L2C outperformed both the Rule-based Fading and Minimally-invasive Assistance baselines on lap time and failure count¶

Claim · All claims
Evidence · 1 study · causal r2 · q3 · i2 medium
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q3 i2 Between-group Welch tests with Holm correction showed L2C outperforming MIA and RBF on both lap time and failure count, with Hedges' g between 0.60 and 0.76. → Wei Wang 2026

Evidence¶

Wei Wang 2026¶

Wei Wang, Enlin Gu, Antonio Loquercio, Haimin Hu, Rahul Mangharam. (2026). AI Coaching for Accelerating Human Skill Development with Reinforcement Learning. arXiv preprint. https://arxiv.org/abs/2606.25337 doi:10.48550/arxiv.2606.25337

q3 · i2 · causal · r2

Welch two-sample t-tests with Holm correction across the three randomly assigned coach groups (N=33) in the drone-racing user study. All four contrasts favor L2C with Hedges' g = -0.63, -0.60, -0.76, and -0.67, described as "medium-to-large effect sizes between 0.60 and 0.76".

"On lap time, L2C outperformed MIA (∆ =−21.7%, Hedges’g=−0.63) and RBF (∆ =−16.6%, g=−0.60); on failure count, L2C outperformed MIA (∆ =−2.41failures per lap,g=−0.76) and RBF (∆ =−1.52failures per lap,g=−0.67)"

Discussion¶

Related Claims¶

• Baseline coaches produced weaker or absent learning gains: RBF improved only failure count, MIA neither outcome — related
• Learners rated the L2C coach higher than both baselines on safety, performance, agency, and satisfaction — related
• L2C coaching significantly reduces learners' lap times and failure counts from pre- to post-coaching in FPV drone racing — related
• The L2C coach adaptively modulates assistance by estimated learner skill and physical context, concentrating intervention around gates — related