I’ve been doing this blog now for 13.5 years (started in January 2006 with my first post), and have generated over 1600 posts in that time. My intentions about productivity started, perhaps, more ambitious, but they settled down a number of years ago. And, I’m finding, they’ve settled again of late. So it’s time to reflect on my status of writing ongoing!

So, while I started with hoping for one every biz day, I was always happy to get 2 or 3 per week. And I’d pretty much settled on meeting a self-imposed goal of 2 per week. Which I’ve kept that up for years; sometimes, like at confs, I’d do 3 per week because of my mind maps, and  occasionally  I’d only get 1. Yet more weeks than not of late (say, the past few months), I’ve struggled to come up with even 1. What’s going on (he asks himself)?

Ok, during that time, I’ve written four more books (the first one came out before the blog started). And I’ve worked, and written articles, and traveled and spoken, and more. And that’s still status quo. So why have I slipped of late? What’s changed?

Well, for one, I’ve gone from occasional articles, to a monthly column for the Litmos blog for the past 4.5 years, and now to a second monthly column for Learning Solutions for the past 2.5 years. Yet, I’ve been keeping up until the past months.

One thing  has  changed. M’lady started working part time, and now is full time. Which is fine, because I am quite capable of some household tasks. The planning meals and cooking haven’t really changed in their demands, but I find I  am spending more time on shopping in particular.  Though that shouldn’t be such a barrier. And it started a year ago.

I’m likely to have another big writing task upcoming (stay tuned ;), and that tends to generate insights. But overall, I’m not feeling positive I’ll be able to continue achieving two posts a week. At least ’til I understand better what’s going on.  I’ll shoot for 2, of course, but I feel like I should be open and say that I may only get to 1 a week. That’s where my writing ongoing seems to be headed. We’ll see.

It’s time again for Jane Hart’s Top Learning Tools Survey, so it’s time for my personal list (and for you to submit yours).  Here goes!

1. WordPress: my first learning tool is this blog. Here’s where I lay out my ideas. The learning comes from just me thinking through things to keep populating the post, and the exercise of actually putting the thoughts down. And of course from comments, whether here or as often happens, on LinkedIn.
2. OmniGraffle: a lot of thinking comes from reflection, both with the blog for thoughts, and through diagramming my understanding. Diagrams allow us to map conceptual relationships to spatial ones to facilitate comprehension.
3. OmniOutliner: another way I think is in outlines.
4. Word: I do most of my writing besides blogging in Word. This includes my Quinnsights column for Learning Solutions and my posts for the Litmos blog. And, of course, books. For the latter, in particular, the outlining features in Word are a necessity for me.
5. Pagico: This is a project management tool, and I have entries for all the projects and groups I work with. I also through in random ToDos. I’m not as good with it as I’d like, but it helps keep ideas from not getting explored.
6. Slack: I work with a number of groups, and one in particular really benefits from the social interaction Slack provides between meetings.
7. Zoom: I use both Blue Jeans and Zoom, but I use Zoom more, as it has chats with my ITA colleagues, as well as video conversations with folks.
8. Twitter: Of course, Twitter is a way to have debates, as I recently found out, as well as chats (c.f. #lrnchat and #guildchat).  There’s also a steady stream of the latest news.
9. DuckDuckGo: I’ve largely replaced Google for search, but search (and Wikipedia) are powerful learning opportunities.
10. Social media (read: LinkedIn/Facebook): places where I hang with my colleagues, ask questions, and see what dialogs are going on.

Those are a partial list of my learning tools. What’re yours?

With any industry, a large quantity of buzzwords exist, and Learning & Development isn‘t any different. Likewise, plusses and minuses accrue.  It‘s helpful to know the buzzword as well as the real meaning behind it, but how do you do this?

