Easy Tips to Enhance Self-Directed Learning

So, how do you support your learners’ initiative while also ensuring they get the resources they need? In this installment of our blended learning blog series, we’ll show you how to use your L&D data to enhance self-directed learning across your organization.

What is self-directed learning, and why is it important?

Self-directed learning describes when learners take the initiative to find resources and learn something for themselves. This includes using online resources—such as Google, Wikipedia, and YouTube, or resources selected from internally curated learning libraries—and offline resources—such as hardcopy publications, coworkers, or subject matter experts.

So, why is this type of learning important? Because, a large part of what people learn in the modern world isn’t from the 70:20:10 elements (i.e., formal, social, and on-the-job) as defined 20 years ago, but from the internet.

Support self-directed learning with content curation.

Dedicated spaces—either online or offline—for people to ask experts questions or share recommendations can be great for fostering self-directed learning. For example, create:

• an online forum for discussing topics, intranet pages for recommending resources, or a wiki page for sharing contact information for experts on different topics.
• a physical library, lunch-and-learn chats, or mentoring program.

Another example is using a learning experience platform (LXP), such as Degreed—which is designed to support self-directed learning. It brings together content from commercial content libraries and your in-house content library, plus content from the internet.

Many LXPs also include training content curation functionality. As a result, you can check that content for quality, accuracy, and relevancy to avoid negative learning and sharing unhelpful information with learners.

Use L&D data to refine and maintain your learning content.

Due to the vast amount of content choices paired with evolving practices and standards, keeping up with resources’ relevance and accuracy can be quite difficult. The good news is that you can use learning data to:

• Ensure the content you’re offering remains fresh and relevant.
• Determine gaps in learning content.
• Identify where learners want to develop a particular skill so you can provide the required training.
• Find scrap learning that’s not useful and taking up space—or worse, may actually be harmful (e.g., In a medical context, this is content that promotes old practices that are now considered dangerous. In a technology context, this is content that promotes using an insecure protocol. Or in a tax context, this is content that describes an old set of rules and allowances.).

For instance, your LXP’s search data is ideal for helping you to identify gaps in your content offering because it tells you what learners are looking for—not just what they are finding. You can compare popular search terms to what content is in your library, or examine searches that don’t lead to completions.

From there, you can identify the topics and skills that learners are looking for, but not finding, and then take action to fill those gaps. It’s likely that what learners want to learn will change over time, so continually reviewing search data helps keep your content offering timely and applicable.

When it comes to finding scrap learning, even basic content analytics can help. For instance, utilization data can tell you what content can potentially be dropped because people aren’t completing it or using it at all. Net promoter scores (NPS) and other rating data also can be helpful indicators for identifying ineffective content.

At a more advanced level, you can analyze the impact of content on knowledge, skills, and job performance to find content that is being used, but is not having the expected impact.

Basic metrics may or may not be available as built-in reports in your LXP. If they are not included (or if you just want more advanced analytics), you’ll need a learning analytics tool that incorporates data from other sources—such as NPS surveys and performance assessment systems.

See how to support self-directed learning during a crisis.

At times of crisis, data becomes especially important, as learners may suddenly need new skills and knowledge as a reaction to the crisis. L&D needs to be able to respond quickly in order to support the business to respond quickly to the crisis themselves.

In our panel webinar How Caterpillar, CHRISTUS Health & PwC Use Learning Analytics during Crisis, L&D experts explain how they used data to stay ahead of shifts in demand for content at the start of the pandemic crisis.

Up Next: How to Prevent Negative Learning

All learning is good, right? Find out in our next post, as we discuss how you can use data to pinpoint and manage negative learning within your organization.