So, the conference was about what’s known in learning science. We had topics about the foundations, limitations, media, myths, informal/social, desirable difficulty, applications, and assessment/evaluation. What, however, comes next? Where do you go from a foundation in learning science?

My answer is to figure out what it means! There are lots of practices in L&D that are grounded in learning science, but go from there to application. My initial list looks like this:

1. Instructional design. Knowing the science is good, but how do you put it into a process?
2. Modalities. When you’re doing formal learning, you can still do it face to face, virtually, online, or blended. What are the tradeoffs, and when does each make sense?
3. Performance consulting. We know there are things where formal learning doesn’t make sense. We want gaps and root causes to determine the right intervention.
4. Performance support. If you determine job aids are the answer, how do you design, develop, and evaluate them? How do they interact with formal learning?
5. Innovation. This could (and should; editorial soapbox) be an area for L&D to contribute. What’s involved?
6. Diversity. While this is tied to innovation, it’s a worthy topic on its own. And I don’t just mean compliance.
7. Technology. There are lots of technologies, what are their learning affordances? XR, AI, the list goes on.
8. Ecosystem. How do you put the approaches together into a coherent solution for performance? If you don’t have an ‘all singing, all dancing’ solution, what’s the alternative?
9. Strategy. There’s a pretty clear vision of where you want to be. Then, there’s where you are now. How do you get from here to there?

I’m not saying this is the curriculum for a followup, I’m saying these are my first thoughts. This is what I think follows beyond learning science. There are obviously other ways we could and should go. These are my ideas, and I don’t assume they’re right. What do you think should be the followon? (Hint: this is likely what next year’s conference will be about. ;)

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In the particular instance, they provided training in particular areas. That is, folks would attend their courses and then, at least theoretically, be able to perform in new ways. Yet, they felt that folks didn’t necessarily sustain allegiance to them nor their offerings.

I asked what else they offered.  From the perspective of a performer, I’m not there to learn! Instead, I’m there to acquire new skills so I can perform better. And, if we take to heart what performance consulting has to say, there’re also resources such as job aids. These lead to success where learning isn’t even necessary. There’s more, too.

We can go further, of course. What about community? If you’re focused on a particular area of performance, would it make sense to be connected to others in the same endeavor? I’ll suggest that it’s likely. As folks develop in ability, they need to start interacting with others.

This organization wasn’t alone, of course. I’ve engaged with a number of organizations over the years that faced the same issue. (Whether they knew it or not.) In fact, I suspect it’s more prevalent that we agree. Particularly in this era of information available online, how do you generate a sustained relationship?

It seems to me that if we’re taking a higher perspective, we’ll realize that courses are just a component of a full development ecosystem. Of course, there are lots of issues involved: finding ways to curate or create all the elements, content management, platform choice and integration, and more. Still, this seems to me to be at least part of the answer. So, what am I missing?

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I dropped out of Learning 24 (in Dec) when the source of the commitment abandoned their support. I hadn’t intended to go, but they asked. Then owing to a management change, they reneged. And the conference understood.

I was committed to DevLearn, however, despite the same change in support circumstances. Not only did I have a session accepted, but I was going to do a book signing too.  Then I agreed to host a panel, and then to co-facilitate a workshop. I was excited and eager. It is my favorite face-to-face conference.

So, no worries. Until…I got Covid. The first time. I’ve had the vaccinations, and wore a mask on my travels. But this was bad: fever, sore throat, more. My voice sounds more like a croaking frog than human voice. And my voice is bad enough as it is!

Now, the CDC says that 24 hours after the fever’s passed, you’re ok as long as you take precautions: masking, distancing. However, I can’t really facilitate or moderate a panel without talking to folks. I can’t really be around folks without a mask when I’m eating. I’m going to a crowded place that doesn’t want you to stay in your room (no water boiler, microwave, or refrigerator in the room).

Not an easy decision. I really wanted to meet my commitments to the Guild, I love the event, and I could use the exposure (see management changes, above ;). On the other hand, I wouldn’t want anyone else to suffer like this hit me, and traveling where I’m around lots of folks just isn’t smart. I’m risking lots of other folks’ health. That’s not a good choice.

It might also preclude me from getting better, what with travel and being active. I’m being quite sessile, and isolating from my family. Not fun, but it’s right for them and me.

