Learnlets

Secondary

Clark Quinn’s Learnings about Learning

Search Results for: top tools

Complexity in Learning Design

by Leave a Comment

a fractalI recently mentioned that one of the problems with research is that things are more interconnected than we think. This is particularly true with cognitive research. While we can make distinctions that simplify things in useful ways (e.g. the human information processing system model*), the underlying picture is of a more interactive system.  Which underpins why it makes sense to talk about Learning Experience Design (LXD) and not just instructional design. We need to accommodate complexity in learning design.  (* Which I talk about in Chapter 2 of my learning science book, and in my workshops on the same topic through the Allen Academy.)

We’re recognizing that the our cognition is more than just in our head. Marcia Conner, in her book  Learn More Now  mentioned how neuropeptides passed information around the body. Similarly, Annie Murphy Paul’s  The Extended Mind talks about moving cognition (and learning) into the world. In my Make It Meaningful workshops (online or F2F at DevLearn 19 Oct), I focus on how to address the emotional component of learning. In short, learning is about more than just information dump and knowledge test.

Scientifically, we’re finding there are lots of complex interactions between the current context, our prior experience, and our cognitive architecture. We’re much more ‘situated’ in the moment than the rational beings we want to believe. Behavioral economics and Daniel Kahneman’s research have made this abundantly clear. We try to avoid the hard mental work using shortcuts that work sometimes, but not others. (Understanding when is an important component of this).

We get good traction from learning science and instructional design approaches, for sure. There are good prescriptions (that we often ignore, for reasons above) about what to do and how. So, we should follow them. However, we need more. Which is why I tout LXD  Strategy! We need to account for complexity in learning design approaches.

For one, our design processes need to be iterative. We’ll make our best first guess, but it won’t be right, and we’ll need to tune. The incorporation of agile approaches, whether SAM or LLAMA or even just iterative ADDIE, reflects this. We need to evaluate and refine our designs to match the fact that our audience is more complex than we thought.

Our design also needs to think about the emotional experience as well as the cognitive experience. We want our design processes to systematically incorporate humor, safety, motivation, and more. Have we tuned the challenge enough, and how will we know?  Have we appropriately incorporated story? Are our graphics aligned or adding to cognitive load? There are lots of elements that factor in.

Our design process has to accommodate SMEs who literally can’t access what they do. Also learner interests, not just knowledge. We need to know what interim deliverables, processes for evaluation, times when we shouldn’t be working solo, and tools we need. Most importantly, we have to do this in a practical way, under real-world resource constraints.

Which is why we need to address this strategically. Too many design processes are carry-over from industrial approaches: one person, one tool, and a waterfall process. We need to do better. There’s complexity in learning design, both on the part of our learners, and ourselves as designers. Leveraging what we know about cognitive science can provide us with structures and approaches that accommodate these factors. That’s only true, however, if we are aware and actively address it. I’m happy to help, but can only do so if you reach out. (You know how to find me. ;) Here’s to effective and engaging  learning!

Overworked IDs

by 2 Comments

I was asked a somewhat challenging question the other day, and it led me to reflect. As usual, I‘m sharing that with you. The question was “How can IDs keep up with everything, feel competent and confident in our work” It‘s not a trivial question! So I‘ll share my response to overworked IDs.

There was considerable context behind the question. My interlocutor weighed in with her tasks:  

“sometimes I wonder how to best juggle everything that my role requires: project management, design and ux/ui skills, basic coding, dealing with timelines and SMEs and managers. Don‘t forget task analysis and needs assessment skills, making content accessible and engaging. And staying on top of a variety of software.”  

I recognize that this is the life of overworked IDs, particularly if you‘re the lone ID (which isn‘t infrequent), or expected to handle course development on your own. Yet it is a lot of different competencies. In work with IBSTPI, where we‘re defining competencies, we‘re recognizing that different folks cut up roles differently. Regardless, many folks wear different competency requirements that in other orgs are handled by different teams. So what‘s a person to do?

My response focused on a couple of things. First, there‘re the expectations that have emerged. After 9/11, when we were avoiding travel, there was a push for elearning. And, with the usual push for efficiency, rapid elearning became the vogue. That is, tools that made it easy to take PDFs and PPTs and put it up online with a quiz. It looked like lectures, so it must be learning, right?

One of the responses, then, is to manage expectations. In fact, a recent post addressed the gap between what we know and what orgs should know. We need to reset expectations.