Buzzwords can become vernacular. With a professional vocabulary, everyone has a shared understanding of what‘s meant. It‘s more efficient when concepts have short words or phrases that define them. “Authoring tools” went from bizbuzz to common parlance. In our field, of course!  We can refer to things tersely that unpack into a complex understanding. (And, it can be cool to have a secret language for those in the ‘know‘. ;)

The flipside is when those buzzwords aren‘t shared, or are vague, or even deliberately misused, confusion ensues.   If people are using terms others don‘t know, there‘s an opportunity for uncertainty or even misconceptions. People can toss around buzzwords to sound cool. Or for more nefarious purposes.

To get concrete, terms like xAPI may be obscure. ‘Microlearning‘ is still ill-defined, meaning two different things by its use. And the prefix ‘neuro‘ has little practical implications, but it sounds like we‘re on top of the latest scientific findings!

How do we deal with this? We need to be aware. A healthy skepticism is a valuable frame of mind around claims. Which requires us to be proactive; we need to be willing to ask people to be clear when they toss terms about. And to keep up with the literature in our field.

The best time to be open is when a term is being used for the first time in your experience. You need to look for definitions. Most importantly, look for independent definitions. And ask yourself “who‘s telling me, and what is their vested interest”

The ultimate goal is to be acquainted with the terminology of your field, and open to new ideas while resistant to unwarranted hype. It requires effort, but the alternative is wasting time or money on things not worthy of resources.

With my wicked smart and totally cool colleagues Jennifer Murphy of QIC and Chad Udell of Float, we‘ll be running a buzzword bingosession at the top-notch DevLearn conference at 3PM on Wed the 23^rdof October. You‘ll cut through the haze, have some fun, and maybe win a prize!   Hope to see you there.

After my previous article on direct instruction versus guided discovery, some discussion mentioned Engelmann’s Direct Instruction (DI). And, something again pointed me to the most comprehensive survey of educational effects. So, I tracked both of these down, and found some interesting results that both supported, and confounded, my learning. Ultimately, of course, it expanded my understanding, which is always my desire. So it’s time to think a bit deeper about Direct Instruction and Learning Experience Design.

Engelmann’s Direct Instruction is very scripted. It is rigorous in its goals, and has a high amount of responses from learners.  Empirically, DI has great success, with some complaints about lack of teacher flexibility. It strikes me as very good for developing core skills like reading and maths.  I was worried about the intersection of many responses a minute and more complex tasks, though it appears that’s an issue that has been addressed. I couldn’t find the paper that makes that case, however.

Another direction, however, proved fruitful.  John Hattie, an educational researcher, collected and conducted reviews of 800+ meta-analyses to look at what worked (and didn’t) in education.  It’s a monumental work, collected in his book Visible Learning. I’d heard of it before, but hadn’t tracked it down. It was time.

And it’s impressive in breadth  and depth.  This is arguably the single most important work in education. And it opened my eyes in several ways.  To illustrate, let me collect for you the top (>.4)  impacts found, which have some really interesting implications:

• Reciprocal teaching (.74)
• Providing feedback (.72)
• Teaching student self-verbalization (.67)
• Meta-cognition strategies (.67)
• Direction instruction (.59)
• Mastery learning (.57)
• Goals-challenging (.56)
• Frequent/effects of testing (.46)
• Behavioral organizers (.41)

Reciprocal teaching and meta-cognition strategies coming out highly, a great outcome. And of course I am not surprised to see the importance of feedback. I have to say that I  was surprised to see direct instruction and mastery learning coming out so high.  So what’s going on?  It’s related to what I mentioned in the afore-mentioned article, about just what the definition of DI is.