In the long run, I decided to not attend. It’s a sacrifice for me and the Guild, but at this time it’s the right thing to do. I may find out tomorrow or midweek that I could’ve been ok or at least attended the later things, but hindsight’s 20:20, as they say. At this point when I need to make decisions on travel and accommodation, the proper thing to do is to not expose the rest of you to this.

I’m not happy, but I am convinced I’m doing the right thing. And that’s better than the alternative. I won’t see you in Las Vegas, but you’ll survive, and most likely better than if I did. Safe travels, and if you’re there, have a great conference!  At least I should be online the week after for the Learning Science conference, Stay curious, my friends.

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I’m not going to ask this cold, of course. I’ve thought about it a bit myself, creating an initial framework (click on the image to see it larger). Ironically, considering my stance, it’s based around ADDIE. That’s because I believe the elements are right, just that it’s not a good basis for a design process. However, I do think we may need different tools for the stages of analysis, design, development, implementation, and evaluation, even if don’t invoke them in a waterfall process. I also have categories for overarching strategy, and for specific learning topics. These are spaces in which resources can reside.

There are also several different types of resources I’ve created categories for. One is an overview of the particular spaces I indicate above. Another are for information resources, that drill into a particular approach or more. These can be in any format: text or video typically. Because I’m weird for diagrams, I have them separately, but they’d likely be a type of info resource. Importantly, one is tools. Here I’m thinking performance support tools we use: templates, checklists, decision trees, lookup tables. These are the things I’m a bit focused on.

Of course, this is for evidence-based practices. There are plenty of extant frameworks that are convenient, and cited, but not well-grounded. I am looking for those tools you use to accomplish meaningful solutions to real problems that you trust. I’m looking for the ones you use. The ones that provide support for excellent execution. In addition to the things listed above, how about processes? Frameworks? Models? What enables you to be successful?

Obviously, but importantly, this isn”t done! That is, I put my first best thoughts out there, but I know that there’s much more. More will come to me (already has, I’ve already revised the diagram a couple of times), but I’m hoping more will come from you too. That includes the types of resources, spaces, as well as particular instances.

The goal is to think about the resources we have and use. I welcome you putting in, via comments on the blog or wherever you see this post, and let me know which ones you find to be essential to successful execution. I’d really like to know what L&D resources do we use. Please take a minute or two and weigh in with your top and essential tools. Thanks!

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Next week isn’t. Relevant to you, that is. I’ll be off for a couple of days guiding a client strategy. I was just supposed to do a keynote, but…when I heard it was a strategy session I offered to help facilitate it. That said, I do think we’ve created a good plan. Fingers crossed.

The week after that is DevLearn, arguably my favorite F2F L&D conference. I’ll be speaking at 3PM on Thursday, 7 November on achieving impact with your interventions. Then I’ll be signing books at 9:30 AM on Friday the 8th near the conference bookstore. I’m coming in for the full thing, arriving Tuesday and leaving Saturday, but it won’t be my usual visit. I’ll be around, saying hi to old friends and meeting new, of course. I’ll also be introducing a colleague new to L&D around.

Then, and this is exciting, I’ll be spending the subsequent week (11-15 November) either participating in or presenting in sessions for our Learning Science conference.  I’m doing a couple (informal/social learning, and making learning ‘stick’) of our curated sessions on my own. Then I’m doing one on myths with my LDA co-director, Matt Richter. The rest of the conference, as mentioned is great folks and important topics. Content’s up front, and no conflicting sessions when we discuss the topics live.

I’ll have a week after that to recover, and then of course Thanksgiving week. I hope to see you live around LV, or online the subsequent week. I’ll try to keep posting here once a week, but things may be a wee bit more random what with a busy few weeks until mid-November. By December, somewhat back to normal except of course the holidays. In the meantime, as I say to my family: be good, stay safe, and have fun!

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We have some of the most respected translators of learning science research to practice. Presenters are Ruth Clark, Paul Kirschner, Will Thalheimer, Patti Shank, Nidhi Sachdeva, as well as Matt Richter and myself. They’ll be providing a curated curriculum of sessions. These are admittedly some of our advisors to the Learning Development Accelerator, but that’s because they’ve reliably demonstrated the ability to do the research, and then to communicate the results of theirs and others’ work in terms of the implications for practice. They know what’s right and real, and make that clear.

The conference is a hybrid model; we present the necessary concepts asynchronously, starting later this month. Then from 11- 15 November, we’ll have live online sessions led by the presenters. These are at two different times to accommodate as much of the globe as we can! In these live sessions we’ll discuss the implications and workshop issues raised by attendees. We will record the sessions in case you can’t make it. I’ll note, however, that participating is a chance to get your particular questions answered! Of course, we’ll have discussion forums too.

