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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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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Many moons ago, I co-wrote a paper on evaluating social media impacts. There are the usual metrics, like ‘engagement’. That is, are people using the system? Of course, for companies charging for their platform, this could be as infrequent as a person accessing it once a month. More practically, however, it should be a person hitting it at least several times a week, or even several times a day! If you’re communicating, cooperating, and collaborating, you really should be interacting at a fair frequency.

I, on the other hand, argued for more detailed implications. If you’re putting it into a sales team, you should expect not only messages, but more success on sales, shorter sales cycles, etc. So you can get more detailed. These days, you can do even more, and have the system actually tag what the messages are about and count them. You can go deeper.

Which is what I think is the answer here. What skills do you want? For an innovation demo with Upside Learning, I argued we should break it down. That includes how to work out loud, and how to provide feedback, and how to run group meetings. (I’m just reading Alex Edman’s May Contain Lies, and it contains a lot of details about how to consider data and evidence.) We can look for more granular evidence. Even for skills like team dynamics, you should be looking at what makes good dynamics. So, things like making it safe yet accountable, providing feedback on behavior not on the person, valuing diversity, etc. There should be specific skills you want to develop, and assess. These, then, become the skills you design your learning to accomplish. You are, basically, creating a curriculum of the various skills that comprise the aggregated topic.

It may be that you assess a priori, and discover that only some are missing in your teams. That upfront analysis should happen regardless, but is too infrequent. The interlocutor here also mentioned the audience complaining about the time for analysis. Yep, that’s a problem. Reckon you have to sell the whole package: analyzing, designing, and evaluating for impact on performance, not just some improvement. Yet, compared to throwing money away? Seems like targeting intervention efforts should be a logical sell. If only we lived in a rational world, eh?

Still, overall, I think that these broad programs break down into specific skills that can be targeted and developed. And, we should. Let’s not get away with vague intentions, explanations, and consequently no outcomes. Let’s do the work, break it down, and develop actual skills. That, at least, is my take, I welcome hearing yours!

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My first book, Engaging Learning came from the fact that a) I’d designed and developed a lot of learning games, and b) had been an academic and reflected and written on the principles and process. Thus, it made sense to write it. Plus, a) I was an independent and it seemed like a good idea, and b) the publisher wanted one (the time was right). In it, I laid out some principles for learning, engagement, and the intersection. Then I laid out a systematic process, and closed with some thoughts on the future. Like all my books, I tried to focus on the cognitive principles and not the technology (which was then and continues to change rapidly). It went out of print, but I got the rights back and have rereleased it (with a new cover) for cheap on Amazon.

I wanted to write what became my fourth book as the next screed. However, my publisher wanted a book on mobile (market timing). Basically, they said I could do the next one if I did this first. I had been involved in mlearning courtesy of Judy Brown and David Metcalfe, but I thought they should write it. Judy declined, and David reminded me that he had written one. Still I and my publisher thought there was room for a different perspective, and I wrote Designing mLearning. I recognized that the way we use mobile doesn’t mesh well with ‘courses on a phone’, and instead framed several categories of how we could use them. I reckon those categories are still relevant as ways to think about technology!  Again, republished by me.

Before I could get to the next book, I was asked by one of their other brands if I could write a mobile book for higher education. The original promise was that it’d be just a rewrite of the previous, and we allocated a month. Hah! I did deliver a manuscript, but asked them not to publish it. We agreed to try again, and The Mobile Academy was the result. It looks at different ways mobile can augment university actions, with supporting the classroom as only one facet. This too was out of print but I’ve republished.

Finally, I could write the book I thought the industry needed, Revolutionize Learning & Development. Inspired by Marc Rosenberg’s Beyond eLearning and Jay Cross’s Informal Learning, this book synthesizes a performance and technology-enabled push for an ecosystem perspective. It may have been ahead of its time, but it’s still in print. More importantly, I believe it’s still relevant and even more pressing! Other books have complemented the message, but I still think it’s worth a read. Ok, so I’m biased, but I still hear good feedback ;). My editor suggested ATD as a co-publisher, and I was impressed with their work on marketing (long story).

