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Understanding Virtual Reality Training is critical.

The maximizing of VR in technical training requires organizations to comprehend Embodied Learning and Perspective-taking. With the commercialization of advanced head mounted displays with accelerometers, modern GPU’s handling multiple camera angles, magnetometers and gyroscopes it is critical for instructional designers to understand the opportunities of movement in the field of VR training capabilities and approaches.  

Embodied Training

In developing VR training, the focusing on knowledge is generally thought as paramount, yet educators know that there are 3 core domains to building learning outcomes. Most educators focus on the attainment of knowledge and its structure or what Bloom and Krathwohl would call the cognitive domain. And if we are to care  what David R. Krathwohl did to detail Bloom’s taxonomy further as deliverers of knowledge is whether the knowledge had any emotional meaning, if so we would add the affective domain.

This is a series of insights from: Dr. Christopher David Kaufman doctoral researcher in organizational learning science.  Dr. Kaufman is a certified social behavioral investigator, author, patented software developer, Fortune 100 strategist, learning design consultant, and earned his EdD doctoral thesis while working with VR development at organizations such as the United Nations World Health Organization at the esteemed Peabody College of Human Development at Vanderbilt University.

These two domains have levels of mastery. On the affective side we have receiving, responding, valuing, organizing, characterizing by value. Each of these levels have verbs that describe ever increasing levels of interest, concern, empathy, and meaning in understanding what is being taught. 

The other most focused on domain is the cognitive domain. Yet it is important to note, none of those verbs have been upgraded to virtual, augmented, or mixed reality education. And while VR instructional designers are beginning to focus on various features and capabilities around those levels of mastery; which include remembering, understanding, applying, analyzing, evaluating, and creating. Despite occasional forays by developers, almost all research on VR training has been lab experiments. 

Still VR has many affordances and should be capitalized to take advantage of the third domain of learning outcomes. This under examined third domain is the psychomotor domain. This domain is the least developed in my opinion, by the founders and committees that Bloom and Krathwohl led back in 1956. The psychomotor domain also has levels of mastery. These begin at the level of imitation, manipulation, precision, articulation, and naturalization. This is the culmination of physical skills mastery. 

In my grid of when to apply VR, what I refer to as Kaufman’s MR-PC H VR Performance Matrix. It deals with 4 kinds of embodied learning and in fact aides in the decision making of whether VR is highly appropriate. 

Making the Task-Technology Fit for Training

VR is especially effective for instruction. But at what parameters does the technology fit for various learning objectives? 

In looking at VR training – there are 4 types of development and deployment characteristics where VR is best suited for educational training.  

Complex levels of Motion: Are the interactions with the content embodied ? Is movement required or aided to gain a skill or learn a task? The range of movement in VR is not best suited to the extremes of either fine granularity e.g. finger dexterity or large movement across courts or fields. Therefore perfecting specific suture knots with fingers using a  thread and needle may not be best in VR. Nor would learning to swim across a lake. But opening a compartment with a monkey wrench or practicing arthroscopic surgery would be effective still in VR.

Complex levels of Risk: Are the interactions with the training environment and objects contain an uncertain level of safety ? Working on an unplugged toaster might not have much risk, where as working on a power transformer on a telephone pole would have great risk. The test would be:  Would I want my loved one or young person to attempt interacting with it untrained? 

Complex levels of Physics: Are the training interactions with objects that have scales beyond the norm? Very small or very large objects and interactions. The test I apply is the VR FedEx test. If the training objects can be easily shipped then VR may not be a top choice. Molecules, viruses or plane engines, cargo bays would be good examples for VR training simulations that are not easily shipped to training centers. Nor are their physics simple. 

Complex levels of Components: Are the interactions of the trainee on various objects one where there are complex relationships of many components . Does the interactions have multiple layers that are non-obvious? The test is the screwdriver test. If one tool or a maximum two tools can disassemble and re-assemble the objects to train, then VR may not be optimal. A blender or desktop fan might not be optimal, where as solar inverter might be or a telecom satellite might be. The number of steps matter as well.   

Advancing the Psychomotor Domain

Let’s break down each of these from the MR-PC matrix, and see where physical movement can add educational value. 

Each of these issues Motion, Risks, Physics, Components are enhanced by motor-skills needed and a level of skill mastery that is required to excel at the intended role of the learner. Content that is designed to develop and integrate motor skills tends to be retained longer. Many if not most skill development can be enhanced with movement to anchor and access knowledge attainment. 

Key to VR is how virtual reality systems today can capture and track gesture and bodily motion. From hand controllers that have inputs and accelerometers to cameras that can capture motion and gestures, VR systems today can record and assess movement. 

Embodied learning where gesture and movement are congruent with both affective and cognitive learning helps increase retention and retrieval . Therefore while challenging, developers should seek out every opportunity to convert 2D learning into active 3D spaces where movement helps support comprehension and meaning. 