As part of that, we need to create better expectations about what learning is. That was what drove the Serious eLearning Manifesto [elearningmanifesto.org], where we tried to distinguish between typical elearning and serious elearning. Our focus should shift to where our first response isn‘t a course!  

As to what is needed to feel competent and confident, I‘ve been arguing there are three strands. For one (not surprisingly ;), I think IDs need to know learning science. This includes being able to fill in the gaps in and update on instructional design prescriptions, and also to be able to push back against bad recommendations. (Besides the book, this has been the subject of the course I run for HR.com via Allen Academy, will be the focus of my presentation at ATD ICE this summer, and also my asynchronous course for the LDC conference.)  

Second, I believe a concomitant element is understanding true engagement. Here I mean going beyond trivial approaches like tarting-up drill-and-kill, and gamification, and getting into making it meaningful. (I‘ve run a workshop on that through the LDA, and it will be the topic of my workshop at DevLearn this fall.)

The final element is a performance ecosystem mindset. That is, thinking beyond the course: first to performance support, still on the optimal execution side of the equation. Then we move to informal learning, facilitating learning. Read: continual innovation! This may seem like more competencies to add on, but the goal is to reduce the emphasis (and workload) on courses, and build an organization that continues to learn. I address this in the  Revolutionize L&D book, and also my mobile course for Allen Interactions (a mobile mindset is, really, a performance ecosystem mindset!).

If you‘re on top of these you should prepared to do your job with competence and confidence. Yes, you still have to navigate organizational expectations, but you‘re better equipped to do so. I‘ll also suggest you stay tuned for further efforts to make these frameworks accessible.  

So, there‘re my responses to overworked IDs. Sorry, no magic bullets, I‘m afraid (because ‘magic‘ isn‘t a thing, sad as that may be). Hopefully, however, a basis upon which to build. That‘s my take, at any rate, I welcome hearing how you‘d respond.

A message to CxOs 2: about org learning myths

by 2 Comments

When I wrote my last post on a message to CxOs about L&D myths, I got some pushback. Which, for the record, is a good thing; one of us will learn something. As a counter to my claim that L&D often was it’s own worst enemy, there was a counter. The claim was that there are folks in L&D who get it, but fight upward against wrong beliefs. Which absolutely is true as well. So, let‘s also talk about what CxOs need to know about the org learning myths they may believe.  

First, however, I do want to say that there is evidence that L&D isn‘t doing as well as it could and should. This comes from a variety of sources. However, the question is where does the blame lie. My previous post talked about how L&D deludes itself, but there are reasons to also believe in unfair expectations. So here‘s the other side.  

