There is a deep sense of where and how representation matters. Then there are less critical, but still important ways in which presentation counts. It includes talking about stereotypes, and calling out inappropriate labeling. Concepts matter, clarity matters, transparency matters. So here are two situations that are worth critiquing.

The first one that struck me this morning was an announcement. A researcher has created a petition asking Pew Research to stop using the ‘generations’ label. They’ve been using it in their research, and yet (as the petition points out) their own research shows it’s problematic.

Now this is a myth I called out in my last book  (specifically on the topic of problematic beliefs). There are several complaints, such as that the boundaries are arbitrary, and the stereotyping is harmful. While we can differ by age, discrepancies are better explained by experience than by ‘generation’.

Another problem came in an article I was connected to on LinkedIn. In it, they were making the case for micro learning. While there are great reasons to tout the benefits of small bits of timely content, they didn’t really distinguish the uses. Which is a problem, since the different uses require different designs.

Here’s where representation matters. Pew Research’s reputation, in my mind, has gone down. I used to fill out some surveys from them, and stopped because the assumptions in the categories they were using were problematic. Finding out that they’re a major proponent of generations only aggravates that. Can I really trust any results they cite when the foundations are flawed?

Similarly, the organization that’s touting micro learning solutions has just undermined any belief in their credibility to actually do this appropriately. When you tout stuff in ways that show you don’t understand the necessary principles, you damage your reputation. I’m not likely to want to use this firm to design my  solutions.

I push strongly for accuracy. This includes evidence-informed design, conceptual clarity, and transparency of motives. If you tout something, do so in a scrutable way. Marketing malarkey only muddies the water, and our industry has enough of a credibility problem.

Yes, there are more important ways representation matters: for kids to see themselves in culturally desirable roles, for voices to be heard. This is a less important aspect, but quality matters. Look at what you are saying, and ensure that it’s worth your audience’s time!

 Learning, I suggest, is action and reflection. (And instruction should be  designed action and  guided reflection.) What that action typically ends up being is some sort of exploration (aka experimentation). Thus, in my mind, exploration is a critical concept for learning. That makes it worth exploring exploration.

In learning, we must experiment (e.g. act) and observe and reflect on the outcomes. We learn to minimize surprise, but we also act to generate surprise. I stipulate that we do so when the costs of getting it wrong are low. That is, making learning  safe. So providing a safe sandbox for exploration is a support for learning. Similarly, have low consequences for mistakes generated through informal learning.

However, our explorations aren’t necessarily efficient nor effective. Empirically, we can make ineffective choices such as changing more than one variable at a time, or missing an area of exploration completely. For instruction, then, we need support. Many years ago, Wallace Feurzig argued for  guided exploration, as opposed to free search (the straw man used to discount constructivist approaches). So putting constraints on the task and/or the environment can support making exploration more effective.

Exploration also drives informal learning. Diversity on a team, properly managed, increases the likelihood of searching a broader space of solutions than otherwise. There are practices that increase the effectiveness of the search. Similarly, exploration should be focused on answering questions. We also want serendipity, but there should be guidelines that keep the consequences under control.

By making exploration safe and appropriately constrained, we can advance our understanding most rapidly, either helping some folks learn what others know, or advance what we all know. Exploration is a key to learning, and we need to understand it. Thus, we should also keep exploring exploration!

As I‘ve been developing online workshops, I‘ve been thinking more about the type of assessment I want. Previously, I made the case for gated submissions. Now I find another type of interaction I‘d like to have. So here‘s the case for model answers (and a rubric).

As context, many moons ago we developed a course on speaking to the media. This was based upon the excellent work of the principals of Media Skills, and was a case study in my  Engaging Learning book. They had been running a face to face course, and rather than write a book, they wondered if something else could be done. I was part of a new media consortium, and was partnered with an experienced CD ROM developer to create an asynchronous elearning course.  

Their workshop culminated in a live interview with a journalist. We couldn‘t do that, but we wanted to prepare people to succeed at that as an optional extra next step. Given that this is something people really fear (apocryphally more than death), we needed a good approximation. Along with a steady series of exercises going from recognizing a good media quote, and compiling one, we wanted learners to have to respond live. How could we do this?

Fortunately, our tech guy came up with the idea of a programmable answering machine. Through a series of menus, you would drill down to someone asking you a question, and then record an answer. We had two levels: one where you knew the questions in advance, and the final test was one where you‘d have a story and details, but you had to respond to unanticipated questions.  

This was good practice, but how to provide feedback? Ultimately, we allowed learners to record their answers, then listen to their answers and a model answer. What I‘d add now would be a rubric to compare your answer to the model answer, to support self-evaluation. (And, of course, we’d now do it digitally in the environment, not needing the machine.)