So, Hattie says: …”what the critics mean by direct instruction is didactic teacher-led talking from the front…” And, indeed, that’s my fear of using the label. He goes on to point out the major steps of DI (in my words):

1. Have clear learning objectives: what should the learner be able to  do?
2. Clear success criteria (which to me is part of 1)
3. Engagement: an emotional ‘hook’
4. A clear pedagogy: info (models & examples), modeling, checking for understanding
5. Guided practice
6. Closure of the learning experience
7. Reactivation: spaced and varied practice

And, of course, this is pretty much everything I argue for as being key to successful learning experience design. And, as I suspected, DI is not what the label would lead you to believe (which I  do think is a problem).  As I mentioned in a subsequent post, I’ve synthesized my approach across many elements, integrating the emotional elements along with effective education practice (see the alignment).  There’s so much more here, but it’s a very interesting result. Direct Instruction and Learning Experience Design have a really nice alignment.

And a perfect opportunity to remind you that I’ll be offering a Learning Experience Design workshop at DevLearn, which will include the results of my continuing investigation (over decades) to create an approach that’s doable and works. Hope to see you there!

I was talking with a vendor of a robust suite of tools. In the course of it, in my usual teasing way, I asked a question. And, while I wasn’t surprised at the answer, I was ‘concerned’. And so should you be. So I’m going to suggest you start asking of your vendors “Do you drink your own champagne?”

So, this was a manufacturer of an LMS (and some other, related, platforms). And they market their advanced capabilities. And, really, I have no problem with their tools; they seem pretty enlightened.  So I asked whether they used their own tools.

And there are reasons to do so. For one, to have credibility, for sure. And, to truly know your own product. But the really important reason is to be able to understand the use experience and tune accordingly. Customer research is an important tool here as well, but it’s not the only one. You really need to use something to truly know what works and what doesn’t.

It’s a form of experimentation. I test myself by trying to apply my principles in my endeavors, and then try to take on new situations to try out my beliefs more broadly.  And so should you, at the individual and organizational level. Using your own tool is a form of this.  It is, essentially, testing your theory with research!

And I think most folks with services and such are likely to practice what they preach.  And that could be for some bad things as well as good (thinking: learning styles vendors).  But I was surprised when the answer was only “somewhat”.  That’s not really good enough.

So, I’m going to suggest that this should be a question you ask of every vendor. I’m also going to suggest every vendor ensure that they do use their own tool. Internally, for their own work. Whether it’s authoring tools, a course management system, a portal, a web meeting tool, what have you. If you don’t drink your own champagne, you’re not only undermining trust, you’re losing a valuable source of information. Now, pass the bubbly, would you?

Over a decade ago, my friend Jay Cross invited me to join the Internet Time Alliance. He had been touting the value of Informal Learning, and realized he was doing it alone. I was honored to join Jane Hart, Harold Jarche, and Charles Jennings, and have come to know and value them as colleagues and friends. When Jay passed away, we determined to honor his ideas by recognizing those who continue to carry the banner for informal learning. We announce the ITA memorial award on 5 July, Jay’s birthday. This year’s winner is Michelle Ockers.

I’ve only met Michelle once, when I was visiting  Australia to deliver a keynote. She was kind enough to ask me to sign a copy of Revolutionize L&D. I didn’t know much about her work then, but have subsequently seen it in a variety of places. She’s active in social media, for instance. She also coordinated the Learning & Performance Institute capability  map  exercise that occurred last summer. She’s systematically demonstrated broad ranging interests and abilities around organizational learning.

I’m pleased that we can honor her and her work helping organizations work more productively and fluidly. The official announcement is on the ITA site. Congratulations, Michelle on the 2019 ITA Jay Cross Memorial Award!

 

I’ve been looking at a couple of things, with a goal is to look for the sweet spot at the intersection.  I’m looking at my missions, interests, and what’s resonating. And, I find, that they’re converging into a few things. Which I thought I’d make concrete, because I really want to see if these are things that are tangible and valuable. What is the right packaging? I’m asking for your help: is this the right suite, and if not, what do you want?

To start, one of my themes for the year is transformation, about deeper learning design. I’ve argued strongly that we need to do deeper learning design before we worry about tarting it up with personalization/adaptation, VR/AR, AI, etc. It’s time to get serious about actually having an organizational impact! And we’ve converging evidence about what it is.