  1. If it looks like schooling… I used this same one against L&D, but it‘s also the case that CxOs may believe this. Further, they could be happy if that‘s the case. Which would be a shame just as I pointed out in the other case. Lectures, information dump & knowledge test, in general content presentation doesn‘t lead to meaningful change in behavior in the absence of activity. Designed action and guided reflection, which looks a lot more like a lab or studio than a classroom, is what we want.
  2. SMEs know what needs to be learned. Research tells us to the contrary; experts don’t have conscious access to around 70% of what they  do (tho’ they do have access to what they know). Just accepting what a SME says and making content around that is likely to lead to a content dump and lack of behavior change. Instead, trust (and ensure) that your designers know more about learning than the SME, and have practices to help ameliorate the problem.
  3. The only thing that matters is keeping costs low.  This might seem to be the case, but it reflects a view that org learning is a necessary evil, not an investment. If we’re facing increasing change, as the pundits would have it, we need to adapt. That means reskilling. And effective reskilling isn’t about the cheapest approach, but the most effective for the money. Lots of things done in the name of learning (see above) are a waste of time and money. Look for impact first.
  4. Courses are the answer to performance issues.  I was regaled with a tale about how sales folks and execs were  insisting that customers wanted training. Without evaluating that claim. I’ll state a different claim: customers want solutions. If it’s persistent skills, yes, training’s the answer. However, a client found that customers were much happier with how-to videos than training for most of the situations. It’s a much more complex story.
  5. Learning stops at the classroom. As is this story. One of the reasons Charles Jennings was touting 70:20:10 was not because of the numbers, but because it was a way to get execs to realize that only the bare beginning came from courses, if at all. There’s ongoing coaching with stretch assignments and feedback, and interacting with other practitioners…don’t assume a course solves a problem. A colleague mentioned how her org realized that it couldn’t create a course without also creating manager training, otherwise they’d undermine the outcomes instead of reinforcing them.
  6. We‘ve invested in an LMS, that‘s all we need. That’s what the LMS vendors want you to believe ;)!  Seriously, if all you’re doing is courses, this could be true, but I’m hoping the above
  7. Customers want training.  Back to an earlier statement, customers want solutions. It is cool to go away to training and get smothered in good food and perks. However, it’s  also known that sometimes that  goes to the manager, not  the person who’ll actually be doing the work! Also, training can’t solve certain types of problems.  There are many types of problems customers encounter, and they have different types of solutions. Videos may be better for things that occur infrequently, onboard help or job aids may meet other needs to unusual to be able to predict for training, etc. We don’t want to make customers happy, we want  to make them successful!
  8. We need ways to categorize people. It’s a natural human thing to categorize, including people. So if someone creates an appealing categorization that promises utility, hey that sounds like a good investment. Except, there are many problems! People aren’t easy to categorize, instruments struggle to be reliable, and vested interests will prey upon the unwary.  Anyone can create a categorization scheme, but validating it, and having it be useful, are both surprisingly big hurdles. Asking people questions about their behavior tends to be flawed for complex reasons. Using such tools for important decisions like hiring and tracking have proven to be unethical. Caveat emptor.
  9. Bandwagons are made to be jumped on. Face it, we’re always looking for new and better solutions. When someone links some new research to a better outcome, it’s exciting. There’s a problem, however. We often fall prey to arguments that appear to be new, but really aren’t. For instance, all the ‘neuro’ stuff unpacks to some pretty ordinary predictions we’ve had for yonks. Further, there are real benefits to machine learning and even artificial intelligence. Yet there’s also a lot of smoke to complement the sizzle. Don’t get misled. Do a skeptical analysis.  This holds doubly true for technology objects. It’s like a cargo cult, what’s has come down the pike must be a new gift from those magic technologists! Yet, this is really just another bandwagon. Sure, Augmented Reality and Virtual Reality have some real potential. They’re also being way overused. This is predictable, c.f. Powerpoint presentations in Second Life, but ideally is avoided. Instead, find the key affordances – what the technology uniquely provides – and match the capability to the need. Again, be skeptical.

My point here is that there can be misconceptions about learning  within  L&D, but it can also be outside perspectives that are flawed. So hopefully, I’ve now addressed both. I don’t claim that this is a necessary and complete set, just certain things that are worth noting. These are org learning myths that are worth trying to overcome, or so I think. I welcome your thoughts!

Reflowable text thinking

by 1 Comment

Ok, I know I just talked about this, but something happened to sharpen my understanding. Recently, a colleague was advocating, for a product she‘s responsible for managing, that she was aware that people were “not used to reflowable text” And, frankly, that surprised me, but also explains the problems I‘ve railed about in the past. Because reflowable text thinking is a key to moving beyond hardwired formatting to separating content from description.  

As I‘ve bemoaned before, the notion of people hardcoding the way a page looks drives me nuts. If you want to change anything (and I frequently find ways to improve things), it‘s very hard to do. It takes a lot of fussing. And, yet, I have been aware of tools that are just for doing detailed page layout. This comes from the days of print, and having to handset the lead into a page to produce a newspaper and the like. But we‘re not there anymore.

Too, I‘ve had an advantage. I had the opportunity to learn to use a word processor very early on. I had vi, the Unix visual text editor to write with, allowing editing, and LaTex to specify visual details, while I was a college student (I was glad to abandon my typewriter!). Then, I got a Mac II and Microsoft Word (2.0) to write my PhD thesis. This was a boon, because I could write, and define things like margins and what headings look like. And, automagically, my paper came out from the printer (ultimately, I had to tweak a few things) ready to pass the library lady with her ruler.  

The point was that I was not fussing about how each page looked, I was instead specifying things like:

  • that a top level header required a page break beforehand (e.g. starting a new chapter),  
  • hat the next level header was left justified,  
  • that a heading should always be printed with the next paragraph or line of text,  
  • and so on.  

And when it was printed, it looked right. If I changed paper size, or margins, or what have you, it adapted.  

