So far in this series, we’ve looked mainly at categories and complexities within the learning analytics maturity model. This week, we’ll look at learning analytics from another angle: What sort of learning activities are organizations collecting and analyzing data about? Join us, as we explain more and highlight several interesting finds along the way.
And it's eLearning for the win!
Our Learning Analytics Research Study showed that most report views are related to e-learning, mixed digital content, or instructor-led training—with the majority of report views relating to e-learning.
The same pattern is seen for the number of reports created, as shown in this chart:
This isn’t especially surprising because eLearning and digital content are the bread and butter of a modern L&D department. And, collecting data about these types of learning experiences is generally easier than collecting data from instructor-led training.
That’s because digital content often has built-in tracking features, while ILT happens in the real world and requires manual tracking efforts.
What’s more interesting is the wide array of learning experience types, as it shows you can track and report on just about any learning experience. Most of these learning experiences are self-explanatory, but we've chosen seven experience types to examine in more detail.
1) Mixed Digital Content
Because several reports cover multiple experience types, categorizing them from an experience-type perspective was difficult. So, we categorized them into one the following:
- Mixed digital content. This is for collections of eLearning, video, and files.
- Mixed blended learning. This includes digital and face-to-face training.
- Mixed learning and performance data. This is for reports combining learning and business data.
In most instances of mixed experience types, clients grouped data together as overall records of learning experiences taking place. Sometimes, however, we saw clients explicitly mix data about different learning experiences for comparison.
Other reports did not have related experiences (e.g., reports looking at the total number of people in a group). These reports were fairly uncommon.
3) Observation & Simulation
We also saw organizations tracking observations and simulations.
These learning experiences don’t have to be technically complex. You can easily collect data about real or simulated job tasks through human observation.
Simply record task progress and success on a mobile device using a checklist app. For example, simulating resuscitation of a dummy patient as pictured.
Video is an increasingly important type of learning experience in the L&D team’s tool kit. So, it’s not surprising we saw a number of reports looking at data about video content.
Because of the kind of data generated from watching videos (i.e., pause positions, sections watched, etc.), reports looking into video interactions are relatively specialized. And, as training video analytics become more popular, we may start seeing the emergence of specifically designed visualizations for video.
5) Platform & Search
When we talk to people about learning data and reporting on learning, their first thoughts are normally around data from learning content; but, we can actually capture a lot of useful data from the learning platforms housing that content.
This data can be used to analyze learner journeys through the platform and improve how easily they can reach their intended destinations.
In particular, search data is an important aspect to track on learning platforms. It tells you what people are looking for and what they’re finding, so you can ensure you have appropriate content on the platform and that it can be found via search.
A number of organizations are analyzing data from surveys as part of their learning analytics. Not only can survey data be a source of learner ratings as a Level 1 satisfaction metric, but also a great source of qualitative data as we discussed in our post about the Advanced Evaluation Complexity.
7) Watershed LRS
And, finally, we found a number of reports that tracked the usage of Watershed.
As you’ve seen from the insights in this series, there’s a lot to learn about how people are consuming learning analytics—which you can use to help inform your own reports and analytics.
Chances are, there’s untracked learning happening somewhere in your organization. If you don’t think you can track it, think again. Remember, we’ve seen organizations tracking all kinds of learning experiences—so, if they can track them, you can too!
Up Next: Report Types
We’ve looked at how people are analyzing learning data. We’ve looked at the kinds of learning experiences they are reporting on. Next, we’ll explore the last piece of the puzzle and look at the kinds of report types and visualizations being used.
About the author
As a co-author of xAPI, Andrew has been instrumental in revolutionizing the way we approach data-driven learning design. With his extensive background in instructional design and development, he’s an expert in crafting engaging learning experiences and a master at building robust learning platforms in both corporate and academic environments. Andrew’s journey began with a simple belief: learning should be meaningful, measurable, and, most importantly, enjoyable. This belief has led him to work with some of the industry’s most innovative organizations and thought leaders, helping them unlock the true potential of their learning strategies. Andrew has also shared his insights at conferences and workshops across the globe, empowering others to harness the power of data in their own learning initiatives.
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