Attention is a complex phenomena. Thinking that we can simply address is probably naive. Worse, there is at least one pervasive myth about it. Trivial attention is probably overrated, but meaningful attention is underrated.

Attention, I’ll suggest, is how we pay conscious awareness to our thinking. We pay attention to the sensory stream that’s available, and as working memory is has limits, our attention chooses what ends up being in working memory (which is where we see conscious thought). This is the picture I paint in Learning Science for Instructional Designers,  my recent book on how we learn. That’s how I learned it in grad school, and little seemed to change that.

As an aside, I suggest that the basic human information processing loop is something that is critical to understand. This is true for learning designers, but I would suggest there’s broader applicability. Knowing how information flows:

• from sensory store to working memory via attention
• from working memory to long term memory via elaboration
• back to working memory via retrieval
• and to decision from working memory

as a simplified story, shows how humans work in many ways. It gets more complex in important ways, but this is a key basis. On top of it comes aspects of how we think, and learn, but this is the core.  It benefits anyone dealing with people, basically: UI, marketing, etc. In short, most everyone.

Recent pictures of the information processing loop suggest, however, that attention has a bigger purview. They have it influencing most of the above. Which may be more accurate, in that if you need to attend to what’s in working memory, and manage the process of attending to information while evaluating what decision to make. You must maintain conscious focus on what you want to learn.

The myth, which still persists, is that our attention span has dropped to 8 seconds. Which folks tout as less than that of a goldfish. (How do we know what the attention span of a goldfish is?) The origin of this myth came from StatBrain misinterpreting a study, and was amplified since it was published by Microsoft Canada.  Marketing, mind you, not their research group! A myth I busted in a previous book!

There is apparently some evidence that our attention span has dropped (to 4o-something seconds, not eight), but we can still disappear into movies, novels, and games for hours. I reckon it’s about how engaging it is. Which, not completely surprisingly, is the topic of my most recent book, Make It Meaningful.

So, please, avoid the myths, and learn the core. Attention is underrated, as is the whole human information processing loop. Learn it, and benefit.

I just saw another of these ‘n things you must…if you…’ headlines, and as usual it had the opposite effect they intended. I guess I’m a contrarian, because such headlines to me are an immediate warning. It happened to be in an area I know about, and I hadn’t done any of the necessary things. Yet, I have done the thing they were saying needed the prerequisites. Arguably well (do awards count?). It made me reflect on how we’re hyping the news. Some thoughts…

Yes, I know that such headlines are clickbait. ‘n‘ should be small. Yet when I tried to boil down Upside’s ‘deeper learning’ list for an infographic, it came to 14 items.  Inconvenient for hype,  I’m afraid, but what I’d put in the white paper. Of course there’s more, but I’m trying to be comprehensive, not ‘attractive’.  Similarly, when I created my EEA alignment, I had nine elements. Not because they were convenient for marketing, but because that’s what emerged from the work.

I similarly see lists for ‘the five things’, or the ‘8 things’ (somehow 8 seems to be a maximum, at least for marketing ;). What worries me about these lists is if they’re comprehensive. Is that really all? Have you ensured that they’re necessary and sufficient? Did you even have a process? It took four of us working through months to come up with the eight elements of the Serious eLearning Manifesto.  None of the above lists (Manifesto, EEA, deeper learning) are definitive, but they are the result of substantial work and thinking. Not just pulled together for a marketing push.

There are good lists, don’t get me wrong. Ones where people have worked to try to identify critical elements, or good choices based upon principled grounds. Typically, if it’s the case, there are pointers to the basis for these claims. Either there’s someone who’s known for work in the area, or they’re transparent about process. However, there are also lists where it’s clear someone’s just pulled together some random bits. Look for inconsistency, mismatches of types, etc.

In the broader picture, it’s clear that generating fear and outrage and sensationalism sell. I just want to demonstrate a resistance, and prefer a clear argument over a rant. (Here I’m trying to do the former, not the latter. ;) This goes with probably my broader prescription: I do want policy wonks making decisions. I really don’t want simple wrong answers to complicated questions no matter how appealing.

So, my short take is if you know the area, read with a critical eye. If you don’t, look for warning signs, and see what those who do know have to say about it. Caveat emptor. That’s my take on trying to stay immune to the hyping of news.

Many years ago, I led the learning design of an online course on speaking to the media. It was way ahead of the times in a business sense; people weren’t paying for online learning. Still, there were some clever design factors in it. I’ve lifted one to new purposes, but also have a thought about how it could be improved. So here are some thoughts on learners as learning evaluators.

The challenge is the result of two conflicting challenges. For one, we want to support free answers on the part of learners. This is for situations where there’s more than one way to respond. For example a code solution, or a proposed social response. The other is the desire for auto-marking, that is independent asynchronous learning. While it’s ideal to have an instructor in the loop to provide feedback, the asynchronous part means that’s hard to arrange. We could try to have an intelligent programmed response (c.f. artificial intelligence), but those can be difficult to develop and costly. Is there another solution?

One alternative, occasionally seen, is to have the learner evaluate their response. There are positive benefits to this, as it gets learners to become self-evaluators. One of the mechanisms to support this is to provide a model answer to compare to the learners’ own response. We did this in that long-ago project, where learners could speak their response to a question, then listen to theirs and a model response.

There are some constraints on doing this; learners have to be able to see (or hear) their response in conjunction with the model response. I’ve seen circumstances where learners respond to complex questions and get the answer, but they don’t have a basis to compare. That is, they don’t get to see their own response, and the response was complex enough not to be completely remembered. One particular instance of this is in multiple response choices where you pick a collection out.

I want to go further, however. I don’t assume that learners will be able to effectively compare their response to the model response. At least, initially. As they gain expertise, they should, but early on they may not have the requisite support. You can annotate the model answer with the underlying thinking, but there’s another option.

I’m considering the value of having an extra rubric that states what you should notice about the model answer and prompts you to see if you have all the elements. I’m suggesting that this extra support, while it might add some cognitive load to the process, also reduces the load by supporting attention to the important aspects. Also, this is scaffolding that can be gradually removed, allowing learners to internalize the thinking.

I think we can have learners as learning evaluators, if we support the process appropriately. We shouldn’t assume that ability, at least initially, but we can support it. I’m not aware of research on this, though I certainly don’t doubt it. If you do know of some, please do point me to it! If you don’t, please conduct it! :D Seriously, I welcome your thoughts, comments, issues, etc.