The Ripple Effect: Learning & Data Ecosystems

Once you’ve identified the learning ecosystems across your different learning programs, it’s time to explore how changes to various elements of an ecosystem can impact learning experiences and other parts of the ecosystem. This blog post will show how one change can impact your learning and data ecosystems.

A small change to a learning ecosystem can have significant impacts.

We know ecosystems, both ecological and technological, are comprised of an array of many interconnected entities that have varied impacts on each other. Another critical component of an ecosystem is that it’s constantly evolving—and when you introduce a new element, it can have massive, unforeseen impacts.

In the context of a learning ecosystem, we’ve seen this scenario play out in various ways. A typical example is introducing a slick, new technology platform into the learning ecosystem. We all strive to provide the most effective and impactful learning, so it makes sense to be attracted to the latest, exciting technologies that promise to help us meet these goals.

Let’s say you introduce a new video management portal into your learning ecosystem. Eventually, you may use it beyond its primary purpose of improving digital learning experiences and communication. So, how does this branched use of the tool impact the rest of your ecosystem?

Well, consider your video delivery options. You might have a few different options outside the video management portal itself. For instance, can you embed videos in other ecosystem entities, such as your LMS courseware or an existing app or microsite?

Hopefully, you can; but if that’s the case, you might have unintended consequences such as random access, incorrect tagging, limited tracking options, and more.

Are there gaps in your data ecosystem?

How might these unintended consequences impact the data ecosystem? For example, videos aren’t often standalone learning objects.

Instead, they’re typically part of a more comprehensive course, curriculum, or learning path. And when these paths span different entities across the learning ecosystem, you risk creating gaps in your data ecosystem, making determining learners’ progress difficult.

Some organizations solve this challenge by exporting endless CSV files from different systems. Then, they painstakingly merge these files into a consolidated data set to show learners’ usage and activity across the entire learning ecosystem.

Alternatively, an easier and more efficient solution is using a learning record store (LRS) to help mitigate potential risks to the data ecosystem. An LRS, which sits behind the systems in a learning ecosystem, saves time and effort by collecting data about all the learning happening in the organization to provide a holistic view of data across the ecosystem.

Learn in the flow of work.

So far, we've focused on how changes to your learning ecosystem might affect your data. But, can changes to a data ecosystem impact the learning ecosystem, too?

As Mike Rustici explained in an earlier post, a data ecosystem is the subset of systems that generate both learning and performance data and the systems storing that data. And L&D needs both learning and performance data to measure impact.

There’s a growing emphasis on learning in the flow of work—which resembles and builds on other concepts, such as just-in-time training and performance support, in that learning becomes part of an essential and existing workflow. In this case, the lines blur between where learning occurs and where the usual business process occurs.

Take a sales training program as an example:

If the L&D team creates a fantastic inventory of just-in-time product training and education on a mobile platform, the team likely can use that content as a sales enablement tool. The learning experiences become part of the workflow as sales agents facilitate customer conversations using the same content they used to educate themselves.

The data describing these experiences has value and is desired by:

  • the learning team to understand how people use and benefit from the content, and
  • the business to better understand customer experiences.

That’s why a flexible data collection and dissemination strategy—for instance, collecting data using a specification such as xAPI and a storage mechanism such as an LRS—is essential for enabling that exchange of information.

Up Next: Thinking strategically about your learning ecosystem

Now that you understand how changing elements in a learning ecosystem can impact both learning experiences and the ecosystem as a whole, it's time to think strategically when it comes to creating a "big picture" about your learning ecosystem. Join us next time as we explore how learning ecosystems interact with other business systems across the organization.

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