That‘s separating out what I‘m saying from how it behaves across screens, devices, printers, etc. And that was useful for the web, mobile, and more. It‘s responsive design. And, it‘s the key to moving our content and experiences forward.  

It‘s about describing behaviors, instead of hand-coding them. And having them refer to centralized descriptions. Which is a lot like coding, having new objects inherit the properties of their predecessors. And, it‘s about Web 3.0, the semantic web.  

Look, this has seemed to be something not all folks seem to be able to get their mind around. And, I hope that‘s not true, that it‘s learnable. Because we have to come to grips with this. It‘s already happening across the business in pretty much every other area. We can‘t lag; we need reflowable text thinking, because our audience needs flexible content. When we can gain considerable power at the expense of some rethinking, that‘s a fair tradeoff, in my mind. I welcome your thoughts.  

Five trends for 2021

by 2 Comments

As frequently happens, I get asked for my predictions. And, of course, I have reservations. Here’s a video that provides the qualifications, and five trends for 2021 that I’d expect, or like, to see.

And the script:

Hi, I‘m Clark Quinn, of Quinnovation (a boutique learning experience design strategy consultancy). I was recently asked about what trends I thought would be seen next year.  

Two relevant quotes to set the stage. For one, Alan Kay famously said “the best way to predict the future is to invent it.” So I tend to talk about trends we should see. The other is “never predict anything, particularly the future.” I heard an expert talk about having looked at predictions and outcomes, and the noticeable trend is that it went as expected, with one unforeseen twist. So, expecting I‘ll get it wrong, here are some trends I‘m either expecting or keen to see:

The first trend I‘m seeing and think will continue is an emphasis on learning science. And that‘s all to the good! Admittedly, I‘m part of this, what with running a course on learning science and having a forthcoming book on the topic. But I‘m seeing more and more people talking about it, and not all hype and even mostly right! There are more books, the Learning Guild‘s regular research reports are good, the launch of an event past summer and an associated new society focused on evidence-based learning (the Learning Development Accelerator) are all signs of growing momentum.

Second, when there‘s a lot of hype about something, it tends to be followed by a backlash.  This may be farther out than 2021, but with all the buzz about AI, I think we might see some more awareness of limitations. Yes, it can do some very useful things, but it also isn‘t a panacea. We‘re seeing a growing awareness of the problems with bias in data sets, the limitations of ungrounded knowledge, and concerns about the human costs.  

Three. On a related note, then, I expect more emphasis on the importance of meaningful practice. This comes from learning science, but also the focus on engagement. Thus, the push for Short Sims, and better written multiple choice questions, and in general a focus on ‘do‘, not know.   Hopefully, we‘ll see tool vendors aligning their content and assessment capabilities towards designing scenarios and contextualized practice, along with specific feedback for each wrong answer and support for reflection.

Fourth, I hope for a push towards content systems as well. This, too, may not be in the short term, but ultimately we have to realize that hardwiring experiences may make sense for formal systems, but not for adaptive learning.LXPs are a good move here, even if misnamed (really, they‘re smart portals, not learning experience platforms). Ultimately, we‘ll be better off if we can deliver content by description and rules, like recommendation system, rather than by having to handcraft content to create a ‘one-size fits all‘ solution.  

Finally, I think that our collaboration tools haven‘t lived up to the promise of technology. They‘re very much oriented towards particular modes, instead of supporting really rich interaction. This, too, is more long term, but we really should be able to talk together while working to create representations that capture our evolving thinking. Easily and elegantly! There‘s real opportunity here to engage multiple representations in an elegant suite.  

So there you have it, a wishful list of five trends for 2021. So what do you expect, or hope, to see?

The plusses and minuses of learning science research

by 1 Comment

A person who I find quite insightful (and occasionally inciteful ;) is Donald Clark. He built and sold Epic, an elearning company, and now he leads a learning AI company, Wildfire. He’s knowledgeable (for instance, having read up and summarized centuries of learning theorists), willing to call out bad learning, and he’s funny. And so, when he reported on a new study, I of course looked into it. And I find that it points out the plusses  and  minuses of learning science research.

To be clear, this is about his product, so there’s a vested interest. However, he’s got integrity; he’s not going to sully his reputation with a bad study. And, it’s a good study. It rightly demonstrates an important point. It’s just that it stops short of what we need for full  learning.

