From Movement Adaptation to De Novo Learning: A Design Space of VR Interaction Techniques

VR interaction techniques define mappings between physical movements and virtual outcomes. While some mappings are learned through the adaptation of existing movement strategies, others require acquiring entirely new control policies. Drawing on motor learning theory, we introduce a design space that organizes these mappings into three families and provides a basis for reasoning about how the mappings are learned. To examine learning within individual families and their compositions, we start with two simple hand-based mappings, mirror reversal and cross-hand control, and their combination, allowing us to probe the design space in a controlled experiment with 96 participants. The mappings differ in initial difficulty, but participants achieve comparable overall learning. In the combined condition, prior exposure produces mapping specific start-up advantages. We discuss how this design space can support the analysis and design of VR mapping techniques.