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The exponential advancement of technology influences every facet of our lives. Corporate learning is no exception. By way of use cases and examples, this article touches upon a few significant technologies and outlines how they are expected to improve corporate learning.
Blockchain
Blockchain is often associated with digital currencies like bitcoin. However, digital currency is only one application of blockchain. At its core, blockchain is a form of encryption for a digital asset that ensures provenance of the asset as it changes owners. As an example of this concept, provenance is also required during the “title search” process when buying property. Someone is paid to review hundreds of records to ensure the buyer is comfortable that the property cannot be claimed by anyone else. Blockchain allows this to be done for a digital asset.
One of the exciting examples of blockchain in learning is the concept of portable credentials. A learning authority such as a university or a corporate body may issue a secure digital credential encoded in blockchain. For example, rudimentary conceptual versions are emerging in the form of learning badges or credentials from companies like Acclaim and Learning Machine.
This credential can then be used to qualify for a role when applying for a job. Other credentials obtained from various reputable sources may be assembled to constitute a degree or a specialization in a certain field. Some credentials may have certain “time to live” and may need to be refreshed.
Consider the rapidly evolving field of cybersecurity. One may obtain a blockchain credential for fundamentals of cybersecurity that requires 12 credit hours, and every year it may need to be “topped off” by four credit hours of cybersecurity refresh learning. A chain of original blockchain credentials followed by a few refresher credentials may certify someone as a current cybersecurity expert.
Artificial Intelligence
Artificial intelligence (AI) has been a buzzword since the 1960s. Recent advances in computing power have made the timely execution of complex AI algorithms possible. It is now practical to apply AI, creating a resurgence with AI applications going mainstream.
Under the AI umbrella, many capabilities are commonly included.
The simplest form of AI constitutes a rule engine. A rule engine determines an outcome based on a finite set of known static conditions. A slightly more advanced form of AI constitutes modeling a phenomenon in terms of a decision tree and traversing the decision tree guided by different weights assigned to the branches of the tree. The weight of each branch determines how the program will behave under different conditions.
An even more advanced form of AI constitutes neural network modeling. Think of the tree with the capability to learn from outcomes and adjust the weight of the branches. This scenario tries to simulate how a logical brain works, so neural networks are rudimentary ways to model that style of thinking.
I believe several forms of AI will fundamentally influence learning in the near term and the future.
In the near term, AI will make more relevant recommendations based on learner preference, history, job data, peer usage data and more. One can already see AI being used in modern learning technology in the form of digital assistants that are embedded directly into a learning experience platform (LXP). For example, at Skillsoft, our Percipio platform has shown a rudimentary conceptual application of Amazon’s Alexa in the learning context. And similarly, Saba’s TIM (“the intelligent mentor”) is another example of AI-based assistant functionality directly embedded in the learning experience.
Soon, AI combined with biometrics will act as a learning coach that is able to measure learning effectiveness and adapt to learning behavior.
Pervasive And Immersive Computing
Over the last 40 years, the cost-performance ratio of computers improved exponentially. This has allowed computers to propagate from the cold glass room to the active badge that one wears to enter the workplace. Some are so integral to modern life that people often do not refer to them as computers. At the same time, new interaction paradigms such as virtual and augmented reality have brought Disney-theme-park-like realistic experiences into the home. Such experiences, although virtual, leave a very realistic mark on the human brain. A combination of these technologies has already started to revolutionize learning.
Step one of pervasive computing is mobile computing. A modern learner is hamstrung if the learning material is not available on the mobile phone, which has clearly become an integral and required part of corporate learning. Along with improved access to learning, the phone provides new opportunities: It makes new modalities like audiobooks more useful. It allows better retention via mobile gaming paradigms. And it allows for learning reinforcement via carefully placed alerts and quizzes.
Early application of mobile learning reinforcement can be found in the Axonify and SwissVBS applications.
Immersive experiences like VR/AR are already part of many kinds of specialized learning. For example, when Walmart wanted a new way to train its employees that was different and more effective than the standard training practices, the retail giant enlisted the help of STRIVR, a specialist in VR training content and a Skillsoft partner. The partnership resulted in a next-gen learning program that utilizes VR technology.
Retail is not the only ideal use case for immersive training experiences. Initial applications will be found in custom training for factory and other field workers because interactions with machinery and physical goods are simply better learned via such simulated experiences. For more generalized learning, VR will be combined with AI to create a dynamic experience for the learner, such as a presentation skills course that virtually places you in an auditorium and incorporates audience reactions as you are speaking.
Obviously, no one has a crystal ball. The combination of the above technologies, however, is certain to create valuable and exciting new learning experiences unheralded in the previous decades. The end result? We will learn faster, better, deeper than ever before.