
Dr. Kaufman helps manufacturing with VRManufacturing Industry
A recent study found that immersive virtual reality training increased cognitive load and decreased knowledge transfer compared to PC-based training, yet it only did so when inserting text and narration (Makransky et al., 2010). Yet in an early landmark double-blind study standard trained resident surgeons made more than six times as many errors as the virtual
reality trained group of residents, and the virtual reality trained group completed procedures faster in a third of the time (Seymour et al., 2002). With conflicting results across many studies on virtual reality or augmented reality training, it would be beneficial to develop a set of pedagogical insights for virtual reality instructional designers and implementors in transferring technical knowledge via immersive augmented and/or virtual reality learning environments for learning and job performance gains.
In working with Siemens and their consulting VR vendors, we were able to use the latest technologies which was great for the brand. While, sharing VR at conferences, recruiting, and annual reports looks great. The question the customer had was; How you implement new technologies to gain quantifiable advantage, is where the rubber meets the road.
Too often new technologies can get used as toys or playthings to try and test out. Nothing wrong with buying new fancy gadgets. But in the end, very little real business value gets generated with this approach. See the reports below how my work with both Siemens and the United Nations World Health Organization changes my views on how effective VR works.
The challenge is to bring the cadre of small AR/VR & AI boutique development firms into the world of learning science with new clients. By having a professional that understands both the technology and the cognitive-neuroscience of learning to aide in the development and delivery of new modes of training. Seems like a no brainer.
- Improve interactive design and development planning:
Teams are too often focusing their efforts on a few of the highest-visible levers in order to get the current planning process quick wins. Yet too often those first lines of code get baked in and gaps in the planning and infrastructure produce wild variability in production quality and deliverables. In complex production chains, that lack of insight is alarming.
- Determine the right real-world performance assessments:
Working with hundreds of interactive developers over three decades has offered me insight into a lack of assessment on performance. Performant code, Performant user experiences, and most importantly for training, performance on transfer of skills. For manufacturing clients this lack of assessment in training and transfer of skills is unacceptable.
- Optimize design loop for perfect development planning:
The diagnostic to determine how a manufacturer’s training should use cutting edge technology is the system of development. Looking at the three core stakeholders; development team and owner, the organizational sponsors, and the community or field, the training application should be architected with all users in mind. This shapes the hardware, software, and services to scale any eventual roll-out. Too often this is left to some vague idea of agile techniques. Agile while highly effective for closed loop development with few stakeholders, is not viable on its own for complex training applications, especially in manufacturing.
The training solution for cutting edge manufacturing clients is understanding the dependancies of real-world use and the horizon of scalability. By re-focusing on the end result and its applicability in the real-world use, new technology gets a reality check on usability and scalability.
By using the ‘Backward Triple Spiral’ method, development, organizational, and community stakeholders are looped in and architecture becomes more inclusive at the start. Keeping in mind that each loop has different timing, dependancies, and deliverables:
- First Loop Development insights and planning:
Most interactive developers, subject matter experts, and project owners are not trained in learning science. Understanding perspective taking, understanding best of breed simulation frameworks, and implementing gesture and embodied cognition are just some of the ways to inject learning science into more effective training.
- Second loop organizational learning:
With hundreds of C-Suite and founder meetings under my belt, the organization needs to grow the capacity to learn. Closing off various organizational stakeholders is a recipe for a silo learning application. Insights in understanding the needs of all stakeholders from the project owner to the field user are critical to understanding the organizations ability to transform and grow.
- Third loop of development:
The community or the field is where the funds of knowledge exist. I have seen too many training applications that never included the customer, the client, or the prospect. If your first question is what real-world knowledge, skills, and abilities would be present outside with customers, partners, suppliers, or wholesalers, why aren’t they included in the development cycle? That is why I call for ‘community edge learning’ where the application is in plain sight of the trainee and the community. So stop training people in a closet or cubicle, and start training them within the community, factory, or customer setting they need to be in as soon as possible to develop the real-life skills they need.
The results are groundbreaking. Now training is no longer a break-out box hidden in the annual report, it’s a driver for organizational transformation. It brings a company whose training was mandatory and boring up to date. The training becomes a catalyst for change for the project team, the organization, and the field. What matters when learning is using the science to deliver better results beyond simple completion rates:
- Improve operations and production planning:
The application focuses their efforts on a few of the highest-value S&OP levers in order to review the current planning process, identify gaps in the planning infrastructure and analytically understand demand and supply variability.
- Determine the right performance level:
With hundreds of training applications in the market, the manufacturer of major engines, transformers and transportation infrastructure needed a proper method to predict and assess their training. Using an instructional efficiency analysis formula (E=[R-P]/√2), the teams defined appropriate difficulty(R) and performance (P) against non-immersive versus VR training on the most complex training modules.
- Optimize the supply chain for perfect service delivery:
In working with dozens of software teams, it is the training development group that owns the monitoring diagnostics to determine the stressors that affected sales and service levels the target learner needed to reach. I get teams focused on resolving issues related to higher-than-normal service-tickets and lead times, by including all three loops the entire supply chain and this leads to expedited trained personnel reaching customers faster.

























































