We’ve worked hard to make this the most valuable grounding you can get, as we’ve deliberately chosen the topics that we think everyone needs to comprehend. I suggest there’s something there for everyone, regardless of level. We’re covering the research and implications around the foundations of learning, practices for design and evaluation, issues of emotion and motivation, barriers and myths, even informal and social learning. It’s the content you need to do right by your stakeholders.

Our intent is that you’ll leave equipped to be the evidence-based L&D practitioner our industry needs. I hope you’ll take advantage of this opportunity, and hope to see you at the Learning Science Conference 2024.

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A colleague of ours sent me an issue of a newsletter (it included the phrase ‘make it meaningful‘ ;). In it, the author was touting a four letter acronym-based model. And, to be fair, there was nothing wrong with what the model stipulated. Chunking, maintaining attention, elaboration, and emotion are all good things. What bothered me was that these elements weren’t sufficient! They covered important elements, but only some. If you just took this model’s advice, you’d have somewhat more memorable learning, but you’d fall short on the real potential impact. For instance, there wasn’t anything there about the importance of contextualized practice nor feedback. Nor models, for that matter!

I’m not allergic to n letter acronym models. For instance, I keep the coaster I was given for Michael Allen’s CCAF on my desk. (It’s a nice memento.) His Context-Challenge-Activity-Feedback model is pretty comprehensive for the elements that a practice has to have (not surprisingly). However, learning experiences need more than just practice, they need introductions, and models, and examples and closings as well as practice. And while the aforementioned elements are necessary, they’re not sufficient. Heck, Gagné talked about nine elements.

What I realize as I reflect is that I like models that have the appropriate amount of complexity for the level of description they’re talking about. Yet I’ve seen far too many models that are cute (some actually spell words) and include some important ideas but they’re not comprehensive for what they cover. The problem, of course, is that you need to understand enough to be able to separate the wheat from the chaff. I’ll suggest to look to vetted models, that are supported by folks who know, and there are criticisms and accolades to accompany them. Read the criticisms, and see if they’re valid. Otherwise, the model may be useful.

Ok, one other thing bothered me. This model supposedly has support from neuroscience. However, as I’ve expressed before, there have yet to be results that aren’t already made from cognitive science research. This, to me, is just marketing, with no real reason to include it except to try to make it more trendy and appealing. A warning sign, to me at least.

Look, designing for learners is complex. Good models help us handle this complexity well. Bad ones, however, can mislead us into only paying attention to particular bits and create insufficient solutions. When you’re looking at simple models and complex problems, you need to keep an eye out for help, but maybe it needs to be a jaundiced eye.

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The problem is that organizations have a structure that is largely to meet short-term needs. For instance, there are pressures to return short-term shareholder benefits, at least in publicly traded companies. Even private organizations are liable to want to reward the founder. There are few enough examples of folks that are taking a bigger perspective.

And, to be clear, I’m not denying the need for efficiencies. That’s a given. The issue instead, to me, is one of whether those efficiencies generate short-term returns, or instead will yield long-term benefits.

For example, when the pandemic hit, lots of orgs were struggling to find ways to continue operations when suddenly everyone had to stay remote. I argued that if you’re going through a digital transformation, you should start with an organizational transformation. My reasoning was that digitizing an old way of doing things was only going to be a short-term fix. What I saw was that this big upheaval was an opportunity for redesign. Not surprisingly, this wasn’t an effective pitch. People needed to fix things now! Yet, the orgs that survived the pandemic best were the ones that had a good culture to survive the enforced digital operation.

Similarly, I see many orgs focusing on ‘leadership development. That’s not a bad thing, mind you. Well, if you get past the Leadership BS (thought I’d written about this, but I can’t find it ;). Yet, most of what we see is expensive and highly interactive. Which sounds great, but it doesn’t scale. Our colleague JD Dillon is starting a book for frontline workers, which I laud. Yet there’s an intermediate level we’re guilty of neglecting. Again, a short term perspective.

Managers, data says, are the biggest reason people leave. Als0, most managers are promoted from the front line, and yet pretty much all of them are novices when it comes to management. Yet, our management training is idiosyncratic. More, our colleague Will Thalheimer recently suggested in an LDA event, that little in leadership development covers how to facilitate learning for your folks. Yet, hat’s one of the best things to help employees think their managers actually care for them (c.f. Self-Determination Theory). Moreover, there are so many managers that can benefit from training (and increasingly, leadership is viewed as something that needs to be present throughout the organization).

