Much like how a tennis coach can hold onto their trainees’ racket and guide them through the motion of executing a swing, haptic feedback delivered through a robotic interface can be used to teach operators how to move. We study this idea in the context of robot-assisted minimally invasive surgery. Specifically, we study how error-amplifying feedback, as well as guidance can be adaptively tuned to accelerate an operator’s learning given knowledge of their skill level.