As we all know, technology is moving at a breathtaking pace. A mere 10 years ago, Facebook launched its mobile app (in earnest) – a milestone many believe marks the true shift to the age of mobile computing, the largest digital transformation since the rise of the Internet in the 90s. Just as impactful as the mobile digital transformation, we are entering the decade of spatial computing. Everything from self-driving cars to advanced autonomous systems will rely on spatial computing, the theoretical apotheosis of industrial and digital transformations.
As we sit on the precipice of our next big digital step forward, we need to ask ourselves how to prepare for an explosion of complexity in our daily lives.
Spatial computing, particularly Augmented Reality, has the potential to force-multiply the power of human intelligence. In many respects, AR is our best way to contend with the inherent complexity of our future. And while AR has limitless applications, one area it will help meet the challenges of our complex future is through training and knowledge acquisition.
AR has already demonstrated huge benefits to employee training. Inherently on demand, AR training can reduce costs significantly without the need to travel to seminars and classes, especially if implemented on existing hardware platforms like mobile phones and tablets. It can also help job training where safety might be a concern. But most importantly, AR training provides more effective learning and retention by removing cognitive barriers, creating stronger emotional connection to content, and narrowing focus to core subject materials in ways that were not previously possible at scale.
In his book, UX for XR (Design Thinking), Cornel Hillman cites studies that show AR participants learn an average of “four times faster, with 3.5 times higher emotional connection while being 2.5 times more confident and four times more focused.” What this study highlights goes beyond mere rote memorization. Emotional connection and focus are primary indicators of true knowledge retention. In situ spatial interaction, gestures and speech all elevate digital engagement in ways that have profound impact on cognition.
Bloom’s Taxonomy of Learning is an interesting framework to consider as we evaluate the impact of augmented reality on knowledge acquisition. Originally published as the ‘Taxonomy of Educational Objectives’ in 1956 by Benjamin Bloom, the framework has undergone various iterations to get it to its current state. The framework is meant to help structure objectives and learning goals, organize the objectives in a way that makes sense, and ensure that instruction and assessment are aligned with objectives. Bloom’s work has served as a cornerstone in structuring curriculum at all levels of education from pre-K to post graduate and professional instruction.
With Bloom’s Taxonomy, we can evaluate the impact of training with the use of AR. One could argue that AR helps redistribute cognitive load from the base levels of Bloom’s taxonomy to the higher levels of cognition focused on evaluation, adaptive thinking, judgment, and decision-making. We can also look at practical applications in training around smart systems and medical equipment to help illustrate the value of AR with respect to Bloom’s Taxonomy.
At its base, we find ‘Remember’, or the ability to recall facts and concepts. Any deficiency in this base level of knowledge impedes efficiency in every level above it. Much of our superficial and factual knowledge has been offloaded to digital sources like Google and Wikipedia. The ability to project factual knowledge into our field of vision, as needed, will supercharge our ability to understand, apply, analyze and evaluate problems and solutions like never before. Rather than ‘right-click -> Look up’ on your 2D screen, a simple gesture or voice command can pull up relevant information in spatial proximity to your focused gaze, accelerating knowledge application in a subtle but paradigm shifting way.
Beyond the level of ‘remembering’ in Bloom’s Taxonomy, we progress to higher levels of cognition. Because AR projects information into the real world, and because AR experiences can optimize around gaze and gestures, learning can accelerate at all levels of the taxonomy with supercharged focus and engagement. Removing a litany of impediments related to focus and context switching will have profound impact on engagement, comprehension and retention. At the ‘Understand’ level of the taxonomy, we want the trainee to identify, locate, select, and classify. At the ‘Apply’ level of the taxonomy, we want the trainee to solve, demonstrate and operate to reflect competency from the lower levels of the hierarchy. Again, in situ information projected into the real world against real objects fast-tracks this level of comprehension.
