Micro-learning: trend, fad or retred?
In terms of online learning, the chunk became the ‘Learning Object’. That goes back to 1994, allegedly to Wayne Hodgins. To be fair, the debate back then was quite sophisticated, as it did focus on discoverability and interoperability. These remain important concepts in online learning, as they require standards. That is why the concept of a 'learning object' was enshrined in IEEE standards and taken up by IMS and ADL.
Reusable Learning Objects
Then, in the early 2000s, the RLO (Reusable Learning Object) was fashionable. There was no end of talk about these digestible bits of learning that could be reused in courses. This was the basis of the awful SCORM standard, still in use today. The debate then was about recombining reusable learning objects in different courses, like Lego. There’s even a literature on the classification of such objects (Churchill 2007). This died a slow, and sometimes painful death, as it never really worked but we were left with the clumsy and inappropriate SCORM standard, David Wiley is just one of many who looked at this in detail in his paper The Reusability Paradox.
Masie became an adherent of nano learning, taking things to new depths of smallness, with ‘nano’ learning. I’m not sure that he ever understood that nano means 10-9 but it seemed, at that point, to be moving towards a meaningless arms race to see how minuscule learning could get, without much else of a theoretical framework. At this point the micro-learning things was more of a bandwagon than anything of substance.
This is another popular term for Micro-learning, championed by the metaphoric school of learning. Lost count of the times I’ve seen the word used in online learning marketing brochures but like the ‘tapas’ theory of Blended Learning, it is for those who rank words over analysis. This is rather like the debate around Blended learning, which got stuck in muddled metaphors around recipes, cocktails, blenders and so on. When 'Blended learning' and now 'Micro-learning' remain in the world of metaphor, they remain banal platitudes.
The ‘chunks of learning’ concept now pops up nearly every year, as if it were something new. This past year it has been rebadged as 'Micro-learning'. I suppose Micro is a bit larger than Nano (in fact it means 10-6) maybe close to a nugget, a bit smaller than a chunk. The term seems to centre around the idea that learning is related to YouTube videos, Tweets, infographics etc. I’m not against this, just against the lazy thinking that surrounds it.
The bottom line is that there is absolutely nothing new in this, apart from the usual failure to define how small is small and the implications for practice. In the debates I see, there is little detail on its actual definition. How does it actually relate to working memory? How are they combined? How can they lead to deep learning? Does chunking also refer to how things are stored and retrieved from long-term memory? How can we use it in searchable systems? What about interoperability?
What to do?
What’s needed is not some superficial branding, and yet another term for 'chunking' invented for ‘trend’ blogs and conference talks, but a more detailed analysis around its use and potential. As you can see above, we’ve been using and discussing the concept for 60 years and have chewed through a considerable amount of analysis and actual practice. To take just one example, the reusability of learning objects, RLAs, nuggets and micro-learning has a long history, largely resulting in its shortcomings. There have been endless attempts to build learning object repositories through expensive LCMSs. The online learning world world is littered with these failures.
Beyond just a description
To take Micro-learning beyond the simple platitude, that is ‘small’, it strikes me that there are several useful applications for what people are calling Micro-learning:
1. Social media – the idea that Tweets, Facebook and Blogs provide different but focused pieces of learning that play to the cognitive rules of attention.
2. AI (adaptive) learning, where networks of learning objects have to be created with meaningful definitions of dependencies, so that personalised learning can be delivered.
3. Chunked content – this is being used in semantic systems, such as WildFire, that automatically chunk content, on the fly, to increase attention and ultimately retention.4. Spaced practice – where chunks are cleverly tagged, interleaved and delivered to maximise reinforcement and retention
If anything, micro-learning has focused on a general observation about small, episodic pieces of learning, driven by mobile, Twitter, YouTube etc. That’s fine. I buy that. Indeed, within the context of adaptive systems, defined by networks of learning objects, there are real attempts to use the idea, as there are in spaced-practice tools. But rather then resurrect a ‘fad’, more accurately one in a series of ‘retreds’, we need some real analysis on what it actually means. To be honest, if this is the great trend for 2016 in learning, we’ve branded ourselves as a profession that simply forgets its past and is too lazy to define its future.