So, his product does something pretty amazing. You give it content, and it can not only answer questions about the content (as, for instance, some chat tools do), it can turn the tables and ask  you questions about the content. That is, it can serve as a sort of tutor. Which is all to the good.

What it can’t do, of course, is design meaningful practice. As Van Merriënboer’s Four Component Instructional Design (4C/ID) points out, you need to know the information, and you also need practice applying it. And I reckon we’re still far from that. So, while this is part of a whole solution (and Donald knows this), it’s not the full solution. He’s subsequently let me know it can do language tasks, which is impressive. I’m thinking more of contextualized scenarios, however.

The study demonstrates, as you might expect, that breaking up a video into reasonable chunks, and having system-generated questions asked in-between, led to 61% better retrieval, going from getting 8 to 14 questions right. That is a big improvement. it’s also impressive, since it’s generating those questions from video! That is, it parses the video, establishes a transcript, and then uses that to generate a knowledge base. Very cool.

And it’s a well-designed study. It’s got a control group, and a  reasonable number of subjects. It uses the same test material, for an AB comparison. Presumably, the video chunking was done by hand, into four pieces. The chunking and break might account for the difference, which wasn’t controlled for, but it’s still a big improvement. Granted, we know that watching a video alone isn’t necessarily going to improve retention (except, perhaps, over some other non-interactive way of dumping content). But still, this is good as it’s an improvement and a lot of work was saved.

What I quibble about, however, is the nature of the retrieval. The types of questions liable to be asked (and it’s not indicated), are knowledge questions. As suggested above, knowledge is a necessary component. But using that knowledge to make decisions in context is typically what our goals are. And to achieve such goals, you basically have to practice making decisions in context. (Interestingly, the topic here was equality and diversity, a topic he has complained about!)

Knowledge about a topic isn’t likely to impact your ability to apply it. What will  make a difference are actually doing things about it, like calling it out, having consequences, and actively working to remedy imbalances. And that requires separate practice. Which he’s acknowledged in the past, and rightly points out that his solution means you can devote more resources to that end.

Thus, the plusses of learning science research are we nibble away at the questions we need to answer, and find answers about the questions we ask. The minus, of course, is not necessarily asking the most important questions. It’d be easy to see this and say: “we’ve improved retention, and we’re done”. However, it won’t necessarily lead to reducing the behaviors being learned about, or building ability to deal with it.  There are plusses and minuses of learning science research, and we need to know the strengths, and limitations, of it when we hear it.

Thinking Transformation

by Leave a Comment

This pandemic has led to everyone scrambling to work digitally. And it‘s not really a transformation (which shouldn‘t be ‘digital first‘), but rather just ‘move what we do online‘. And that‘s understandable. Over time, however, I think we want to shift our mindset. And, I think a previous exercise in thinking transformation is valuable here. I‘m talking mobile.

When I originally was talking about mobile, I was doing so from a perspective of augmenting our brains. The 4C‘s framework was a way to think about core mobile affordance from a point of view of what mobile offers. Then I moved on to the role the devices play in our (working) life. It‘s about not just courses on a phone, but:

  • Augmenting formal learning: extending it
  • Performance support: cognitive augmentation
  • Social: tapping into the power of social and informal learning
  • Contextual: mobile‘s unique opportunity

And, I suggest, these are valuable ways to think about using technology in general to support us. On principle, I like to think about how technology supports our thinking (not the other way around ;). To future-proof what I propose is one driver, so tech changes don’t undermine relevance. Further, since mobile is a platform – a strategy not just a tactic – focusing on fundamentals makes sense.

For instance, elearning shouldn‘t look like just a classroom online. That can and arguably should be part of it, but there‘s more. It‘s about extending formal learning, not just delivering it. And aligning with how we really learn, because it really does have to be effective.

Similarly, with folks working from wherever, thinking about the support they need is important. What tools, aids, guides, etc., will help them work more effectively without their prior context? Let’s change workflows to align better with what‘s known about how we work.

And making people available in useful ways for communication and collaboration is important. The demands of online meetings are becoming more prevalent and onerous. Zoom fatigue is a thing!   How can we optimize the experience?

Contextual is more uniquely mobile, taking advantage of where and when you are (and other contextual factors), but we probably do need to account for them more astutely. If your kids are in the other room, what does that do to your ability to work? Here, of course, is the greatest difference from mobile, but the mindset is still relevant.

