First, we hope that microlearning as a buzzphrase disappears. We’d prefer folks think about performance support as a solution, and spaced learning as a different solution, both with their unique opportunities and rationales. At one level, of course, you’re talking about the same thing: the contextually-relevant delivery of a small amount of content. In one, however, the context is what people are doing, and there aren’t entailments between elements of the content. In the other, the context is about time and there are definite entailments. We don’t yet know of a platform that elegantly does both.
Beyond that, as has been famously attributed to various individuals: “It is difficult to make predictions, especially about the future.” As such, we prefer to suggest what we’d like to see. Here is our wish list.
For one, we’d like better tools. While there are context-sensitive support platforms and learning spacing approaches, none are quite ideal. For instance, we’d like easy cross-platform delivery, including not only across desktop and mobile, but across email, text, and other communication channels. We’d also like the ability to be able to specify contexts for push instead of pull. You can make content available as a ‘pull’ request (e.g. a QR code) where they’re asking for help. However, it may be more useful at times to push for help to someone who may not even be aware of the opportunity. This includes having the ability to create schedules for delivery, or pattern-driven engines that are smart about delivery.
Further, we’d like standards. Proprietary approaches are understandable from the vendor’s perspective, certainly. However, from a user perspective, we prefer to have the ability to swap systems without having to translate content or start from scratch. This includes interoperable data outputs. We’d like to tailor the data we receive to answer the questions we have. We don’t want others to provide what they think is important.
The above suggests we need a broader understanding of microlearning and what it takes to make it work in each situation. Which suggests a need for ongoing research. We need data and then theories about how to do it best. For one, how do we make good decisions about spacing? For another, what sorts of performance support map to particular needs? Much is currently grounded in observation, but empirical validation would be helpful.
The component parts of microlearning provide real opportunities. We also run the risk of losing our way with these approaches. What will help us is making sure we know what we’re doing, and have to tools to do it well. With that, microlearning has a future, and that’s what we hope to see.
Discover the true potential of microlearning with our in-depth eBook, ‘Microlearning: It’s Not What You Think It Is.’ Gain valuable insights and learn about the future of performance support and spaced learning. Download now and explore the possibilities. If you have any questions or would like to discuss microlearning further with our team of experts, feel free to reach out to us at firstname.lastname@example.org. We look forward to hearing from you!