Based upon the successes of those books (I like to believe), and an obvious need in our field, ATD asked for a book on the myths that plague our industry. Here I thought Will Thalheimer, having started the Debunkers Club, would be a better choice. He, however, declined, thinking it probably wasn’t a good business decision (which is likely true; not much call for keynotes or consulting on myths). So, I researched and wrote Millennials, Goldfish & Other Training Misconceptions. In it, I talked about 16 myths (disproved beliefs), 5 superstitions (things folks won’t admit to but emerge anyways) and 16 misconceptions (love/hate things). For each, I tried to lay out the appeal and the reality. I suggest what to do instead, for the bad practices. For the misconceptions, I try to identify when they make sense.  In all cases I didn’t put down exhaustive references, but instead the most indicative. ATD did a great job with the book design, having an artist take my intro comic ideas for each and illustrating them, and making a memorable cover. (They even submitted it to a design competition, where it came close to winning!)

After the success of that tome, ATD came back and wanted a book on learning science. They’d previously asked me to edit the definitive tome, and while it was appealing, I didn’t want to herd cats. Despite their assurances, I declined. This, however, could be my own simple digest, so I agreed. Thus, Learning Science for Instructional Designers emerged. There are other books with different approaches that are good, but I do think I’ve managed to make salient the critical points from learning science that impact our designs. Frankly, I think it goes beyond instructional designers (really, parents, teachers, relatives, mentors and coaches, even yourself are designing instruction), but they convinced me to stick with the title.

Now, I view Learning Experience Design as the elegant integration of learning science with engagement. My learning science book, along with others, does a good job of laying out the first part. But I felt that, other than game design books (including mine!), there wasn’t enough on the engagement side. So, I wanted a complement to that last book (though it can augment others). I wrote Make It Meaningful as that complement. In it, I resurrected the framework from my first book, but use it to go across learning design. (Really, games are just good practice, but there are other elements). I also updated my thinking since then, talking about both the initial hook and maintaining engagement through to the end. I present both principles and practical tips, and talk about the impact on your standard learning elements. In an addition I think is important, I also talk about how to take your usual design process, and incorporate the necessary steps to create experiences, not just instruction. I do want you to create transformational experiences!

So, that’s where I’m at. You can see my recommended readings here (which likely needs an update.) Some times people ask “what’s your next book”, and my true answer at this point is “I don’t know.”  Suggestions? Something that I’m qualified to write about, that there’s not already enough out about, and it’s a pressing need? I welcome your thoughts!

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The classic model is the ‘ropes course’. Folks have to work together to get everyone safely across some challenge. By working together to achieve success, you should build team cohesion and respect the different capabilities of your colleagues. Yet, investigations suggest that what’s learned doesn’t carry back to the workplace. People who got along, when they get back to the workplace, can be surprised and disappointed that the same conflicts exist.

What’s happening, of course, is context-specificity. The resulting benefits worked in the context of the team-building, but it’s not the same context as work. Just like the ‘brain training’ exercises didn’t transfer to other tasks, so to any learning is likely to dissipate quickly and still not transfer to another context. What do we need to do, then, to generate retention over time and support transfer to the workplace as well?

For one, we need more than one practice. I just read the results of interesting research suggesting two stages of memory. The first stage says initial memories can last briefly, but for sustained retention, you need a second stage of retrieval practice. Yes, we should know that, but too often we don’t practice it! (Which also suggests that a test at the end of a learning event may not be a good indicator!) Also, I’ll suggest, if we want appropriate transfer, we have to engineer it.

How do you engineer transfer? I’ll posit two steps. For one, you need experience across several different contexts. So, do task A together, then B which is widely different, then C, which is different again. You could do a task that requires different physical attributes (tall, small, strong, heavy), and then one that requires different creative approaches (art, music, prose). Along the way, you reinforce a particular team approach that works across contexts. You facilitate reflection, as well, on what’s common.

Matt went further, suggesting that then you need to take that facilitation back to the workplace, and I’ll agree that it’d be ideal. If you then brought the models back to the workplace and facilitated their application to situations at work, you could extend the internalization and appropriate re-contextualization of the learning.

