Distributed Learning & Prioritization: Learn (Step 3)

     

You can’t improve distributed learning experiences without first gaining important insights from captured data. In this post, we’ll explain the different questions and potential insights you might gain from various data sources.

Ask Questions, Get Insights

Knowing how to monitor and analyze your learning experiences is key to gaining useful insights from a data source. As you add more data sources, you should find even more insights, which might include discovering unexpected correlations across multiple data sources. Or, you might use data from one source to answer questions that arise from studying data from another source.

Click to download "Seven Steps Cheat Sheet."

Depending on the questions you ask and the data you collect, you might find insights like these:

  • People who are more active in one type of learning experience are more/less likely to be active in another.

  • Certain competencies are being developed more frequently via informal learning than other competencies.

  • Some people are learning about areas that are more relevant to other roles within the organization.

  • Certain learning experiences have positive, negative, or neutral effects on job performance.

  • Certain learning resources are popular or not used at all.

  • More learning experiences are recorded at certain times of the day or year.

Up Next: Acting on Your L&D Data

Now that you’re on your way to capturing and learning from your data, it’s time to start making adjustments to your learning programs. In our next Distributed Learning post, we’ll explain how to take an appropriate course of action depending on your insights.


L&D Evaluation Made Easy

Not sure where to start when it comes to capturing and evaluating data from your learning program? Download our Seven Step Learning Evaluation model, which is our "super method" of effectively evaluating your L&D process from design through implementation. It also combines the best parts of the Kirkpatrick, Kaufman, Anderson, and Brinkerhoff models.

Or, download our eBook, the Essentials of Learning Evaluation, for an in-depth look at different learning evaluation models and how to apply them.eGuide: Essentials of Learning Evaluation


About The Author

As one of the authors of xAPI, Andrew Downes has years of expertise in data-driven learning design. And, with a background in instructional design and development, he’s well versed in creating learning experiences and platforms in both corporate and academic environments.