Imagine the simple case of AR training for maintenance of a robotic arm. The goal is to diagnose and fix a problem related to restricted movement of the equipment. With a simple voice command, device instrumentation data can appear overlaid on top of the arm with various status readings and error codes. A voice command can bring up details for a particular error code. AR has helped at the “Remember” level. The AR instruction could then walk the trainee through a procedure, step by step, while she is working with the physical equipment. Having all of this information overlaid in context accelerates the trainees ability to identify and classify a mechanical issue with the robotic arm. AR has helped the trainee ‘Understand’ more efficiently than ever before.
Because augmented reality accelerates the ability to recall facts and understand basic concepts in novel and effective ways, cognitive load shifts away from areas of the brain devoted to memory retention and moves toward the area of the brain responsible for critical thinking. With the limitless simulations possible through AR, the trainee is engaged at a level that promotes emotional connection with the content, which then fosters deeper retention of the material. Quick visual feedback loops at the point of execution accelerates richer application, analysis and evaluation – concepts at the higher end of Bloom’s hierarchy.
Medical device training is a brilliant use case for augmented reality. When successful, it improves the accuracy, reliability, and speed of patient results to make measurable impact on human lives.
As an example of real-world application of AR integrated into an overall learning experience, consider the assembly of test kits for medical labs. These kits require careful placement of various test tubes and solution vials into precise locations depending on a particular SKU. AR content can help with repetitive selection and placement of the parts into the correct position in the kit. Once the trainee achieves a certain level of comfort in remembering and understanding the general kit construction, AR can start introducing variants of the kit on the fly, including incorrect part numbers and assembly ordering. The trainee is now engaged at the application, analysis and evaluation levels of our hierarchy. The number of hours required for a trainer to prepare and execute these scenarios in the real world makes this type of dynamic training nearly impossible without AR.
As we conclude our application of Bloom’s Taxonomy to AR training, we consider the top of the hierarchy: Create. This level of the taxonomy reflects true mastery of subject matter. As we look at the next technology wave, we see a human capital resource gap. The demand for mastery cannot be met with traditional forms of knowledge acquisition. Curriculum development and execution, especially for the medical devices and smart systems of our future, faces too many impediments to be truly effective without augmented reality. Costs of training prep, lack of access to heavy equipment and safety concerns present practical problems that AR can solve. Beyond cost and logistics, AR offers a revolutionary opportunity to accelerate mastery. Given the growing complexity of technology, we need the AR revolution to help get us there.
As we highlighted in a previous post, AR has already demonstrated huge benefits to workforce training. Inherently on demand, AR training can reduce costs significantly without the need to travel to seminars and classes, especially if implemented on existing hardware platforms like mobile phones and tablets. It can also help job training where safety might be a concern. But most importantly, AR training provides more effective learning and retention by removing cognitive barriers, creating stronger emotional connection to content, and narrowing focus to core subject materials in ways that were not previously possible at scale.
Many organizations have begun to embrace and prove out the effectiveness of augmented reality as a critical method to train their workforce. Boeing has reported a 90% increase in ‘first-time’ quality and 30% reduction in delivery time with the use of AR in the training of its manufacturing engineers. Major investments in AR are accelerating in important industries and sectors. For example, the US Department of Defense, more specifically the US Airforce, is turning to AR to train over 16,000 Civil Engineers on equipment too expensive to be made readily available at all the necessary outposts throughout the world. This massive investment in augmented reality underscores the essential role it will play in all areas of the economy in the not-so-distant future.
You may ask: “But how do I implement a training program leveraging the power of AR technology?” This prospect can be very intimidating. But, in many respects, you have the infrastructure in place already.
Hardware
While we expect to witness big leaps in technology in the next couple of years, particularly as it relates to head-mounted devices (such as the Hololens), an AR device is probably in your pocket as we speak. Unlike Virtual Reality which requires specialized wearable equipment, iPhone and Android devices have had AR componentry in them for quite some time, including advanced cameras, sensors and chipsets. The good news is that your workforce is already equipped to take advantage of AR at scale. Sure, the future holds some very promising immersive “Metaverse” experiences with fancy glasses, but there is no need to wait to start integrating AR into your existing digital learning and development strategies.
