Darren Hockley , MD at DeltaNet International

We’ve come a long way since the early days of workplace e-learning. From the text-only prototypes of the 1980s, to the advent of multimedia capability in the ‘90s, and then mainstream internet, flash video, and HTML5 in the 2000s.

The demand for more innovative, relevant, and engaging workplace training has meant e-learning has continued to be disrupted and reimagined by technological advancements – a fact that’s almost certainly responsible for the medium’s longevity.

e-learning’s rise as the preferred training choice of many organisations today seems to fly in the face of its original sceptics – many of whom spoke out against its detraction from ‘human’ experience, or else called it ‘homogeneous’, suggesting it lacked the personal touch a real-life trainer could provide.

Whilst today there are many well-documented benefits of e-learning, the industry’s innovators have continued to take these issues seriously and address them in earnest. Design-techniques like immersive and scenario-led learning, e.g., were created to encourage critical thinking and problem-solving skills amongst digital learners.

The issue of personalisation also began to be addressed as Learning Management Systems (LMSs) evolved. Using pre-assessment tools, the systems could highlight gaps in knowledge and create personal development plans for each learner. Indeed, it was (and I believe, still is) this shift away from a ‘one-size-fits-all’ approach to workplace training that informed the intelligent e-learning of 2020 and beyond.


A New Learning Experience

Today’s Learning Platforms are very different from the ones used even a few years ago. One major difference being the incorporation of artificial intelligence and machine learning into their application – an innovation that was largely enabled by the Experience API, or xAPI.

xAPI revolutionised the way data is collected and analysed, allowing learning systems to build a much more comprehensive picture of organisational learning. One reason for this is that xAPI – unlike its predecessor, SCORM – is not limited to e-learning courses or an LMS. It can collect and aggregate data across multiple sources and track learning experiences wherever they take place, both on and off the learning platform.

Any learning activity users undertake (e.g. articles accessed on knowledge bases, queries submitted to helpdesks, documents shared on collaboration platforms, information input into performance management portals, quizzes taken and re-taken, online searches performed, and so on) is recorded as a statement and saved inside of a Learning Record Store (LRS) unique to each user. This data helps create comprehensive learning pathways for each employee – and it also helps to inform the learning design of the future.


Here are some of the ways AI is transforming corporate learning and development: 


There’s a reason many e-learning companies no longer refer to their learning platforms as a learning management system or ‘LMS’; the name doesn’t quite cut it anymore. These days you’re much more likely to hear about ‘learning experience platforms’ or LXPs.

LXPs mark a move away from formal, externally managed learning systems and concentrate instead on delivering a learning experience built around the user and their predisposition for learning.

Like LMSs before them, LXPs are built to deliver learning content, but they are also built to be able to learn themselves. This type of artificial intelligence is known as machine learning.

Driven by xAPI’s ability to aggregate data, today’s LXPs can track and respond-to user behaviour (i.e. what learning style they prefer, what they tend to search for, how long they spend learning, how many attempts it takes to pass, and etc.) and deliver content it infers meets our goals, interests, and preferences.

As you can imagine, this process creates highly personalised learning environments that are vastly different from the e-learning of yesteryear.


Learning in the Flow of Work

More sophisticated still, LXPs are being built to interrogate what users are working on and look for learning opportunities to keep the workflow on track. This is a development known as ‘learning in the flow of work’ and it is designed to support work, rather than distract from it.

Rather than stopping work to attend a seminar or sift through an hour-long course looking for vital information, LXPs will simply be able to suggest snippets of information/short videos as we work to help clear up areas of confusion – allowing employees to get on with the task at hand.

The same logic applies to the LXP’s ability to curate lengthier content if necessary. For example, if the system identifies a reoccurring knowledge gap. By pre-empting a learning requirement, the platform will be able to filter and curate content from multiple sources (e-learning course libraries, newspaper articles, journals – basically anything online) and create digital ‘textbooks’ made up of the type of learning content it knows we respond well to. These might be digestible study guides, videos, summaries, quizzes, podcasts, practice tests, gamified challenges, and so on.


Measure the Impact of Learning

Of course, no e-learning is perfect, and quality control is another area AI can help us out with. For instance, AI can explore the efficacy of learning content by analysing learner performance data.

It can, for example, identify instances where significant groups of learners have failed to answer a question correctly and interrogate their data to find commonalities amongst them. Perhaps they have all overlooked a specific course update or learning material that the LXP can then prioritise and promote to close the knowledge gap.

Alternatively, it’s possible the course content itself requires further attention from its developers and designers. The issue could be misleading or outdated information, or confusion over some instruction given in the course itself. Artificial intelligence expedites this investigation process and completes necessary data analysis without human bias or emotion impacting the results.

It’s in this way that I see AI complementing rather than replacing human experience when it comes to corporate L&D. In the future, I see AI redefining our understanding of personalised workplace training and envision it enabling e-learning suppliers to be more creative, more progressive, and – dare I say it – more human than ever before.


Darren Hockley is MD at DeltaNet International. The company specialises in creating engaging compliance and health and safety e-learning, and provides an intelligent learning platform, for businesses around the globe.

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