Curiosity-oriented linguistic interventions in LLM tutoring dialogues increased exploratory learner behaviors up to 2.4x across 270 conversations spanning multiple models and domains.
arXiv preprint arXiv:2302.04662 , year=
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PERSA combines RLHF with selective parameter-efficient updates to top transformer layers, raising style alignment scores from 35% to 96% on code feedback benchmarks while holding correctness near 100%.
Randomized classroom trial of 215 students shows natural language LLM feedback improves completion rates and convergence speed over test-case feedback or none, with test-case effects varying by validity.
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A Classroom Study of LLM-Generated Feedback Intervention in Introductory Programming
Randomized classroom trial of 215 students shows natural language LLM feedback improves completion rates and convergence speed over test-case feedback or none, with test-case effects varying by validity.