As triangulation, what’s appearing as interests are those things people are asking for, or are tracking. And I’ve been asked recently (and been happy to oblige) talking about learning science. The eLearning Guild just had a summit, and my learning experience design workshop from Learning Solutions has been again  accepted for DevLearn (and I’d welcome seeing you there!).

We also know what’s largely lacking, and how to help. Through experience, I’ve found there are several ways to make progress. For one, you need the foundational knowledge, and it really needs to be shared and agreed in the organization. For another, you can benefit from a clear understanding of your current state. You can’t move forward if you don’t know where you are! Then, you need a clear plan that gets you from where you are to where you can be, that’s right for you. No ‘best practices’, but a principled  approach, looking at the bigger picture. Finally, support in moving forward can be valuable. There are ways you can fall back or barriers can hinder you that you need fresh thinking to address.

So the offer involves any combination of the following things:

Workshop: we actively explore and bring to bring it to life the necessary knowledge, and then practice applying it. This brings a shared vocabulary and understanding of what needs to change and why.

Assessment: an independent assessment of where you are in your processes, and what are the opportunities for change. The goal is to identify the minimal interventions that can have the biggest impact.

Strategy Session: here the goal is to determine the path to change. What are the opportunities, barriers, and what are the sequence of moves that create the change? It’s about understanding context and opportunity, bringing in the best principles, and using them as a guide to move forward.

Coaching: here we provide the lightest weight support that will keep momentum. In my experience, it’s been easy for folks to fall back into prior thinking without an ongoing stimulus, and the ability to comment early on in a plan on interim moves help keep a strategy on track.

These can manifest in several ways:

• a learning science workshop for the team and an evaluation of your design process for the small changes with the big impact
• the assessment, a strategy session for improvements, and a termed coaching engagement to support success

Your situation would make a particular combination more sensible. They’re better together, but any one is a catalyst for improvement. And these are all things I’ve done with organizations and have had success with. Each alone is done for quite less than $10K (parameters vary), but the goal is to make these very accessible. And, of course, substantial discounts for taking on more than one (to make the change more likely to stick).

I note that my other theme for the year is ‘intellectricity‘, unpacking the power of your people in informal learning. While I’m helping organizations around this as well, I haven’t yet formalized it like this. Yet it’s clear each could be done in the above formats as well, and I’m happy to make the same offer. And there seems to be growing interest in this area as well.

The reason I’m putting this out there, however, is because I want feedback and/or uptake. It’s not enough to just encourage, I want to actually support meaningful change! I have strong grounds to believe these are important and necessary changes, and I want to help make it happen, the more the faster the better. And if this isn’t the packaging you expect, let me know. I’m happy to discuss and adapt. What I want to do is have an impact, so help me figure out how.

How are learning design teams are distributed (or not) in an organization? I’ve seen both totally separate teams in organizations (spoke), and totally central ones (hub), and of course gradations in between.  While size of the organization is one driver, there are tradeoffs in efficiencies and effectiveness. And, I think tech can help. How?

So, to start, this has been an ongoing debate. I cynically (who, me? :) suspect that when a new manager comes in, whatever it is that’s been done, they have to do the opposite. Something must be done, right away!  More seriously, there are strengths to either.

Distributed teams as closer to their partners. They have greater internal knowledge, and can be more responsive. Central teams make it easier to maintain quality. You don’t get driven as much by differing team cultures and  can maintain a bastion of quality. Similarly, you can often find efficiencies from scale and lack of redundancy.  And sometimes, you can have distributed teams taking advantage of some shared resources such as video production.

However, I was pondering how we can use technology to help break through the tradeoffs. As we build a community  around the design of learning, the teams can be distributed as long as they’re continuing to learn together.  If the community is continuing to learn together, showing their work and lessons learned, and regularly connecting whether through lunch-and-learns, offsites, or what have you, the shared learnings don’t need to come from physical proximity.