So, for instance, when I ran a mobile course for the Allen Academy, we had a week dedicated to each of these elements (as well as kicking off a mobile mindset and closing on strategy). Given that it was still early in this new world, I didn‘t really push the thought of how this is a more general tactic. Of course, I now would.

And, given that I‘ll be running the course again, I definitely will! Look, mobile hasn‘t gone away, and we‘re possibly using mobile tools more now even though we‘re not on the road! So mobile‘s still relevant, and the mindset behind ‘thinking mobile‘ is even more relevant. I’ll be talking with Christopher Allen of Allen Interactions about it tomorrow (12 Aug) at 11AM PT, 2 Eastern (see below). And, if you‘re interested in the course, check it out!

Practicing the Preach

by 4 Comments

I’m working on my next plan for global domination. And as I do, I’ve been developing my thinking, and there are some interesting outcomes. Including a realization that I wasn’t doing what I usually recommend. And I also believe that you should ‘show your work‘. So here I’m practicing the preach.

First, I’m developing my understanding, getting concrete about it. I usually use Omnigraffle as a diagramming tool, to represent my conceptual understandings. And I started doing that as part of the ‘developing thinking’ part. But I started with a diagram, and took the elements out and mindmapped them, and threw in other bits. In short, the ‘diagram’ has become a visual place to store bits and pieces of different diagrams, representations, mindmap, prose, or more. As well as outlining elsewhere. But it’s working out for me, so I thought I’d share.

The overall visualization gives me a place, like a business canvas, to drop stuff on and rearrange. It’s a ‘thinking tool’. I’m also copying part of the the activity map and linking things together to capture the actual flow between content and activities. Etc. A virtual whiteboard, I guess.

Second, one of the things to represent was how this would be communicated. Whether a course, or interactive ebook, or whatever, I want to create a flow. And I realized an activity map might make sense. I haven’t done this before (I’ve used storyboards and diagrams), but I find it interesting. Here’s the current status.

Across the top are the various stages (Introduction, the Principles, the resulting learning Elements, the associated Process, and the Closing). Your stages may vary.  Along the side are the different components (the Content topics, the associated practice Activities, the Emotions I to be evoked, the Stories to tell, and the Tools). I think putting in ’emotion’ is an important step! And then I can drop text bits into the intersections.

Finally, as I started developing the associated content, I realized one thing I advocate is backwards design. That is, envision the performance and how it’s distributed across tools and brains. Then, I realized I hadn’t designed the tools first! I’m going back and doing that. So it’s now in the activity map as well ;).

Just thought I’d share this, practicing the preach, and hope that you find it interesting, if not useful. Feedback welcome!

 

A mlearning course?

by Leave a Comment

As I mentioned in my last post, yes, I’ll be running a course on mobile learning (starts next week! 😱). And I can understand if you’re thinking “a mlearning course?”   So I thought I’d lay out the thinking a bit, and see if I can help you see why I’m doing this.

So, I don’t usually do things just for money. I’ve turned down things I thought were inappropriate in the past. (Which is amongst the reasons I’m not rich! ;) I try to do things that I think are needed.

And that’s part of the reason I’m doing it the way I am: the folks I’m doing it with. Michael Allen’s established a reputation for quality in learning, advocating for good design in print and talks, and living it in his work. We’ve had a good relationship, endorsing each other’s books ;), but working with him on the Serious eLearning Manifesto reinforced that not is he smart and committed, but just a great guy. So doing the course with the Allen Academy ensured that I could trust the integrity of what we’d do.

So isn’t mobile learning already in place? You’d think so, since my book on the topic came out nine years ago, and is already out of print! (And it was a good book  and  since I based it on the cognitive principles, it’s still relevant. It’s also now available again (at a much improved price).   However, I was recently asked to give a mobile talk by the local chapter. When I opined that mobile is old, the organizer let me know “it may be old for you, but not for everybody!”   So there’s still a need!

And, of course, the content is relevant. I derive the course form cognitive principles, so even if the tech changes (and it has) the foundations are transferrable. Whether you’re talking about tablets, phones, or watches, the implications are apt.

