The Industrial Metaverse and the Promise of Improved Knowledge Transfer

3D vs. 2D, Interactive vs. Passive, co-starring Signaling and Segmentation

Example 1 from the Kartorium platform - showing a 3-dimensional, interactive environment demonstrating signaling and segmentation

There are many claims being made about the benefits of the Industrial Metaverse, especially involving knowledge transfer in heavy industries. Here I explain the four data-backed strategies that Kartorium utilizes to live up to some of this hype. 

Background: What is the Industrial Metaverse?

The Industrial Metaverse is a digital ecosystem that combines modern tech like digital twins, augmented reality (AR), virtual reality (VR), artificial intelligence (AI), and Industrial Internet of Things (IIoT) to create a connected, interactive, and immersive environment for businesses and industries. Done well, it enables users to work, collaborate, and share knowledge without being held back by geographical and physical barriers. I've noticed the concept of the Industrial Metaverse evolve over the years from the initial idea of a purely virtual world (way closer to a video game), to an integrated and practical tool designed specifically to meet the needs of various industries.

Traditional methods of knowledge transfer within industries have relied heavily on face-to-face interactions, physical documentation, and on-site training. These methods, while definitely still effective in some cases, have several limitations. For example, they can be time-consuming, resource-intensive, and subject to miscommunication or information loss. As workforces are more and more spread out and more and more strained, these traditional approaches to knowledge transfer aren't going to cut it anymore. The new normal will require rapid access to information, better collaboration, and continuous learning.

The Industrial Metaverse has the potential to revolutionize the way knowledge is transferred within and across industries, addressing many of the limitations of traditional methods. By leveraging the capabilities of digital twins, AR/VR, AI, and IIoT, the Industrial Metaverse promises to provide a more efficient, safe, and accessible platform for knowledge sharing and collaboration. If you've followed this space at all, you've heard the promises.

The Industrial Metaverse allows for real-time data exchange, streamlined training, and the ability to simulate complex scenarios for learning and problem-solving. As a result, the Industrial Metaverse empowers businesses and industries to work smarter, innovate faster, and navigate the challenges of an ever-evolving global market.

- every Industrial Metaverse LinkedIn post ever

Kartorium is undeniably an Industrial Metaverse tool. The truth is, I believe strongly in just about all of the talking points I briefly outlined above. However, I don't think it's fair for enthusiasts like myself to assume everyone in the industry will take these claims at face value. This blog is my brief attempt at a literature review, one that highlights the strategies Kartorium has used to achieve better knowledge transfer for our clients. I'm hopeful this puts some meat on the bones of the Industrial Metaverse claims, especially those around knowledge transfer.

Strategy #1: 3D instead of 2D

The primary benefit of 3D knowledge transfer in industrial settings is the improved spatial awareness it provides. Spatial awareness is essential for understanding the layout, size, and position of machinery, equipment, or processes in an industrial environment. With 3D technologies, users can gain a more accurate sense of depth and perspective, which can greatly enhance their comprehension of complex systems, supplementing on-site experience. This heightened spatial awareness can lead to better decision-making, more efficient problem-solving, and a deeper understanding of the intricacies involved in various industrial processes.

Additionally, studies show that trainings which incorporate spatial learning, the use of 3D environments, instead of simple 2D diagrams or schematics, lead to retention improvements of up to 64% and as much as a 48% improvement to engagement. Examples of studies observing these benefits include a comparison of the transfer of route knowledge using various teaching methods (Witmer 1996), an investigation on the effect of snapshot exploration on spatial memory in a virtual city (Vidal 1999), and an assessment of the retention of immersive training compared with traditional education methods in aviation safety (Chittaro 2015). 

Strategy #2: Interactive instead of Passive

3D knowledge transfer which is interactive offers more immersive and engaging training experiences compared to traditional 2D methods. By providing an iteractable virtual environment, users can explore various elements in ways that are not possible with 2D materials. This interactivity encourages active learning, where users are not just passive recipients of information but active participants in the learning process. Studies have shown that immersive training experiences can lead to higher levels of engagement, which in turn can result in better knowledge retention and longer-lasting learning outcomes. Examples of studies showing these benefits, specifically through the use of virtual environments, include a comparison of spatial knowledge resulting from different virtual and real exploration modes (Wallet 2009) and a study on the impact of virtual learning on satisfaction, engagement, recall, and retention (Ryan 2019).

