Motor Learning and Feedback Until recently, the most common means for providing feedback about performance errors involved a high degree of abstraction, presenting errors in the form of simple plots, gauges, bars, lines, or numbers.13 Abstract visualizations might suffice for simple tasks because they can represent a key feature of a movement in an unambiguous way, but few art/dance students relate to them immediately and emotionally. Furthermore, it is difficult to convey to dance students feedback about complex multidimensional movement in 3D space in abstract form. They are accustomed to learning through animmediatesensory(kinesthetic) experience. Augmented reality and VR simulators have great potential for facilitating motor learning. Feedback can be provided either during task execution (concurrent feedback) or afterward (terminal feedback). Although terminal feedback is effective for simple tasks, concurrent feedback is more effective for complex tasks with several degrees of freedom, which are unlikelytobemasteredina single session. Concurrent visual feedback presents side-byside or superimposed moving-image visualizations of the ideal movement14 and student’s actual performance. The concurrency of the feedback makes the relevant information more immediately comprehensible. Concurrent visual feedback has been shown to be effective in learning complex tasks in domains such as sports and physical rehabilitation. (For example, superimposing target angles over liveaction video has been successfully used to teach pitching in baseball.) Similarly, concurrent display bars or force-time plots have been used to indicate the deviation from the desired or ideal (target) force for physical therapy patients practicing mobilization skills. In some cases,a headmounted display provides concurrent visual feedbackbysuperimposing aghost target image over what the client would ordinarily see. Studies found that this form of feedback was not optimal however because it required frequent head movements and restricted the user’s field of view. Prescriptive feedback is designed to help more experienced learners correct deviations between their performance and the target movement. Such learners benefit from more focused feedback, with the information supplied when deviations reach a certain threshold. With such feedback, a convention is generally used to signify the degree of movement errors (such as highlighting with different colors superimposed on the limbs). Prescriptive feedback allows learners to focus on the specific aspects of their performance they want to over real videos (as well as side-by-side and superimposed visualization) in that the animations are simplified to the point of offering only the most salient information.