3 Easy Ways to Enhance Self-Directed Learning with L&D Data

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 rule elements (i.e., formal, social, and on-the-job) as defined 20 years ago, but from the internet.

What are examples of self directed learning?

Examples of self-directed learning in professional or corporate contexts include:

• Online courses and webinars. Take online courses and webinars to gain expertise in a particular subject or skill. Learners can choose courses relevant to their job responsibilities and interests and learn at their own pace.
• Professional networking. Connect with peers within a specific industry to learn from their experiences and insights. Networking examples include:
  • participating in professional associations and groups,
  • attending conferences and events, and
  • joining online forums and social media groups (e.g. a LinkedIn group).
• Reading and research. Read books, articles, and research papers to learn about topics, whether they're online or offline resources.
• Mentoring and coaching. Seek out mentors or coaches who can offer professional support and guidance. Learners can identify areas where they need help and work with a mentor or coach to set goals and develop an improvement plan.
• Project-based learning. Participate in project-based learning to gain hands-on experience, develop new skills, and work with various departments.

What are the benefits of self directed learning?

Self-directed learning offers several advantages for people looking to enhance their knowledge and skills:

• Flexibility. People can learn at their own pace and on their own schedules. They have the freedom to choose when and where they want to learn, which is particularly beneficial for those with hectic schedules or other commitments.
• Customization. Tailor learning experience to specific needs and interests. Learners can focus on the areas they want to improve or explore new topics that align with their goals, making the learning experience more relevant and engaging.
• Autonomy. Self-directed learning puts individuals in control of their own learning journey. They can take ownership of their learning process, set goals, and monitor their progress.
• Collaboration. Self-directed learning doesn't mean learning in isolation. People can still collaborate with peers, mentors, or experts in the field through networking, online forums, or group projects. And, in turn, this collaboration facilitates knowledge sharing, feedback, and valuable insights from others in the same industry or with similar interests.
• Continuous improvement. Learners can continuously update their skills and knowledge while developing a mindset for lifelong learning.

Support self-directed learning with training 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.

Remember, self-directed learning allows learners to take ownership of their learning and development outside traditional training programs. It offers benefits such as flexibility, customization, and collaboration.

By taking the initiative, diagnosing learning needs, and choosing strategies that work best for them, learners can enhance their professional growth and stay competitive.

Up Next: All learning is good, right?

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.