Personalisation has become an expectation, and it’s not just about cookie-laden webpages. Manufacturers like Dell primed us for this with bespoke PCs long before the internet properly let mass customisation loose into every interaction, whether social, civil, or commercial. Marketers, especially the scared ones from traditional businesses, understood: Levi Strauss’ online tailored jeans were an early example of pioneering mass customisation that seems quaint compared to the refinements that enrich even the most banal of purchases today.
Our now compulsive appetite for individualisation is nowhere higher than in digital experiences, where the bespoke and highly personalised is an expectation. This expectation is not necessarily bought but certainly sponsored by the wanton abandonment of personal data that we relinquish to the datasets, registries and algorithms that make it work.
Now that every product and service we encounter has made personalisation so routine, it’s hardly unsettling to hear about the hidden costs. For a Google computer on one side of the world to personalise my search for something on another, a complex digital cognition is triggered by even the most absent-minded moment of digital curiosity. This apparently consumes so much cooling energy to perform that data centres are being moved to the Arctic (Facebook, 2013) and underwater (Microsoft, 2016).
The search engine aspect of personalisation alone has made the world’s most valuable company also one of its biggest computer hardware manufacturers. Gartner Group already listed Google as the world’s fourth largest ten years ago. At the time, it was also the fifth biggest customer of AMD processor chipsets, but now it makes these itself, as well as its own servers. So, there is apparently infinite value in being able to understand individual requests for information, however trivial or niche, and instantly respond with something relevant. Retail activity aside, we also all know that a good portion of these super-cooled searches are for results that improve knowledge, competencies and skills.
There’s something about data
All of the above is effectively about pull, sucking in a vortex of data and applying intelligent personalisation. Being visible and instantly reachable to anyone initially driven by their own or their employer’s motivation, such as the need to be trained, gives you the opportunity to pull them through to something pertinent to their need and opportune for yours. Implicit is an anticipation of effective personalisation, as artificially intelligent as you can afford to muster, in reciprocity for them deigning to engage at all. With attention universally deficit, you don’t have long and they won’t wait in line. The term attention economy has already been coined.
It is here that instructional design is presented with an opportunity to engage a learner with an experience they can believe is personally relevant and a good use of their time. There is a receptiveness to effective training that will convert into improved behaviours, and the return on investment this can fuel, by employing personalisation and mass customisation in elearning design.
To pull, entice or drag people into online training and through to new skills and competencies is easier if the quality and benefits of the digital learning experiences chime with their more habitual and self-motivated ones. Since that universally includes a personalised mix of the social, simulated, gamified, augmented and increasingly virtualised; instructional designers are confronted with some dauntingly high user experience benchmarks. Games, online retail environments, social networking and even office productivity software are unrelentingly refining user engagement, at a pace that long cycles of training development are not typically resourced to match.
Clients are increasingly noting the paucity of their digital experience at work, especially the training, compared to at home and at leisure. Keeping them engaged with the presented content becomes an instructional design challenge. The expectations that consumers, and so learners too, bring to this engagement, experience and reward are merciless. Nonetheless, learning technologies are responding with design and social networking-inspired treatment of learner data. Combined with increasing facility of integrating online learning with other collaboration channels and workflows, standardisation like xAPI that improves the handling and sharing of learning data enables intrinsically social and personal learning experiences. And since instructional design can use learner data in real time, like an instructor in a classroom might, this can exceed the personalisation of search because the delivered content can continue to evaluate the user’s need and adapt to it during the learning, which a search engine won’t.
So, a streamlined experience needs to pervade not just the locating of personalised content but also the harvesting of skills and competencies offered within it. To get online learning content to resonate with the emotional and socialised states that engender behavioural change, instructional designers are personalising courses with the ambition and refinement of social marketing maestros. We can now mass customise learning experiences. This extends dramatically beyond just filtering suitable courses for a self-expressed or organisationally defined profile. After all, Google has a button for that and there are better ones coming. Adaptive learning experiences can attain improved practice far richer than an interaction around what size and colour you want or like or should like. Using plausibly realistic scenarios in which the content adjusts responsively to learners’ progress dramatically improves and shortens their route to appropriate new knowledge and behaviours.
To do this immersively requires sustained personalisation and customisation both throughout the learning management and HR information systems, as well as within the course content itself. Socialising learning catalogues already structured around competencies and roles with user reviews, leader boards and ratings is now pretty standard fare. More bespoke and intelligent platforms offer algorithm-driven personalised pathways and playlists that can be easily broadcast by one user to others, providing an adaptive learning environment and deeply individualised experience attuned to business productivity outcomes.
A personalised and socialised journey through branching scenarios simulating real world systems and behaviours can be scaffolded with scored games, polling, forums and supplemental features of informal enhancement such as virtualised coaching and peer participation. We know these techniques can dramatically improve real world practice when intelligently applied. Personal and reflective insights on decisions made within such simulations, further informed by embedded psychometric tools, can support practice transfer with diagnostic takeaways relevant to validated typing of an individual, their understanding of themselves and how to pull this training further through to the goal of best practice.
It’s simulated, personalised and socialised interactions with virtual peers and stakeholders that are being used with measurable effectiveness to deliver improved learning in first aid, medicine, transport and many other fields. The personalised approach is agnostic to any sector because we’re hardwired to respond to it, and we’ve yet to even glimpse the learning foothills of virtual and augmented reality. But perhaps not for too long.
Learning Performance Consultant
James has extensive experience in the design and delivery of elearning programmes, especially in accredited environments, built up through international programme and account director roles supported by an MBA and Prince2 project management training. His digital learning technology skills cover a broad spectrum of authoring and publishing environments, and he combines these with project management and business development skills.