The Tutoring Effectiveness Index (TEI) uses four signals from LLM conversations to select math tutoring responses, raising student improvement rates from 59.0% to 81.9% at N=8 on a frozen DeepSeek-R1-8B model without training or judges.
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Training-free prompt optimization methods, including five new education-focused ones, surpass the strongest RL-trained baseline across five conditions on two OOD suites while showing distinct teaching behavior patterns.
Special-R1 combines two-dimensional adaptive prompts and a disability-conditioned Thinking Reward in RL training, lifting persona-aware Fit by 1.65 and SPED Helpfulness by 0.048 on a 690-dialogue test set while staying competitive on an out-of-domain benchmark.
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LLMs Are Already Good Tutors: Training-Free Prompt Optimization for Pedagogical Math Tutoring
Training-free prompt optimization methods, including five new education-focused ones, surpass the strongest RL-trained baseline across five conditions on two OOD suites while showing distinct teaching behavior patterns.