Game-based simulated learning environments that leverage extended reality technologies are expected to become a cornerstone of STEM workforce development as they offer accessible, flexible, and adaptable alternatives to traditional physical spaces. While these environments may be designed to provide social and experiential learning opportunities that can support students’ acquisition, practice, and transfer of fundamental skills, there is much research needed to understand how to capture, model, and transfer trace data to inform these support scaffolds. Some conceptual theories and explanatory models of immersive virtual reality learning are beginning to emerge, but either fail to account for the role of trace data or still require empirical testing. This paper briefly describes an immersive virtual reality (IVR) study that examines the development of basic chemistry lab skills for (N = 45) high-school students using the VR game HoloLAB Champions. Participants completed multiple chemistry lab skill training exercises in a physical lab and in the game-based simulation lab space. During this experiment, participants’ multimodal data were captured including self-reports, audio and video recordings, event-based data, and gestures. We discuss the challenges of modeling and transferring various trace data between the real and simulated world experiences and what this may entail for the future development of adaptive and intelligent scaffolds.