Since its genesis in the 16th century, ballet training has largely been unchanged: it relies on the word of mouth expertise of ballet teachers passed down generation to generation. Top-tier training is only found in few locations around the world, and comes at an exceptional price. In this context, remote education might represent an affordable alternative: it would allow skilled dance teachers to connect with a wider audience. Although prior research has begun to develop technologies for dancers, there is no consensus on the type of feedback that should be provided to allow remote ballet learning. We prototyped four variations of a technologically simulated mirror to evaluate different combinations of feedback commonly used in traditional ballet settings. Our preliminary results suggest that systems for remote ballet learning should provide combinations of visual, verbal, value, and corrective feedback.