New technological paradigms have been adopted in recent years to move beyond static representation approach to university-level chemical education, offering alternative ways for students to understand molecular science outside the wet lab. For example, computational chemistry can provide students with the ability to watch screen-based movies of molecular motion or build structures for subsequent postprocessing using specialist codes, as well as introducing them to the power of computational workflows for understanding molecular processes. However, few tools enable students to intuitively interact with the rigorous 3D dynamics that governs molecular motion. In the past few years, research within psychology and neuroscience has shown that multisensory processing increases attention. Inspired by findings like these, our group has actively been developing immersive technologies for enabling multisensory perception of nanoscale dynamics, exploring perceptual channels beyond vision, including audio, touch, and proprioception. In this work, we illustrate the use of research-grade simulation tools to enable interactive molecular dynamics simulations in VR (iMD-VR), which can be used to create multi-person interactive dynamics environments to help students learn about molecular motion and dynamics. In utilizing state-ofthe-art tools like those described herein, students not only increase their understanding of chemical structure and dynamics, but they also gain fluency in using sophisticated visualization tools, providing benefit in the form of transferable skills and computer literacy which is practically useful beyond their university education. As a research field, computational chemistry is increasingly essential, providing insight into molecular physics, structural biology and materials science, and driving progress in areas such as drug design, catalysis and biochemistry, where it routinely provides molecular-level insight into experimental results, and enables the investigation of areas which are difficult to study using standard laboratory and analytic tools. Important challenges arise in teaching computational chemistry techniques and tools during undergraduate degrees. Because of the complexity of the field, most courses allot little time to the teaching of these tools as well as the required computer literacy. Moreover, given the wide range of domains where computational tools can be applied, it is not often possible to give more than a cursory introduction to some of the tools and the physical insight that they can provide. For example, training in one area, such as classical molecular dynamics using a forcefield approach, does not necessarily provide students with the tools to tackle other computational chemistry areas, such as electronic structure calculations. The difficulty is compounded by the fact that many computational tools are legacy scientific codes, and therefore offer a user experience which feels dated compared to the sorts of apps and media experiences to which students are often accustomed. For example, problems arise from the fact that molecular dynamics packages often require students to deal with bespoke (and often dated) input formats and bash scripting for the first time. Many computational chemistry codes are not user-friendly, requiring specialist training to acquire familiarity with each code and its associated jargon, in part because several popular molecular dynamics simulation packages were designed prior to the availability of modern human-computer interaction technologies (CHARMM for example can trace its origins back to the time of FORTRAN punch cards). Over the past several years, we have run computational chemistry classes teaching students how to use these powerful but highly specialised legacy tools, and we have often found that it can be difficult to convince students that learning to use such tools is preparing them to cope with the workflows of the future. Most common molecular viewer interfaces used for teaching chemistry require the user to interact with molecules through the traditional 2D interface. For complex 3D structures, such interfaces have clear limitations. The more popular molecular visualisers of the last 30 years provide a 2D perspective on what are naturally 3D structures and processes, and also suffer co-location issues. In a recent paper by O'Connor et al, we described this so-called 'colocation problem' in detail. Briefly, perfect co-location arises when the interaction site in physical space is perfectly aligned with the interaction site in digital virtual space. For example, touchscreens achieve perfect co-location in 2D because the interaction site in physical space is identical to the interaction site in virtual space. This is a significant reason why children at a very young age find it straightforward to navigate a touchscreen. Programs such as Gaussview or VMD which are primarily built to utilize a mouse and screen interface do not represent co-located forms of interaction. For understanding and manipulating complex 3D structures, the constraints of this type of interaction can lead to unintended motions (e.g., moving an atom out of a molecular axis by accident) and can be frustrating for students.