So what  will it cover? Here’re the topics of the six weeks:

  1. Introduction. Defining mobile, and some overarching concepts that will guide the rest: the 4Cs, and four major categories of use.
  2. Formal learning. The first of the four categories, and it’s  not about courses on a phone. We’ll look at augmenting  formal learning.
  3. Performance support. We’re looking at why it’s mobile’s natural niche, and what makes it work.
  4. Social/informal. Here we’re looking at going beyond optimizing performance and moving to continual learning and innovation. And mobile’s role.
  5. Contextual. This is mobile’s real opportunity, not just bringing things to wherever/whenever, but doing things  because of when and where we are. And more.
  6. Strategy. This is the wrap up, where we talk about what it takes to make this all work in the organization.

I’ve designed in discussions, and group assignments, so while it’s grounded in the book, it’s both updated and more interactive. I should be careful to mention that it’s not about development, using authoring tools, or more. It’s about  thinking different, which mobile requires. The mindset is performance ecosystem, and not surprisingly therefore coupled to the thinking behind the L&D revolution I continue to advocate for.

I’m not dunning for students, since we’ve already got a good number of registrations, but instead I just wanted to expose the thinking behind the choices (showing my work). That is, show you why a mlearning course. Still, I’d welcome seeing you there if you’re interested in getting your mind around some transferrable principles that enable mobile, and more!   Other than that, stay safe and take care.

Extreme Times

by 2 Comments

This was originally intended to be one of my Learning Solutions Mag columns (Quinnsights). Sadly, that platform is no longer an option. Guess this  is part of the extreme times! It’s a bit long for my usual posts, but I didn’t want it to go to waste.  

In 2004, I co-wrote a chapter with Eileen Clegg for Marcia Conner & James G. Clawson‘s Creating a Learning Culture book to accompany the event they held on the topic. Eileen‘s husband was doing research on ‘extremophiles‘, organisms that survive in extreme conditions, and we were looking at biomimetic inspiration from those mechanisms. Titled The Agility Factor, I think the lessons we wrote about are all the more important now in these extreme times.

Sure, at this point everyone is touting solutions for working and learning at home. With most of the population under some form of lockdown, there are a lot of prescriptions, to the extent there’s already a backlash! Even I‘ve been guilty. But here I want to talk a bigger scope than just learning. People are worried. Organizations are struggling.

At the time, our commentary was largely reacting to the crash of the internet bubble circa 2001. Times were tough, and organizations were wondering how to cope. Fast forward to 2020, and we‘re in even more dire circumstances. While then we had economic turmoil, now we‘re adding in a lethal disease. Uncertainly abounds. Our employees, our managers, our executives are all scrambling to make sense. And so, I thought it appropriate to revisit those lessons in this new era, and consider the technology/human intersection in these times.

Coping with Extreme Times

One of the main issues that contextualizes this conversation is that different organizations are at different places in their digital transformation. And, as I opined recently, it‘s about getting the culture right first.

It‘s easy to think of organizations that just haven‘t yet started using digital, and are faced with the need to change. They‘re going to struggle. There is a lot of guidance out there, but if you haven‘t got your mind around the technology, or what communication, collaboration, and learning are all about, there‘s more to it.

If you‘ve started with some experimentation, it should be easier. You‘ve tried out some things, and so you‘ve had some technology experience. You may well have tried and failed, but the knowledge from losses should be useful too! That‘s what a learning organization is all about.

Which means that another organization type that will struggle is the one that‘s rigidly hierarchical. One that‘s had all the thinking done up top, and filtered down. They may well have dictated technology practices, but they‘re likely more about making things more efficient. And so, trying to be effective at scale at distance is a different issue.

Instead, the organizations that thrive are those that are continually experimenting, learning, and moving forward. I reckon many folks are wishing they‘d tried out some things already, rather than scrambling. Of course, this is different not just quantitatively, but qualitatively, and that means we‘re going beyond just adaptation. We need to go big in extreme times!

Extremophiles

Across the globe, and presumably the universe, conditions vary from desiccating heat to crippling cold. Environments may have high toxicity owing to chemicals, salt, and more. And, as circumstances change, organisms need to adapt. And yet, life somehow exists in many of these circumstances. How? Through a variety of mechanisms. Not all are unique to extremophiles, but each is used and provides some insight. Here are the suite we talked about:

  • Ionic bonds: while all organisms have proteins connected by ionic bonds, extremophile organisms have more and stronger bonds.
  • Environmental monitoring: here, the organism is in tight coupling with the environment, the better to respond, though sometime the responses are unusual.
  • Heat-shock proteins: special proteins are released under threat to help protect other proteins.
  • Equilibrium: extremophiles can not only attempt to expel any toxicity, certain extremophiles work to neutralize the toxic element internally.
  • Symbiosis: certain organisms create unique relationships that allow them to mutually coexist in extreme conditions.

