How to Deliver Personalized Learning

By Kathryn Nixon

Personalized learning has become a bit of a buzzword in L&D, but with the right approach it can deliver learning that’s tailored to your learners’ needs. In this blog post, we explore several misconceptions around personalized learning and effective approaches you can use to deliver learning journeys that really work.

What Is Personalized Learning (Really)?

Depending on who you ask about personalized learning, you might hear something like, “It’s adding a role filter so learners only get what they need.” Or perhaps, “It means my team will only create the minimum content required.”

Personalized learning also can get misconstrued as delivering the bare minimum that learners need in as short a time as possible. And microlearning is often caught up in this perception because it splits a learning course into smaller “chunks,” which enables it to be delivered based on specific criteria.

But personalized learning is really about giving your learners their own learning journeys in a meaningful, thoughtful way.

This means:

  • Delivering learning that gives people what they need right now to do their jobs effectively, based not just on their roles but on other factors, such as confidence and competence.
  • Designing effective blended learning journeys that give learners the flexibility to create their own learning paths and empower them to pursue self-directed learning.

This means:

  • Delivering learning that gives people what they need right now to do their jobs effectively, based not just on their roles but on other factors, such as confidence and competence.
  • Designing effective blended learning journeys that give learners the flexibility to create their own learning paths and empower them to pursue self-directed learning.

How to Deliver Truly Effective Personalized Learning

So what should you be thinking about to deliver personalized learning journeys? First, as mentioned earlier, reframe the idea of personalization away from being purely role-based. True personalization could, for instance, consider a learner’s:

  • Competencies
  • Needs
  • Confidence levels
  • Attitude

This requires a thoughtful approach to design upfront, but when implemented correctly it delivers a far more effective learning experience that actually feels individually tailored.

Second, think about microlearning as discrete components. Learning that is meaningful, not just small. Microlearning is effective when it delivers the right type of learning for the right context. That might be an array of different components packaged in a way that empowers your learners to choose what they need.

Three Examples of Effective Personalized Learning

Here are three quick examples that demonstrate a considered approach to giving learners their own learning journeys.

1) Pre-Learning Diagnostics

Use a diagnostic to deliver a tailored learning program by asking learners to complete a series of Likert scale questions on their confidence levels, attitudes, and working practices.

Based on the answers they submit, learners then receive a tailored “menu” of learning comprising a variety of different components. This can display learning by subject area, or even by priority, depending on how a learner has answered the diagnostic.

2) Microlearning Components

The following diagram shows the vast array of different learning components we created for one learning program. This was a large-scale, long-running program, so don’t be put off by the sheer volume and variety outlined here.

Some of these components formed a core element of the program, while others supported it. Part of the design of the program was to ‘pull’ learners in and empower them to learn in their own way, asynchronously. The sheer variety of different formats and channels made this possible, with learners given access to what they required in any given moment.

This is a good example of how to empower learners to define their own learning journeys by delivering an array of discrete components, designed to support self-directed learning.

This diagram shows the types of learning journeys, including eLearning formats, live learning, collaborative online learning and user-generated content

3) Information Design

Strong information design underpins the last example. When you’re considering giving learners the freedom to define their own learning journeys, conduct a discovery phase that enables you to understand what it is that people need and the best way to deliver that training content to them.

This includes not only understanding what learning is already out there in the business that can be leveraged, but also supplementing that material with pieces of new content. Then think about how to present and curate that information in a way that makes it easy for learners to search and find that content.

Adaptive Learning: Data-Fueled, Highly-Personalized Learning

The examples we’ve described above are based on taking a design approach upfront that supports personalization. But another, more data-led approach, can enable the delivery of tailored learning in a different way.

Adaptive learning uses data to adjust the path, pace, and content of a learning program according to the learner’s needs. This adaptation occurs while the learner is completing the learning, rather than at the start.

Adaptive learning can harness data from learning activity as well as behaviors, interactions, and external activities that may take place outside of it. This enables L&D teams to gain a detailed understanding of learner performance and then deliver highly-personalized learning that targets individual strengths and weaknesses.

This type of approach is greatly enhanced by the use of xAPI technology, which enables the collection of data on a wide range of learning activities. This data can then be used to plot a learner’s activity and progress against other known factors—such as the learning and behaviors associated with evidenced successful learners, and adapt the learning journey accordingly.

Adaptive learning is potentially the future of personalized learning as the use of data analytics becomes more widespread in L&D—so it’s worth thinking about how you can start getting to grips with learner data so you can start taking this approach to personalized learning.

Automation for a Personalized Learning Experience

Use Personalized Learning Designer (PLD) to create tailored experiences. PLD automates actions—like sending messages, following up with course materials based on learners’ results, enrolling students in another course, and more!

LEARN MORE

A version of this blog post originally appeared on LEO Learning.

Find out more

Open LMS provides world-class LMS solutions that empower organizations to meet education and workplace learning needs .