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New technologies impacting on-demand learning

Artificial intelligence, augmented reality, voice interfaces, and other emerging technologies are helping learners at their point of need.

By Karen Hebert-Maccaro

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merging technologies like artificial intelligence (AI), voice interfaces, and augmented reality (AR) are poised to radically change the nature of work—and learning. And in response, Learning & Development (L&D) and HR departments are changing what they do and how they do it. They have a new role to play: architects of dynamic learning ecosystems.

While the formal learning experiences at the center of most current L&D programs are as valuable as ever, L&D professionals now have a huge opportunity to bring more value to their organizations through on-demand, informal learning powered by new tech-enabled platforms and tools. With these new offerings, L&D expands its mandate and impact beyond “programs” to providing an ecosystem that enhances workers’ productivity precisely because it’s embedded in their daily routines and is right at hand when they need it.

Employees’ expectations of technology are often shaped outside of the workplace. Voice assistants like Alexa, Siri, and Google Assistant may be available in as many as 55% of homes by 2022. Smartphones and tablets are constantly by our side, letting us get directions or send a text. In many cases, these technologies are helping us become more productive outside of work.

We see similar behavior on O’Reilly’s learning platform. A significant portion of learning events over the last year have been nonlinear—our users are frequently logging into the platform to answer a quick question, solve a problem, and return to their workflows. We’re hearing from several clients that this type of behavior is helping their employees save time and be more efficient.

Emerging technologies such as natural language processing (NLP), voice interfaces, virtual reality (VR), and augmented reality (AR), among others, are likely to accelerate these nonlinear trends. Of course, these technologies will not replace the need for immersive learning experiences but will supplement them with access to high-quality tools and information at the point of need.

Point of need, but embedded or adjacent?

It’s useful to consider two distinct kinds of point-of-need learning: performance support and performance adjacent. Performance-support technologies are directly embedded in the workflow itself. Performance-adjacent tools are not embedded into a workflow but are easy to access and allow the learner to jump out of the workflow, get the answer or idea they need, and get back to work seamlessly. Performance-adjacent tools can be more cost effective and scalable than traditional performance support because they don’t need to be customized to specific workflows or embedded in particular technologies.

While performance-adjacent tools don’t need to be custom built, they do need to provide learners with precise and efficient help at their point of need. This is no small feat. People want the best and quickest solution. They don’t want to read through several pages or watch an entire video, as formal learning experiences commonly require.

Enter the wonders of increasingly sophisticated technologies!

Natural language processing (NLP) is a field of computer science that uses AI to process large bodies of natural-language data. NLP allows fine search capabilities, so learners can jump to the exact point in a digital book, chapter, video, or paper that provides the relevant information they need.

AI is a key component of another emerging technology that may well be on your kitchen counter or a favorite conversational partner of your toddler (think voice-enabled devices like Google Home or Amazon Echo and voice assistants like Siri). Voice technologies
represent an exciting frontier for learning. These interfaces recognize and respond to the user’s speech, in effect creating a new, but familiar, communication channel that runs parallel to the learner’s “regular” work. The learner can speak a question and receive an answer from a trusted learning source without even taking their eyes off what they are working on.

While some of the technologies that will likely accelerate this nonlinear trend are still nascent in the learning world, we know that learners are already seeking performance-adjacent tools. For example, we see performance-adjacent behavior in the 2.25 million users of the O’Reilly learning platform. By aggregating one quarter’s worth of usage data across 12 industries, we examined 1,622,983 individual learning events executed by 169,146 unique learners. We found that inside these organizations, learners were engaged in nonlinear learning behavior an average of 42% of the time.

Learning powered by AR and VR

The growth of augmented reality (AR), a technology that overlays digital information on real-world settings, and virtual reality (VR), a system that creates simulated digital environments, is empowering learners in new ways.

AR has enormous potential for point-of-need learning. In December 2017, Apprentice raised more than $2.5 million in venture funding for its AR tool aimed at scientists, engineers, R&D professionals, and those in associated manufacturing roles. Their solution runs on smart glasses and allows workers to troubleshoot machinery remotely or conversely to share what they see on site with others in remote locations. It’s an intriguing glimpse into how AR can help workers learn on the job.

AR and VR also hold promise for formal learning activities. Walmart, partnering with VR startup STRIVR, has developed training for its associates utilizing the Oculus Rift VR headset. STRIVR’s technology puts Walmart employees in simulated real-world situations so employees can learn how to deal with a myriad of retail challenges. In a nod to blended design, Walmart is connecting headsets to a classroom screen that allows a class and an instructor to observe the active learner (i.e., the one wearing the headset) and prompt discussion and instruction.

Architecting an ecosystem

L&D professionals must tackle the challenge of enabling frictionless learning across every boundary we currently hold. We must do this to remain relevant, to meet the demands of our learners and organizations, and to continue to be strategic enablers of individual and organizational success. Fortunately, advances in technology are fueling our ability to answer this call. In many instances, we need only ask the right questions and seek the right features for the ecosystem to become balanced. So the next time you are considering your portfolio of learning offerings, consider these questions:

1. Do the learning tools that you’re providing to your employees allow for performance support and performance adjacency? Are learning tools being used in this way in your organization, and can you tell the story of their impact?

2. How “smart” are your learning tools? Can learners engage with them in different ways (e.g., reading, watching, talking) or find a quick answer to a question (e.g., find what they need without having to skim through irrelevant material)?

3. Where are you using AR, VR, and voice in your strategy? What problems (behavioral, structural, or technical) could an AR, VR, or voice solution solve for your organization?

4. Can you create more opportunities for fun (which leads to engagement and retention) in your learning experiences through simulations, gamification, and social learning? What would lead to more engaged employees and learners?

Many organizations have the linear and formal learning experiences optimized after years of practice. These experiences have value and shouldn’t be discounted, but they don’t provide the fully balanced ecosystems our learners need. The on-demand, simulative, and augmented technologies we have at our disposal allow us to truly architect ecosystems that meet the learner where they are and exactly when they need the learning. The possibilities are many but one thing seems certain: point-of-need and on-the-job learning experiences are about to get a whole lot more fun and drive stronger results.