So that‘s what I‘m looking for again. I don‘t need verbal answers, but I do want free-form responses, not multiple-choice. I want learners to be able to self-generate their own thoughts. That‘s hard to auto-evaluate. Yes, we could do whatever the modern equivalent to Latent Semantic Analysis is, and train up a system to analyze and respond to their remarks. However, a) I‘m doing this on my own, and b) we underestimate, and underuse, the power of learners to self-evaluate.  

Thus, I‘m positing a two stage experience. First, there‘s a question that learners respond to. Ideally, paragraph size, though their response is likely to be longer than the model one; I tend to write densely (because I am). Then, they see their answer, a model answer, and a self-evaluation rubric.  

I‘ll suggest that there‘s a particular benefit to learners‘ self-evaluating. In the process (particularly with specific support in terms of a mnemonic or graphic model), learners can internalize the framework to guide their performance. Further, they can internalize using the framework and monitoring their application to become self-improving learners.

This is on top of providing the ability to respond in richer ways that picking an option out of those provided. It requires a freeform response, closer to what likely will be required after the learning experience. That‘s similar to what I‘m looking for from the gated response, but the latter expects peers and/or instructors to weigh in with feedback, where as here the learner is responsible for evaluating. That‘s a more complex task, but also very worthwhile if carefully scaffolded.  

Of course, it‘d also be ideal if an instructor is monitoring the response to look for any patterns, but that‘s outside the learners‘ response. So that‘s the case for model answers. So, what say you? And is that supported anywhere or in any way you know?

I was reflecting on a few things on terminology, buzzwords and branding in particular. And, as usual, learning out loud, here are my reflections.

The script:

So I’ve been known to take a bit of a blade to buzzwords (c.f. microlearning). And, I reckon there’s a distinction between vocabulary and hype. Further, I get the need for branding (and have been slack on my own part).  So, here I talk about buzzwords and branding.

First, vocabulary is important. I’m a stickler (I’m sure some would say pedantic ;) about conceptual clarity. We need to have clear language to distinguish between different concepts. (You shouldn’t say ‘cat’ when you mean ‘dog’, someone’s likely to get a wee bit confused!)

And, to be clear, there’s internal and external vocabulary. For instance, other people don’t really care about objectives, they just want outcomes. This internal vocabulary can be shortcuts, and help us minimize what we need to say to still communicate. Brevity is the soul of wit, after all.

And then there’s hype. The distinction, I reckon, is when we start tossing in buzzwords that are new, drawn from elsewhere, and promise great things. Adaptive and neuro- are two examples of buzzphrases that are open to interpretation but sound intriguing. Yet they require careful examination.

Then, there’s branding. You attach a label to something to identify it specifically. Harold Jarche’s Personal Knowledge Mastery (PKM), for instance, is a brand for a framework. So, too, would be Michael Allen’s SAM (Successive Approximation Model) and CCAF (Context-Challenge-Activity-Feedback). They’re ways to package up good ideas. And of course, t0 take ownership.

This latter step, I confess, I’ve failed on. The alignment in Engaging Learning and the different categories of mobile are two places I dropped the ball. I recently tried a brief attempt to remedy another, when I released the Performance Ecosystem Maturity Model.

I  do have the 4C’s of Mobile, but while that turns out to be useful, it’s not the most important characterization. In a conversation with someone the other day, he asked what I called the mobile framework I mentioned and he found useful. And I didn’t have an answer. I’ve talked about it before, but I didn’t label it. And yet it’s kind of the most important way to look at mobile! I use it as the organizing framework when I talk about mobile (really, the performance ecosystem):

• Augmenting formal learning
• Performance support (mobile’s natural niche)
• Social (more the informal)
• Contextual (mobile’s unique opportunity)

I wasn’t sure what to brand this, so for the moment it’s the Four Modes of mLearning (4M? 4MM?).

And for games, that alignment I mentioned I briefly termed the EEA: Effectiveness-Engagement Alignment. The point is that the elements that lead to effective education practice, and the ones that lead to engaging experiences, have a perfect alignment. It’s been a good basis for design for me. But, again, that labeling came more than a decade after the book first came out.

Ok, so I was counting on the ‘Quinnovation’ branding. And that’s worked, but it’s not quite enough to hang products on. So…I’m working on it. (And it may be that having ‘Learnlets’ separate from Quinnovation is another self-inflicted impediment!)

Still, I think it’s important to distinguish between buzzwords and branding. And they shouldn’t be the same (trademarking ‘microlearning’, anyone ;). Again, vocabulary is important, for clarity, not hype. And branding is good for attribution. But they’re not the same thing. Those are my thoughts, what are yours?