Top 5 digital tools driving the next generation of eLearning

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Top 5 digital tools driving the next generation of eLearning

It’s well known that workplace learning or in fact all kinds of learning are now being thought about in different ways and is no longer the learner sitting facing the instructor who then imparts learning materials.

Naturally the content of what people are taught is a fluid thing, depending on the objectives of the instructor and needs and current level of the learner. But recent advances in digital technologies have opened opportunities to create far more engaging, flexible and therefore effective training approaches.

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Here’s a snapshot of our top 5 digital tools which are driving workplace eLearning:

1.     xAPI
Originally known as ‘Tin Can’, xAPI is one of the most disruptive technologies to intersect with the world of workplace training and education. Like so many great digital innovations, it was originally born out of the US government as an open standard for enabling learner engagement and learner interactions to be tracked, monitored and managed.

Its genius lies in its ability to work across any digital platform or environment. This makes it an extremely powerful technology for supporting mobile communications, allowing staff to progress with their training programs wherever they are. A key added benefit is being able to deliver training and information to staff while they are in the field, therefore delivering more authentic ‘real-world’ experiences.

2.   Virtual Reality  
You’ve probably seen or experienced yourself the somewhat disconcerting effect of virtual reality (VR). You might be hang-gliding in the Andes, driving Formula One at Monaco or in some other highly-convincing scenario which has your adrenaline pumping as you feel you might lose balance.

But in the realm of training and education VR is much more than a game or a toy, able to deliver highly immersive and interactive learning experiences.

In highly-technical professions such as medicine, engineering or high-end manufacturing, VR has been shown to be very effective in framing tasks like problem solving whereby elements can be presented in a more fluid way. It’s also being applied to help with the transfer and learning of so-called ‘soft skills’. For instance, an aged care worker might be able to mentor a colleague in conducting an argument with a dementia patient, presented as an avatar, to better prepare them for what is no doubt a very challenging scenario in real life.

3.   Augmented Reality 
Not to be confused with VR, AR (augmented reality) systems are designed to input information to real-world situations.  Instead of there being an avatar with the example above, you might imagine a motor mechanic remotely sending an apprentice audio and other data in real time to a headset that helps the learner learn a task or grasp a concept.

Apple’s imminent ‘AR Smart Glasses’ is being tipped as a potential game-changer for such interactions, whereby the user would be able to stream live video to their manager who would give instructions as well as information to help resolve a complex mechanical or other sort of problem.

4.   Artificial Intelligence 
Artificial intelligence (AI) is a broad term that refers to the ability of computers to apply human like intelligence to solving problems. Humans, when presented with variable data sets or information look to find connections to reveal patterns and concepts. AI is able to achieve this on a grand scale, sometimes yielding insights that may take even the smartest people months, years or longer to see.

5.   Machine Learning

Machine learning (ML) takes AI to another level whereby discoveries within data sets influence the behaviour of the algorithm. Put another way, if AI can find meaning in the data, ML uses that knowledge to make adjustments and implement informed queries of that data.

Take for instance a driverless-car. In wet weather, it will make certain calculations like a human would such as how it brakes and steers. In medicine and healthcare ML opens up new possibilities for identifying illnesses faster and understanding how to treat them on an individual, even cellular level.

It’s exciting to imagine the sorts of powerful learning applications that are possible as data engines become smarter and smarter.

The opportunities presented by AI and ML in learning are potentially enormous and are already appearing in the form of teaching systems that can crunch big data sets, revealing how individuals learn and then adjusting iteratively to develop more effective approaches.

Discover in our eBook about how these powerful digital technologies might be applied in helping your organisation better train and educate its most valuable assets.

By |2018-08-08T05:48:31+00:00June 20th, 2018|digital tools, eLearning, Learning, workplace learning|0 Comments

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