Often VR training misses the opportunity to add the right movement to the training in unique ways. The key here is finding the middle ground of space, gesture, and sensorimotor recall. The movement should not depend on the hardware or software library, it should be what is required in real-world scenarios. 

For example, in training to repair a jet turbo engine, the typical VR physics allow one to raise the engine above the users head. But by enforcing the true laws of gravity, the VR trainee must bend down and crawl under the engine in VR. By embodied movement that mimics real – world gestures, retention of the training is enhanced. And more importantly transferability of the training is strengthening the overall procedures being taught.   


Understanding how to repair a mega-watt power transformer underground can be a high risk endeavor. Often body position in terms of distance can be a factor. Integrating tool tips and feedback is essential. But what if you add warnings via signage for example, this can be bring a higher level of real life fidelity. Looking around for key information, is a stand-by for discovery games, but as instructional designers who want to ensure proper situational awareness, designers should include those movements as well and support feedback for correctly achieving it.  

To further strengthen risk assessment via motion, try combining the knowledge of risk with what is called Proprioceptive accuracy or re-calibration. This is enabling the force-feedback of variable movement speed and span to be adjustable or reactionary. Think of this as with your setting up a PC or laptop mouse or track pad. How fast does the mouse cursor move? And what distance does it move based on a gesture. This is especially effective in trial and error of “is the kettle hot” sequences. Moving the trainee into or out of spaces and allowing them to adjust speed and span when feedback creates positive or negative consequences from that gesture or action will help embed the importance of the cautionary gesture, particularly if the wrong or hasty motion creates a red alert or virtual explosion. And in particular if that motion has specific characteristics that are important. “Cut the red wire first” are these types of variable feedback proprioceptive procedural actions that may need emphasis. 


Do you move the molecule, or do you walk around it? The evidence from research suggests both but for different goals. There are reasons for this but rather than go into the ways the visuospatial sketchpad part of our memory system works, instructional designers should use both with intent. It’s relatively simple to gesture a large industrial engine to spin it using Unity or Unreal as your platform of choice. And adding a crane or forklift with their own dynamics to do so might seem costly or a diversion from learning the workings of the engine. But care must be taken to allow the environment to match the various views. 

Perspective taking is the act of perceiving a situation from alternative points of view and it enhances learning . Let’s return to the molecule. If you want the student to understand the structure, then allowing them to move, flip-around, or tilt can help them map the structures to the ionic bonds between atoms. But would flipping the molecule when it reacts to another molecule be helpful? For sequences or interactions, it might be better to have the student move around the phenomenon to get a 360 degree view. And we might change the environment with each perspective taking. 

So if the student needs to understand the phenomenon of say baking soda and vinegar to create carbon dioxide gas, moving around the event might be more effective to see how the object reacts to each other and their environment. Therefore, using various types of environments to cue the perspective is relatively easy and can reinforce the understanding of structural understandings vs phenomenal events vs action-reaction of objects or procedural consequences. And each of these perspectives have vastly different meanings in terms of physics of how the objects behave in real-world scenarios. That is important to learning, and since the real world does not allow you to expand and flip molecules in space with the twist of your wrist just yet, anchoring environments to different perspectives can help provide a scaffolding structure and sense making to reduce cognitive loads to the various levels of physics in learning modules. Too many motions without meaning can deleterious to learning as well. 


As the cost of digitizing training comes down, often companies take training manuals and convert these to visual 2D or now 3D training. Beware, complex sequences with various tools, many precise procedures, and dozens of objects can be overwhelming for trainees. Therefore, slowing down the steps with precise gestures and movements can aid in the understanding of the various layers of the training. By adding congruent gestures and movement to the procedure the training utilizes, better learning is achieved. 

This is where motion, risk, and physics add up to increase the educational impact across various components. Let’s take a few questions about complex component training. Are there specific movements that ensure better outcomes? Are there risks involved if a gesture or procedures are not done correctly? Does the size, weight, motion of objects have serious consequences? Each of these questions demand answers that can be added to the components and their procedural interactions. Does a fan belt need not just added but tightened. Why? What are the failures of loose fan belts? Striped nuts and bolts, do these increase misfiring’s? Do trainees understand how the objects work together? Do they understand the financial cost of failure? Would an animation of the spinning of the engine help in understanding the components’ function? Building a transformer from the ground up may not include what each part functions as. But why would you train a repair man to replace a part if they don’t know the function, behavior, expense, and interaction with other objects? Each of these questions provides ways for your VR instructional designer to add gestures and motion to actuate the objects in their environments to aid in their building a broader and deeper understanding of their training. 

Finally, while the focus here has been on the psychomotor domain, the training of building or repairing an engine or understanding a chemical reaction with embodied learning, does not preclude the importance of using the cognitive and affective domains as well. Providing meaning and value with levels of understanding around various levels of facts, functions, and figures only deepens the actual learning experience by utilizing the whole brain in an integrated fashion. If you use advanced technology such as VR, the learning science you apply should be just as advanced.          

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