One-shot events are unlikely to generate the sustained transfer you need, at least not without specific design and support. If you’re not trying to achieve retention (over time after the event until needed) and transfer (to all appropriate and no inappropriate) situations, why bother? If you do want retention and transfer (and you should), design for it. Specifically engineer to support retention and transfer. Use spaced repetition with increased challenge to achieve the former. Use contextual variance and reflection facilitation to support the latter. When you do, you’ll have outcomes worth the investment.

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So, I’ve been a bit concerned about the rabid interest in generative AI. Not that I think it’s inherently bad, despite its flaws. Instead, my concern is the uses it’s put to. If you think about the classic engineering proposition – cheap, fast, or good; pick 2 – you know you can apply AI to any of the areas. Always, however, it seems that the focus is on cheap and fast. Which concerns me. There’s substantial evidence that our L&D efforts aren’t having an impact. Thus, doing bad faster and cheaper is still bad!

Part of this, it seemed to me, to stem from a rabid focus on short-term returns. I read The Japan That Can Say No many moons ago, and became convinced that a purely financial focus isn’t in the long-term interests of organizations. Now, there’re reinforcement!

First, in Australian news was a report about how a famous economist was rethinking the role of economics. While I didn’t agree with all of it, one aspect that resonated was captured in these bits:

“…we have largely stopped thinking about ethics and about what constitutes human well-being. We are technocrats who focus on efficiency…We often equate well-being with money or consumption, missing much of what matters to people.”

The juxtaposition happened with this quote aggregated by Learnnovators and posted to LinkedIn:

” The early signals of what A.I. can do should compel us to think differently about ourselves as a species. …Those skills are ones we all possess and can improve, yet they have never been properly valued in our economy or prioritized in our education and training…”
– Aneesh Raman, VP, Workforce Expert at LinkedIn & Maria Flynn, President & CEO of Jobs for the Future (JFF)

The overlap, to me, has to do with the undervaluing of what humans bring to the economic table. Efficiency isn’t the only good. Pushing L&D to do ‘box ticking’ learning design faster and cheaper isn’t consonant with recognizing what gives our work meaning. Besides undervaluing what learning design could and should be, it’s disrespectful to the learners and the organization.

I think that what’s driving organizations should be how they contribute to society as a whole. The means to that end is creating an internal environment conducive to supporting people, individually and collectively, to contribute their best in ways that respect what we offer. There are things technology can do that, frankly, we as people shouldn’t. Similarly, there are things we can do that we shouldn’t abrogate. To paraphrase the meme, I don’t want people doing menial tasks leaving the creativity to machines.

A holistic synergy, each doing what they do best to augment the other, alone and together, is optimal. Our economics should support that as well, and to the extent our structures don’t, it may be time to rethink them. Otherwise, it’s a misplaced organizational focus. Thoughts?

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There are, of course, lots of good reasons. For one, the privileges I’ve had haven’t been shared. Folks often come from less opportune backgrounds than others have had the advantage of. Moreover, such advantage hasn’t been accounted for before they get to work. Unfortunately, schools and social welfare haven’t adequately addressed this We have racism, and misogyny, and other forms of discrimination to deal with. ‘Us against them’ isn’t a healthy perspective. However, perhaps you wonder, why should organizations be a source of remedy?

My argument it pretty simple, really. Research says that we get better results when we have diversity in looking for solutions. There’s a pretty simple explanation why, too. What we’re doing, when looking for answers (research, design, trouble-shooting) is searching a potential solution space. It’s easy to not explore thoroughly. I’ve talked about brainstorming, for instance, as something we can do badly or well. That’s about process. But there’s more.

Garvin, Edmondson, & Gino wrote about learning organization dimensions, and one of the four aspects of a supportive learning environment was “appreciation of differences”. I want to emphasize it’s not ‘tolerating diversity’, it’s valuing it! In exploring that space of solutions, the more diversity in the group, the more likely we are to cover a big range. (There’re caveats, of course, particularly that all have to share a commitment to finding an answer.) Homogeneity is the enemy here!

