I regularly rant about the quality of the learning designs we see. Knowledge dump and information test, I rail, is not going to lead to meaningful outcomes. Consequently, I work to promote more learning science in what we do. However, I have to acknowledge that frequently, the problem isn’t in the designer, but in the requester. Too often, there are RFPs (emblematic, they’re equivalent to the internal request for ‘a course on X’) that are asking for designers to take content and essentially put it up on the screen with a quiz (and window dressing). So we need better RFPs, please.

Ideally, RFPs would be expecting a good process. That includes a number of steps, from analysis through to deliver. For instance, to expect due diligence in analysis, with either clear metrics of success, or expectations of an appropriate process. That latter would include where appropriate individuals (experts, supervisors, performers) work with the team to identify ideal performance, gaps, and the causes.

Similarly in design, there’d be an expectation of iterative development and review, with testing. Where’s the expectation of meaningful practice, where the lowest level of practice is mini-scenarios (better written multiple choice questions) through full scenarios, to even serious games? We need identification of misconceptions and specific feedback as well.

Yet, the RFPs that come out often focus on cost, visual design, and an expectation that PPTs and PDFs are a sufficient basis to build a course. I recently suffered through a droned presentation of bullet points and unclear diagrams, followed by quiz questions that a) focused on random knowledge that wasn’t emphasized during the presentation and b) provided as feedback only ‘right’ or ‘wrong’. Let me assure you that little meaningful learning came from that experience.

While we need to push ourselves to be better, we also need to educate our clients (internal or external). They need to educate themselves, too. Orgs will get the courses they ask for. However, will the ask have any impact? Too often, unfortunately, the answer is no. There’s a quote in the article The Great Training Robbery that estimates suggest only 10% of the multi-billions spent on training has any impact. That’s a staggering loss. While there are many contributors, it behooves us to try to address them all. For one, can we have better RFPs, please?

It’s easy to believe that if we build solutions according to the principles, what we build will work. Certainly, that’s the case in many instances. But not, I suggest, when we’re talking about solutions for people? Why do we need to test and tune? Because we’re complex.

Materials, such as wood and steel have predictable properties. When you build a deck, you can follow the building codes for what you need to do for fixing posts to the ground, etc. However, people aren’t quite that predictable.

There’s a case to be made that the brain is the most complex thing in the known universe. In fact, we don’t fully know how it works! Thinking, then, that we can achieve a reliable change in the brain with simple mechanisms is kind of naive. We have to understand how the brain works, first, and then for complex changes, we need some detailed analysis and careful specification. However, we’re not done.

Once we’ve built it, we need to test and tune! Any solution isn’t guaranteed to be optimal or even effective, at least initially. Since people are complex, we can’t just design for the average (c.f. Todd Rose’s The End of Average). We can’t follow waterfall models, despite how appealing it is. Assuming we can is a path to boring and ineffective solutions. “If we build it, it is good” isn’t a useful assumption.

You see this in the best approaches. Michael Allen’s Successive Approximation (SAM), Megan Torrance’s Lot Like Agile Management Approach (LLAMA), David Merrill’s Pebble in the Pond, or Guy Wallace’s PACT approach (I’m not even going to try to deal with that acronym) all have iteration as a fundamental component.

You need some metrics, of course. You test against them, and then tune to get closer. The answer to “when do we stop iterating” is not “when we run out of time and money”. If you’re running out of time and money faster than you’re getting to your metrics, you need to explicitly consider some alternatives, like relaxing your goals, or investing more, or (horrors) abandoning where you’ve at. But it’s better to do it consciously!

To do this, we need to build ‘test and tune’ into our practices. We need to allocate time and money to it. Does this mean things will take longer and cost more? Possibly. The tradeoff is that we should be doing less courses overall, once we’re asking questions, and our solutions will be more effective. Going beyond knowledge dump courses that achieve no organizational benefit? I think that’s a fair exchange. I hope you do, too.

Time for an update, as things have been happening, Some over the past year, some more recently. So here’s what’s new at Quinnovation.

