "curse of knowledge" bias means AI systems lack insight into human learning challenges. Researchers demonstrated that LLMs consistently misjudge question difficulty compared to student performance. The findings call for a shift toward models that understand learner cognition, not just produce correct answers.