Of course, this means equity in treatment, and inclusion. If you’re excluding people, you’re not taking advantage of diversity. If you’re not promoting equity, the injustices perpetuate. The only good way to get people to feel good about diversity if it is equitable and inclusive.

Interestingly, one of the hosts mentioned that there’s separate evidence of value. This was something I hadn’t heard. Apparently, having more diversity in the room makes people more diverse in their thinking. That is, even before getting people to generate ideas, people’s attitudes are more diverse because of the observed variety. I haven’t been able to confirm this, but I have no reason not to believe it, and it’s an interesting (and valuable) result.

Now, as said, there are lots of good reasons. But one that is very pragmatic is that you get better solutions when different viewpoints are incorporated. We should be looking at complementary and varied viewpoints. That involves bringing different people together that have something to offer, and just being different is one! Celebrate that!

So, that’s why DEI in my mind; done right, the outcome is better!  Overall, we fare better when we work in the ways that align with how our brains operate. That’s alone and together. Let’s do the best for us and our organizations.

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The article starts with a suite of evidence. I know I’m mighty lucky to have been born as a white male in California, had both parents, was able to secure a really good education, and more. The data says that all these things are boons to the likelihood of success. There were also all sorts of weird variations (including middle initials contributes to success?).

Further, the article reports on how two researchers ran some simulations. They had characters with varying degrees of ‘talent’, and then also some good and bad luck. What happened, of course, is that the folks with a combination of luck and ‘talent’, did best. Talent alone didn’t do it, nor luck. In fact, the most talented didn’t succeed the most. “The most successful agents tended to be those who were only slightly above average in talent but with a lot of luck in their lives.”

The research goes further. It’s typical, in academia, that folks who get grants then are more likely to get subsequent grants. Which, it turns out, isn’t the best option. A different simulation by other researchers suggested random was better!  And, arguably, the best policy was giving everyone the same amount!

When we take this back to the real world, what seems to be important is that luck plays a big role in success. Those folks at the very top appear to have been very lucky. Further, their future success isn’t guaranteed (note that currently there’s a prime example of over-valuing previous success). If you’re smart, and dedicated, you’re more likely to do well, but you can also be subject to the slings and arrows of fortune which can similarly contribute.

I think we should be wary of rewarding past success with greater opportunity. We should also be wary of any assessment of how smart someone must be, just because they are successful. There are a lot of factors that contribute to success (for instance, research suggests, that being taller and having a deeper voice, increases the likelihood of doing well in business). They do say luck favors the prepared mind, so do work hard. But you’re also dependent on the vicissitudes of fate. Do you feel lucky?

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So, many years ago I spent a summer working on a large engineering floor. The group I was assigned to finally told me to slow down, that I was making them look bad! In another firm we were acquired by, they weren’t happy with sales and fired the team, but then hired the leaders responsible for the broken practice to create a new process. My own previous ISP had a great app, and not only broke their implied promise but lied to me. My current ISP is more human when you can get through to them (and their app is horrid).

What’s common is a lack of alignment across the organization. I’ve eventually come to expect pockets of inefficiency in most organizations (I wonder how any of them make money!). Now, it can be bad management on the part of a particular leader, or miscommunication between units. The main point I see here is the lack of effective communication. It can be just within a team, or upwards to a business unit or community of practice, or between business units.

Look, there are lots of ways to go wrong. Lack of measurement, insufficient resources, culture hiccups, and more. One clear barrier, however, that can solve some of the others, is communication. Even before collaboration, which is better, is communication. We need to be social in appropriate ways.When we have trust and safety, we can towards transparency. When we know what others are doing, we can can work in coordination. We can show our work, we can cooperate, and even collaborate.

Achieving alignment is a useful tool for businesses, but it isn’t automatic. You need to work at it. One of the ways is to work to creating an environment where people are sharing. When you do, the benefits emerge. At least, that’s how I see it. How about you?

BTW, our final LDA debate this year will be tomorrow, December 20, at 1PM ET (10 AM PT), on lying, which is directly tied to transparency! Come for the fun, stay for the learning.

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