So, as I’ve already noted, I was asked to join the Learning Development Accelerator last fall as Editor in Chief of the new LDA Press. That means, practically, serving as both acquisition and development editor. So far, I’m better in the latter than the former. We did publish our first, book, er, mine ;). I’ve also joined as co-0rganizer.

We’re doing some fun things with that. The first is the You Oughta Know series of Wed webinars, introducing people, well, that you oughta know. We’ve had an amazing run of guests. I’ll also be starting up a series of Very Opinionated Tech Takes. Yeah, it’s me going off on various techs, but I will be unpacking my thinking behind the takes. And I have had a number of decades of experience at it… Finally, there’s the forthcoming Learning & Development Conference, where we’re looking to do what we think should be done. That is, a focus on important specifics; we’ve two tracks, one more for beginners and one more advanced. Attendees can choose. We’ve got a good tight faculty, and are expecting a great development experience.

In addition to my LDA duties, I’m still continuing on with Quinovation, of course. That has meant some steady client work since the beginning of the year; including two projects on learning and performance strategy. One is likely to be continuing at least a little while longer. From that one is a topic I’ll be discussing as part of at DevLearn. I’ll also be running a ‘Make It Meaningful workshop there; a full day digging into the principles and tricks of making experiences emotionally engaging. (I’ll also be part of a panel of the Guild Masters.)

I’ve also taken on some other roles via Quinnovation. For one, I’ve been working with an initiative attempting to take K12 STEM into the 21st Century. Yes, there are plenty of efforts in this area, I just happen to be involved in this one that has an approach I’m getting to shape aligned with my perspectives. I’m also now on the advisory board of a startup with a platform for augmenting formal learning programs. Finally, I’ve signed on to assist an established elearning firm improve their approach as part of a growth initiative. All are focusing on applying learning science to make bigger and better impacts. Those are the types of things I can comfortably get behind.

So that’s what’s new at Quinnovation. Reckon I’ll be busier than the proverbial beaver, but that’s preferable to the alternative. Stay tuned!

A colleague mentioned me in calling out a post that was touting a myth. Which is bad enough, but as I’ve done before, I looked deeper at the post, and found more problems. It’s worth breaking down the problems, both to sensitize you to the potential problems, and provide some guidance about what’s right. So here’s a cautionary tale.

First, the post was promoting Dale’s Cone (referred to in the post as the Learning Retention Pyramid). You’ve probably seen it, saying people retain X% if they listen to a lecture, Y% if they read, … all the way to Z% if they teach others. It’s been resoundingly debunked. It is made up, Dale never added numbers, etc. So, we’re starting off on the wrong foot.

The post points to an article by an organization. As I’m wont to do, I went to the article. Not surprisingly, it wasn’t any better. It talked about the importance of looking at retention practice. That is, designing for retention; a good thing. Along with a definition were nine strategies for promoting this desirable feature. Which is where we start to go wrong.

There’s nothing wrong with an aggregation of strategies, but it helps if there’s any reason to believe this is a full and complete list, and maybe oriented by biggest impact. No, this appeared to have no rationale other than just a collection. Please, please, provide the rationale for any such collection!

Then, the very first one immediately jumped into an example that “generation Z’ would process. Ok, we’re onto myth number 2. Generations. Isn’t. A. Thing! Sigh, can we please stop thinking in terms of limiting categories.

Moreover, much of the recommendations seemed focusing on remembering information, not on applying it. Only one, “apply learning to the real world” talked at all about actually doing things. A side note: by and large, recalling information isn’t going to lead to meaningful behavior change.

Aside from some minor grammatical errors and odd statements (what does “large muscular people are dump” mean?), this seems like a random collection. It’s not that the strategies are wrong, but they’re unjustified, badly presented, and unfocused. To me, this is a cautionary tale. I would actively steer away from an org that used such marketing to promote its understanding of learning. (For the record, there’s no attribution to authorship, and though the original poster on LinkedIn was identified, they don’t appear in the ‘About’ page of the org.) Caveat emptor.