So far, we’ve established an overview of modern learning ecosystems and how you can identify them across your different learning programs. Now, it’s time to explore how changes to different elements of an ecosystem can impact not only learning experiences, but also other elements in the ecosystem.
One small change can have far-reaching impact.
We know ecosystems, both ecological and technological, are comprised of an array of many interconnected entities that have varied impacts on each other. Another key component of an ecosystem is that it’s always evolving—and when a new element is introduced, it can have massive, unforeseen impacts.
In the context of a learning ecosystem, we’ve seen this scenario play out in a variety of ways. A common example is the introduction of 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. So, let’s say you introduce a new video management portal into your learning ecosystem. Eventually, you may use it beyond its main purpose of improving digital learning experiences and communication. 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 existing 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 unplanned access, incorrect tagging, limited tracking options, and more.
Are there gaps in your data ecosystem?
How might the data ecosystem be impacted as a result of these unintended consequences? For example, videos aren’t often standalone learning objects. Rather, 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—which makes determining learners’ progress difficult.
Some organizations solve this challenge by exporting endless CSV files from different systems. From there, these files are painstakingly merged 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.
Recommended Resource: Use this interactive eBook to see how Watershed and Kaltura use xAPI to seamlessly add a new video portal to your 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 the 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 as well as 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 start to 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, it’s likely that content might also be used as a sales enablement tool. The learning experiences become part of the flow of work, 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 both the learning team to understand how people use and benefit from content, but also by 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 key to 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. In the meantime, sign up for Watershed Insights to have blog posts delivered right to your inbox.
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