There are problems trying to deliver manager training at scale. We see demand, but it’s hard to deliver, particularly cost-effectively. Technology is part of the solution, but to make it work takes (wait for it) a long term perspective. These are only two examples, from the area of learning and development that I largely work and play in.  I’d argue that, for instance, the shift to a learning organization would be one of the best investments you could make. Well, for the long term ;). That’s the type of transformation that would be greatly augmented by a subsequent digital enablement. But without that initial refocus, the digitization will continue to support hierarchy, lack of transparency, and other factors that interfere with ongoing innovation and success.

I’d welcome hearing that most organizations are working on both the short- and long-term, but I’m skeptical. And more than willing to be wrong!  I’ll merely reiterate the point the late Jay Cross would make; investing in your people’s ability to learn is probably the best one you can make. In the tradeoff of short term thinking versus long term benefits, it seems obvious to me that playing the long game is the right way. That, at least, makes sense to me. What am I missing?

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To start, the notion is that it’s learning at the moment of need. Which sounds good. Yet, do we really need learning? The idea Jay pointed to in his book Informal Learning, was talking about Gloria Gery’s work on helping people in the moment. Which is good! But is it learning? Gloria was really talking about performance support, where we’re looking to overcome our cognitive limitations. In particular, memory, and putting the information into the world instead of in the head. Which isn’t learning! It’s valuable, and we don’t do it enough, but it’s not learning.

Why? Well, because learning requires action and reflection. The latter can just be thinking about the implications, or in Harold Jarche’s Personal Knowledge Mastery model, it’s about experimenting and representing. In formal learning, of course, it’s feedback. I’ve argued we could do that, by providing just a thin layer on top of our performance support. However, I’ve never seen same!  So,  you’re going to do, and then not learn. Okay, if it’s biologically primary (something we’re wired to learn, like speaking), you’re liable to pick it up over time, but if it’s biologically secondary (something we’ve created and aren’t tuned for, e.g. reading) I’d suggest it’s less likely. Again, performance is the goal. Though learning can be useful to support comprehending context and  making complex decisions, what we’re good at.

What is problematic is the notion of workflow and reflection in conjunction. Simply, if you’re reflecting, you’re by definition out of the workflow! You’re not performing, you’re stopping and thinking. Which is valuable, but not ‘flow’. Sure, I may be overly focused on workflow being in the ‘zone’, acting instead of thinking, but that, to me, is really the notion. Learning happens when you stop and contemplate and/or collaborate.

So, if you want to define workflow to include the reflection and thoughtful work, then there is such a thing. But I wonder if it’s more useful to separate out the reflection as things to value, facilitate, and develop. It’s not like we’re born with good reflection practices, or we wouldn’t need to do research on the value of concept mapping and sketch noting and how it’s better than highlighting. So being clear about the phases of work and how to do them best seems to me to be worthwhile.

Look, we should use performance support where we can. It’s typically cheaper and more effective than trying to put information into the head. We should also consider adding some learning content on top of performance support in times where people knowing why we’re doing it as much as what we should do is helpful. Learning should be used when it’s the best solution, of course. But we should be clear about what we’re doing.

I can see arguments why talking about workflow learning is good. It may be a way to get those not in our field to think about performance support. I can also see why it’s bad, leading us into the mistaken belief that we can learn while we do without breaking up our actions. I don’t have a definitive answer to “is workflow learning a myth” (so this would be an addition to the ‘misconceptions’ section of my myths book ;). What I think is important, however, is to unpack the concepts, so at least we’re clear about what learning is, about what workflow is, and when we should do either. Thoughts?

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What are the essential elements of feedback? Well, it should be on the performance, not the individual. It should be model-based, in that you should be using models to explain how to perform, showing examples of the model being used in context, and then asking the learner to use them. The feedback, then, uses the model to explain why what went right, or what went wrong. Also, it should be minimal other than that.

So, here I tried to show that the individual (or group, hmm) produces output. That output is evaluated by the model to ascertain correctness, or not. (Not the individual!) If the answer’s wrong, you say why, and then the right answer. If it’s right, you just reinforce the right answer.

Of course, this representation doesn’t convey the minimal aspect. It’s also not clear about using the model in the feedback. Still, so far it’s a representation I can talk to. So, this is my first stab at diagramming feedback. I welcome same!

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