t’s a fact few companies would dispute that training and learning in the workplace has been slow to embrace the digital technologies now critical for driving success in most other parts of their business.
There are many reasons for this. But generally, what it boils down to is the lack of consideration business managers and executives give to how better education correlates directly with a competitive advantage.
And as we’ve explained in past blogs, the most important knowledge and skills in the workplace are the so-called ‘soft’ or ‘discrete’ skills. These include empathy, patience and being able to establish rapport.
Frustratingly for many companies, soft skills are often the hardest to convey. But it doesn’t need to be that way.
Today’s powerful, yet totally affordable, digital technologies such as smartphones, clever mobile and cloud-based apps, social media platforms and dramatically faster mobile networks have all served to level the playing field.
Today any organisation can harness the most cutting-edge technologies to ensure staff can absorb and retain more information faster while doing so in ways that are more engaging and fun.
Let’s take a look at the top five.
Mobile Devices and Apps
The technology trend having arguably the greatest impact on eLearning these days is the inexorable rise of mobile computing.
Coming back to soft skills, it’s a no brainer that allowing people to access information wherever they are, and via any mobile device, creates immediate opportunities for creating ‘real-world’, on-the job experiences. This is also known as ‘experiential’ learning.
As its name suggests, ‘experiential learning’ goes beyond merely acquiring skills and learning processes. It’s all about understanding brands, products and services, and the customers you hope will buy them on a far deeper level.
This flows on to better communications, engagement and ultimately more sales conversations.
Technologies like virtual reality (VR) and augmented reality (AR) are already disrupting the value proposition for learning and education.
With VR, for instance, a company could create a training module that can be delivered all over the country, or the world without needing to dispatch trainers along with it. Only the headset and perhaps some other portable equipment need make the journey.
VR also allows for the creation of interactive so-called ‘avatars’ to guide staff through training programs, including simulating real-world situations that might otherwise be hard to create in the field.
Related but by no means the same, AR could allow for instance a junior engineer working to solve a problem have their teacher transmitting instructions and other information remotely, which might appear via an interface such as digitally-enabled glasses. While Google Glass might not have set the world on fire, Apple is close to launching its ‘Apple Smart Glasses’ which are already creating a big buzz in the business world.
These technologies empower organisations to make eLearning an iterative, measurable process of customisation and improvement.
Originally born out of the US government, the ‘experience’ API, or xAPI, is one of the most disruptive technologies to intersect with the world of workplace training and education.
Developed specifically with education and training in mind, it’s an open programming standard for enabling better learner interaction and engagement. xAPI also lets any software application interface with a system that stores, analyses and reports on learning data. This could be a LRS (learning record store), a LMS (learning management system) or some similar information repository.
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.
But how do know whether what you’re doing is working, and how can you improve.
Machine learning 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 as it goes and then makes more informed queries of that data.
Think about medicine and healthcare. ML opens up new possibilities for identifying illnesses faster and understanding how to treat them on an individual, even cellular level.
Or think about a driverless, autonomous car, in wet weather, where it is able to make accurate calculations like – or better than – a human would such as how fast it travels, brakes and steers.
Workstar has helped some of Australia’s most successful companies develop effective digital eLearning strategies yielding genuine business improvement. Talk to one of our specialists today and find how to get onboard.