Building culture is hard, but as I’ve argued elsewhere, L&D really should take ownership of the new ways of working  first, before proselytizing it elsewhere. Thus, L&D should be practicing the principles of a learning culture. Then, it really doesn’t matter if you’re hub  or spoke, or anything in-between, because you  are a community.

As I reflect further on the improved surprise model, I realize there’s one thing I missed. The model gives a motivation for learning, and an implication for design. But there’s one thing more in the model, and one more implication for design. And this has to do with safety.

So, first, the initial model says that we learn to  minimize surprise. We’re driven to remove the mismatch between what we expect and what occurs. This  could lead to a desire to do nothing, or as little as possible, but a further elaboration says we also want to maximize outcomes. Thus, we won’t just sit around, but explore.

That means that helping learners know 2 things: that they want to know this (it’s to optimize what they care about), and that they don’t know it (the gap they have to minimize). If we do that, they’re ready to learn. But there’s one more thing.

We  won’t explore other alternatives to see if they’re a better solution if the consequences are high. We’ll only explore if the cost of this exploration isn’t higher than the benefits we gain if it’s better. So that one other things is safety.  If it isn’t safe, we’ll stick with the known solution.

Which means that we need to make it safe to explore in our learning.  And, that includes both formal learning and  informal.  Mistakes in learning must be expected and accepted. In formal learning, mistakes are learning opportunities. Have alternatives that represent reliable ways folks go wrong, and it’s ok if they choose those because you have feedback specifically for that selection. And informally, mistakes (not the same ones, or obvious ones, there’s accountability too) are fine when the lesson’s learned.

Understanding how, and why,  we learn is critical to optimizing learning. And I think that’s a valuable goal. It’s too important to leave to chance, or old habits. It’s time to be alert to what we know, and put it into practice.

I was perusing an old list of potential column topics, and came across one that asked about MOOCs. Now, you probably recognize that the term is pretty much evaporated from any list of top L&D concerns. That’s kind of funny, to me (ok, so you may question my sense of humor).  And it makes me wonder what topics are current and are on the horizon. What is the coming buzzword?

I talked in a column about the problem with chasing shiny objects. In short, it’s easy to get swayed by the latest hot topic, and want to be seen to be on top of things. But, as I’ve said repeatedly, a gilded dud is still a dud. If we get the core right first,  then we can move on to see what’s real. And, of course, we need to dig into the real affordances, not just the hype (PowerPoint in Second Life, anyone?).

So there are some buzzwords already on the wane. Such as MOOCs. A good sign is if someone’s trademarked it, it’s jumped the shark. Frankly, that already characterizes  microlearning. And we’ve had someone recently claim to have invented workflow learning (though it’s been talked about for years).  When they’re fighting about ownership, it’s done.

What’s waxing as opposed to waning?  How about ‘bots?  That’s the topic du jour! Often, as part of AI; as is Machine Learning, Deep Learning, and so on. Also Analytics (I think Big Data is already in the last paragraph’s category). Not necessarily bad, but part of this phenomenon is a lack of clarity about what we mean when we use any of these terms.  So, maybe it is like AI: if you know what you’re talking about, it’s no longer new and shiny! And of course, AR and VR are very much  now. And personalized and adaptive! (Time for some ownership moves!)

So here’s the question: what’s the  next buzzword? Would that it were learning science!  Ok, there’s been a bit of a resurgence (time to plug the coming Science of Learning  Summit, with the usual caveat), but not near enough. C’mon, folks, lets get together and work on taking your design approaches and tuning them up!  Of course, I could wish we’re talking IA instead of AI, too. What else? Contextual. Content Systems. Those are my thinking (and I’ve been talking about these things for years; maybe it’s time).

So, what’s on your list? What’s next? What’s ready for primetime? Wearables? Post-AI? (I just made that up.)  I look forward to hearing your thoughts!