For each of these there are organizational corollaries that we can consider, and then we can look at how technology and learning & development can help. We need to go beyond the usual and think about how to do these in a big way.

Organizational Equivalents

How do translate these? There are not direct transfers, but inferences we can make. Just as organizations been using inspirations from animals to guide new thinking in products, here we‘re looking at inspirations for how to work together better. What do organisms that adapt to environmental extremes mean for organizations coping in extreme times?

First, strengthening the bonds is about building trust in the organization and believing in the organizational mission. First, of course, it‘s about connecting people, so that they care about one another. And having managers work as coaches, using data to improve folks, not censure them. Then, as Dan Pink, in Drive, helped us know, it‘s about connecting people to purpose. That means an organization has to have a meaningful purpose, one that people feel proud to align with. And everyone in the org needs to understand how their role contributes. Yes, this is all work, but the point is that these organisms invest extra effort to be able to withstand extraordinary conditions.

Environmental monitoring isn‘t new, as most organizations track market trends, competitive analysis, customer sentiment, and more. Here it means going further, with everyone being active in their community of practice and actively monitoring trends in related fields for implications to improve practice. The organization needs to be sensitive to what‘s happening in rich and deep ways. This has to not be done as a special operation, but permeate the organization.

Heat shock proteins suggest a proactive approach to trouble. One form is internal monitoring for problems. Health initiatives in the organization are not just promoting healthy behaviors, but also actively developing the skills to notice and watch out for your fellow employee. It‘s about caring enough to look for signs of struggle and reach out and try to help. In times like this, it‘s more, ensuring that as people face changes, they have support to understand, act differently, and persist until it becomes a new way of doing things.

Equilibrium is an interesting one that suggests taking in new ideas, trying them out, and seeing what they imply. Think “let‘s try it out and see how it‘s re-contextualized here and then what it might mean that we can do better”, not “that‘s not how we do it here”. It‘s about experimentation, and internalizing new ideas. It‘s got to be more than just copying (e.g. best practices), and going beyond to understand the underlying ideas and modifying them to work in this context (e.g. best principles).

Finally, symbiosis implies working with other organizations in a radically more integrated manner. Instead of just consuming things, you look at the practices that were instituted by Toyota. They looked at their supply chain partners and assisted them in becoming more effective and efficient. It‘s about radical cooperation.

L&D Technology Role

So, given that we‘re about eLearning, what‘s the role of technology here? At core, it‘s about communication. It‘s about moving to showing your work, including mistakes and lessons learned (always together).   And there are lots of ways to do this.

One of the most important steps is to have bosses, managers and executives, share their thinking. I know, it seems risky, but it builds trust. If ‘the boss‘ is willing to admit mistakes, it makes the environment feel safe. And that builds those bonds that will help an organization weather tough times.

It also means helping individuals develop active monitoring skills. There are tools that track outside news and filter it for particular interests. Everyone can tailor their own feed. And this is part of building your personal knowledge mastery. Everyone should be looking for new ideas to improve.

The new ideas need, of course, to be coupled with experimentation, such as equilibrium suggests. And this may involve collaboration to make it work. So collaborative tools are important to develop testing plans and evaluate outcomes. Building in an expectation of lessons learned, and having scheduled sharing events for these lessons, is a complement. And, if not digitally moderated, at least capturing and sharing the outcomes for others to learn from.

It‘s important also to support people in these new ways of working. Don‘t just expect them to get it, but build support into and/or around the tools. Don’t just train, but anticipate struggles and build support. And have support for unanticipated struggles! This also includes quick references about what to do when you‘re worried about someone or even yourself. This is the heat-shock approach of preventing breakdowns during the transitions.

And, of course, building a network that includes your partners along the supply chain is the symbiotic approach. It‘s about building a sharing community that can help them be better, and they can do the same for you. It‘s also about collaboration, working together on problems rather than casting blame. This builds bonds with them too!

The L&D role is to facilitate all this communication and collaboration. In extreme times, L&D is part of the solution. Continual learning is required, and building a strong framework for keeping people together to work and learn is critical. We’re increasingly learning that working together is better; bake that into your own operations!