Now that you do not have to worry about expensive hardware roll-outs to your workforce, you can begin to evaluate how to extend your existing learning and development investments to integrate augmented reality content.
Content Creation
At the heart of any learning and development strategy is the curriculum. Organizations rely on a set of industry-standard tools to create content… Everything from PowerPoint, video-editing tools like Premier and Camtasia, as well as high-end tools like Articulate’s Storyline for interactive course material. Tools like these give authors endless possibilities for delivering information and assessing comprehension. An AR authoring tool like WorkLink Create from ScopeAR provides a similar content creation experience, but with giant leaps forward in interaction and engagement possibilities.
Like most creator platforms, WorkLink Create allows authors to create step-by-step training experiences. However, with WorkLink Create, training content can overlay on top of real world subject matter. Animations and highlights can help guide and direct the learner as they step through a learning module. Additional contextual information can appear with a simple voice command. You can even repurpose your existing 2D training material alongside real-world subject matter or provide video inset windows for on-demand supplemental information as a learner steps through a particular AR training experience.
Content Delivery
AR instructional content needs to integrate into existing curriculum. A learner should expect to see all content necessary to achieve competency in one spot. Imagine a training curriculum, say for maintenance of a genetic analyzer for a medical device manufacturer, and the curriculum includes a series of courses. Each course contains a collection of learning modules. A routine maintenance course could include a series of interactive web training modules, a couple of videos, and potentially a quick assessment in the form of an augmented reality quiz. The course is accessed through your Learning Management System. Instruction designers can now integrate AR content into traditional course material as an interactive learning module. As an example, after selecting an AR learning module from the course’s table of contents, the learner is presented with a QR code. The learner can easily scan the QR code with their phone and launch into the specific AR learning module.
Assessment
Beyond content management and delivery, an AR content platform needs to support the common ways of assessing a learner. The key promise of AR is to accelerate comprehension and retention by promoting critical thinking. AR content needs to enable the key components of assessment through standard data tracking and reporting. At the very least, the platform should make it very easy to report on the following items:
Did the learner complete the training module?
How long did it take to complete?
Did the learner pass/fail?
What was the overall assessment score?
While these may seem like basic items, the majority of online assessments captured within a Learning Management System are based on these 4 items. AR content platforms need to make it easy for creators to build content that will provide assessment output. Once a learner has completed an AR training module, the AR platform needs to make this data available to the LMS for a training administrator to track overall competency.
No device or travel needed to train. Only a flat surface required.
Taking our example of the DNA analyzer, a learner has launched an AR experience on their mobile device focused on troubleshooting technical issues with equipment. They are guided through an interactive instruction projected onto the real-world subject matter. Throughout the AR instruction, knowledge checks are presented to the learner. Some of these knowledge checks can be interactive, perhaps asking the learner to select the correct inspection approach needed to troubleshoot a maintenance problem. Answering correctly unlocks the next set of steps in the training module.
Creators should have the option to create scored quizzes in their AR experiences as well. At the end of the training module for troubleshooting technical issues with the DNA analyzer, the content creator can insert a quiz, picking from a variety of standard question types. Beyond typical multiple choice and true/false type questions (which have value in AR with their spatial proximity to real-world subject matter), AR enables highly interactive training assessments, such as selectable hotspots in 3D space, taking the learning experience to a new level. This type of interaction has been proven to increase overall learning and retention.
Once the learner has completed the work instruction, the AR platform should package and send the assessment data to the LMS. A number of different methods should be available to make this integration, but at the very least, data should be made available through a secure API. And native integrations with market leading Learning Management Systems should make a closed loop learning experience relatively seamless.
In summary
Organizations have invested millions of dollars in their content delivery infrastructure in the form of Learning Management System, Content Management Systems and Competency/Skills Management Systems. An AR solution needs to integrate with these existing ‘systems of record’, thereby extending the value of these investments. They have also invested in the talent needed to deliver compelling learning experiences. Launching an AR Learning and Development program can sound daunting, but in reality, it is extending existing investments to augment (pun intended) a comprehensive and future proof strategy to train your workforce.
