Petra Peeters, Marlo Kengen and Ger Driesen
explore the power of personalisation in learning
Personalisation of learning is one of the hot topics in learning today. Organisations yearn for it. Vendors rave about the personalisation possibilities of their tools. While at the same time there seems to be a Babylonian confusion about what we mean by personalisation. To determine the pieces of the personalisation puzzle, we need to distinguish and describe several aspects of learning where personalisation can take place.
This will help you to do the following:
The definition of personalisation of learning will be: creating a unique learning experience on a personal level based on characteristics of the individual learner in a specific context.
Personalisation of learning content can be based on different triggers.
Job roles and performance requirements can trigger what kind of learning content is relevant for the learner. This can be based on mandatory compliance or certification training for the learner to prove skills to be licensed to operate. It can also be more open, based on explicit or implicit agreed knowledge and skills related to jobs or tasks. A check on how well a specific person compares to ‘the norm’ helps to personalise relevant content for each person.
A peer group, professional member or a professional association can trigger learning content by determining and sharing what they see as relevant and useful content. Think of LinkedIn suggesting specific content to you because “many other professionals with a profile like yours have taken course X or training Y”.
A ‘digital footprint’ can trigger content by tracking how a person behaves within a digital application. This can be within a digital learning application where the system tracks the learning process, progress and results of each individual learner. Based on that, it presents pushes or suggests the ideal next content topic to work on. But it could also be within any other digital application where tips and microlearning nuggets pop up when the system discovers that the user is struggling with the application.
The learner can choose what to learn based on interests or future ambitions.
Professionals might have very different reasons why they want or need to learn. There may be an actual performance issue to solve in a specific job task. In that case the concept of ‘five moments of needs’ developed by Bob Mosher and Conrad Gottfredson serves as a clear framework.
It shows a distinction between learning something new, more deeply or for application. Next are more specific circumstances when a problem occurs and there is a need to solve. And lastly, when something changes there is a need to re-learn and even unlearn.
Personalisation in this case is providing support to a specific person depending on the nature of need in a specific context. Think of using a new app. First there is a need to get acquainted with the app, then understand how it works and then apply it. Later, you may have to know how to solve a problem with your app, and you might have to relearn after installing a major update of the app. These five moments of need are usually based on a concrete, known job task with an established work process and is transactional by nature.
When current solutions don’t do the job (anymore) there’s a need for innovation. This means that learning is focused on finding new solutions or approaches. Personalisation in this situation can be focused on curation of new filtered content and insights that becomes available every day. An example might be using Google Alerts to automatically send news about new concepts and ideas every day.
“ Professionals differ in capabilities
and may need a different, personalised,
pace when learning. ”
There can be a need for reskilling to land in a different job or to learn a different profession because former skills are not relevant enough anymore. Think of Arnold Schwarzenegger as a movie star reinventing himself to become governor of California.
Although these jobs are very different, a personalised learning path can help to find what knowledge, skills and experiences from the previous job might be relevant in the future job and even how they might be helpful in creating the optimal learning path for a new job. Learning focused on innovation or deep reskilling are more transformational by nature.
For effective learning, not only content but also context is a very important element. In what kind of context does the learning take place? Or even more important, in what kind of context is learning supposed to be applied? We see three personalisation options here.
Based on the infrastructure of the location. Depending on the specific location in, for example, a hospital, on the railway or highway, or at a production line, some learning materials will be (most) relevant and others not. Easy access to the most relevant learning and performance support materials on a specific location can be a powerful way to personalisation. This can be done via a pull strategy; think of scanning QR codes at location or on equipment. Or it can be a push strategy, think of iBeacons pushing relevant content on a specific location. Ideal could be smart push with a system knowing what each individual needs at a specific location.
The next option is focused on the legal, cultural, language differences or even weather conditions of the geographical locations. For example, identical tasks might be simpler or more complex in different countries because of legislation.
Finally, those based on learning modalities, as the learner learns anytime, anywhere, either at work, during a commute or at home. It works best if the content is responsive so it can easily be approached via different devices such as PC, tablet or smartphone.
This aspect of personalisation focuses on options for professionals to tailor their learning into a personal blend. This personal blend can comprise various aspects. The professional may choose media and devices to switch between written content, video or audio, and work with this content on devices ranging from PC to smartphone, or even good old paper.
The professional can make choices regarding order to create – or to be offered – a flexible and personal learning path. The professional chooses – or is offered – a personalised set of interventions for a personalised learning journey, for example training sessions, e-learning modules, coaching, participating in a project, or joining a learning community.
Professionals differ in capabilities and therefore they may need or wish a different, thus personalised, pace when learning. These differences can be based on the professional’s knowledge level, education, their prior knowledge or their ambition. Some examples would be the professional determining their own pace within the content and across all content.
This can be achieved through online and offline programmes with little synchronous learning or where synchronous learning adapts by offering fast track, medium track or slow track options. Depending on prior knowledge and experience, possibly checked by in-learning tests or intelligence within the system, the learner only focuses on relevant elements and is not forced to learn things already known or mastered. Really smart systems offer adaptive learning where the system determines learning characteristics of the learner and offers content in a tailored pace, via tailored chunks and media to each learner.
The last piece of the personalisation puzzle considers personalising the degree of social activity when learning. A professional can make choices along the learning solo-social continuum, thus determining the degree of social learning, or learning with others. An example might be to become a certified assessor, professionals can choose to:
In addition, a professional can choose the amount of active participation within a particular social learning intervention, be it in a classroom training or in a social MOOC. A professional can choose with whom to learn: within a known peer-group or organisation or across borders and learn with professionals from other organisations or jobs.
For example, learn presentations skills by an in-house company programme or outside the organisation in an open group with participants from various organisations.
It’s clear by now that personalisation offers opportunities on quite a number of very different aspects. Building a sensible blend can be a puzzle. Perhaps even personalisation should be personalised. At one end of the continuum able, innovative experts are able to build their own personalised learning paths. On the other end we find learners with limited meta-cognitive skills and self-directedness necessary to build a smart personalised path.
Here, learning and development professionals play an important role, by serving as a smart coach who thinks along with the learners to achieve creative and fitting personal blends. The challenge is for all learners to find the most efficient and effective route to performance, using the growing number of personalisation possibilities.
This article has previously appeared in Training Journal on November 2019. Ger Driesen is Learning Innovation Leader at aNewSpring. Marlo Kengen and Petra Peeters are lecturers and advisers at HAN University of Applied Sciences.