Example 2 from the Kartorium platform - showing a 3-dimensional, interactive environment demonstrating signaling and segmentation

Strategy #3: Signaling

The use of signaling in knowledge transfer materials has long been recognized as a highly effective method for enhancing recall, retention, and engagement. Signaling refers to the various techniques employed to cue or highlight relevant elements within information materials, such as outlining, spotlighting, arrows, annotations, etc. These visual cues help users to focus their attention on critical aspects of the content, making it easier for them to process and internalize the information. In industrial settings, where complex systems and procedures are commonplace, signaling can play a vital role in ensuring that users grasp and retain essential knowledge. A meta-analysis conducted by Schneider et. al. in 2018 encompassing over 100 studies on the use of signaling in learning media sheds light on the significant impact of these techniques. According to the analysis, signaling improves retention by between 42% and 64%, recall by between 22% and 43%, and engagement by between 4% and 22%. These findings underscore the importance of incorporating signaling methods into information materials, particularly in industries where effective knowledge transfer is crucial to success.

The Industrial Metaverse, with its immersive and interactive capabilities, offers an ideal platform for incorporating signaling techniques. In a 3D virtual environment, signaling can be used to emphasize critical aspects of machinery, processes, or systems, guiding users' attention and ensuring that they focus on the most important information. Furthermore, the Industrial Metaverse allows for real-time signaling, with cues and highlights that can be dynamically adjusted based on incoming data values or a user's actions. This adaptive signaling can provide tailored guidance, ensuring that each user receives the appropriate level of support and reinforcement as they navigate a digital twin or other 3D experiences.

Strategy #4: Segmentation

Segmentation is a well-established learning strategy that involves dividing information into separate contexts to facilitate better memory retention. By breaking down complex concepts or processes into smaller, more manageable segments, learners can more easily process and internalize the information, ultimately leading to improved retention. In industrial environments, the application of segmentation is particularly valuable for promoting better understanding and long-term knowledge retention among workers. Numerous studies have demonstrated the effectiveness of segmentation in enhancing memory retention. Some of these studies have specifically investigated the use of segmentation within virtual learning environments, highlighting its potential for integration into Industrial Metaverse applications. One such study (Logie 2021) examined the impact of splitting information into virtual rooms as a means of facilitating segmentation and subsequently comparing retention rates. Another study (Horner 2016) assessed the role of spatial boundaries in shaping long-term event representations, providing valuable insights into how segmentation can be applied in immersive virtual environments.

The complexities of industrial environments and processes often necessitate breaking them down into separate contexts to ensure effective knowledge transfer. For instance, a complicated assembly line or manufacturing process can be segmented into distinct stages or components, with each segment presented separately within the virtual environment. This approach enables users to focus on one aspect at a time, building a comprehensive understanding of the overall system without causing cognitive overload. Tools like Kartorium, with the ability to create immersive and interactive 3D environments, are well-suited for implementing segmentation strategies. By dividing complex industrial processes or systems into separate virtual spaces or contexts, users can navigate and explore each segment individually. This approach not only facilitates a more manageable information intake experience but also allows for better data organization.

Conclusion: Our own LinkedIn-worthy claims

Kartorium offers a transformative approach to knowledge transfer in industrial settings by leveraging the advantages of 3D environments, interactivity, signaling, and segmentation. The immersive nature of 3D virtual spaces enhances spatial awareness and allows for more engaging learning experiences, while interactivity promotes active learning and better long-term retention. The integration of signaling techniques helps to direct users' attention to critical information, improving recall and engagement, while segmentation breaks down complex processes into manageable parts for easier understanding. By harnessing the unique capabilities of Kartorium and incorporating these data-backed strategies, organizations can create effective and personalized 3D experiences that empower their workforce, driving improved performance, productivity, and innovation across the industry.

- Kartorium

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