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Extreme Times

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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!

What’s in an image?

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My post earlier this week on the images processed 60K faster prompted some discussion (over on LinkedIn ;). And there appears to be some debate about the topic. I think it revolves around the issue of just  what’s  in an image. So let’s unpack that.

So, the claim is that ‘images’ are processed 60K faster than text. And, of course, trying to find the actual citation has been an exercise in futility. But can we address it on principle? I’ll suggest we can.

Let’s take it apart. What’s in an image?  Is it a photo? A diagram? An infographic? Even a video?  I think we need to nail it down. So let’s talk about the presumed cognitive processing that goes on.

Let’s start with photos. They capture context. If it’s a familiar context, processing likely happens almost immediately. But others? Not so fast. Unless a context has already been established, a picture isn’t going to make much sense. That is, we probably should account for the context processing as part of the story.

As soon as we get to diagrams, the story gets more complex. Ok, Jill Larkin and Herb Simon once opined on  Why a Diagram is worth 10000 words, but it’s about mapping conceptual relationships to spatial relationships. And I’ll still argue you need to process the elements, and the relationships, before you understand it. So it’s not instantaneous.

And, yes, there’s the lovely example in Don Norman’s  Things That Make Us Smart, where he showed how a relationship was more quickly processed than the equivalent text description (he kindly didn’t mention it was from my Ph.D. thesis ;). Yet not all text can be replaced by images.  What would convey Nike’s  Just Do It  slogan more concisely than that text? You’d have to establish the relationship  first. E.g. their ‘swoop’.  As I mentioned, familiar words are processed essentially as images, as whole words, not being processed by individual characters.

The same holds true for infographics, by the way. They’re not ‘grokked’ immediately. They need to be parsed in terms of message, and flow, and information. They’re a mashup of text and info, but that doesn’t make it any faster. Though they  may support retention, but we should use diagrams and images appropriately  with text.

Video’s even more complex. It’s a linear medium, as is text. And it’s powerful, but is it processed more efficiently? Again, I think it depends on what you’re saying. A video can be a narrated slide show. Is that faster than reading the text? I read faster than folks speak.

Which brings me to my take-home conclusion. A simple statement like “images processed 60K faster than text) is misleading.  What image? It all hinges on  what’s  in an image. Be vary wary of such claims. In the previous article, I provided some questions to ask yourself. And I may have to rant again about myths in general!

Upcoming TK2020’s new approach

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Amongst the conferences I go to (frequently the eLearning Guild events, others as invited or doing something) is ATD’s Techknowledge. And I’ll be there again this coming year (get 10% with this code: 30TK2020). And while I think both offerings are of interest, one is more problematic. So I’m asking your help in dealing with the upcoming TK2020’s new approach.

It’s in San Jose, which is always nice since it means I don’t have to get on a plane. (I don’t object, but I’d prefer to train or drive.). It’s at the beginning of February (5-7), which  can be a quiet time. Also, Downtown San Jose has some really nice dining options (e.g. the mega food court at San Pedro Square Market). And the weather’s unlikely to be icy or snowy. Maybe some rain, but tolerable temperatures. So it’s convenient all around.

One session I’m doing is a traditional one hour presentation. This is one I trialed on my local chapter, and I enjoyed it and it seemed they did too. It’s about how learning science suggests changes to curriculum and pedagogy. (Officially it’s “Transforming Learning: A Learning Science-Based Curriculum and Pedagogy.”) It’s very LXD, and I think there are some interesting and challenging observations in it. In particular, I’ll be bringing in the Free Energy principle and it’s implications about why learning can and should be transformative. And more.

The other session is something new in format. They’re being adventurous, and kudos to them. They’re creating a suite of stages doing a variety of different themes (in their words):

  • In the Build area, you‘ll engage in hands-on learning and experimentation with the latest learning technologies.
  • The Disrupt area will feature ten hyper-focused facilitator-led conversations about industry issues.
  • At the Spark area you’ll find your next big idea through mini-sessions and discussions on emerging trends.
  • At the Connect area, you‘ll participate in structured topic or industry-focused networking with your peers.
  • The Advance area will allow you to hone your skills in specific areas by participating in accelerated, mini-sessions and discussions.
  • At the Explore area you‘ll examine case studies of named organizations for new ideas and inspiration. Play sparks creativity, and what you do here will ignite your potential.

My session is in the Disrupt area, and not surprisingly the topic is myths. Well, the official title is “Professionalism in Practice: Resisting Hype, Myths, Superstitions, and Misconceptions.” The issue is what to do!

I have 30 minutes. And I can see several things to do. The question is, which one is most appealing/interesting, and effective? So I’m hoping you’ll help determine what I should be doing for the  upcoming TK2020’s new approach.

Some options:

Make it just a Question and Answer session. I could open it up to whatever people would like to hear about myths and how to be prepared to withstand them.

Another option would be to do it as a slightly game show event; I did this with Jay Cross one time. I’d pick nine topics, put them up on the screen in a 3 x 3 grid, and address them in the order people choose.

In the spirit of the description, I’m  not going to just give a presentation, but “hyper-focused” means what? Maybe wrap a format around several top myths? (How many can I do in 30 minutes?) Asking attendees “what makes this appealing”? Then a brief explanation of why it’s wrong. Then “what might you do instead?” And, finally “how can you prevent this?”

Or, focusing on the ‘resist’, I could crowd-source ideas around a general model of resistance. Asking, in some order: “Where do myths come from?” “Who can you trust?” “What’s good evidence?” “How would you do it yourself?” “What’s a practical process we can use?”

Or something else?

Obviously, I’m not short of ideas, but converging is challenging, I can see pluses and minuses on each. So, I thought I’d ask you all what you think about how I should adapt to the upcoming TK2020’s new approach. Feedback not just welcome, but eagerly solicited!

So, c’mon, give me a gift here! (Obligatory season imprecation; or of course an interesting project for your organization ;).  And happy holidays to you and yours, and all the best for the coming year.

Content systems not content packages

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In a conversation last week (ok, an engagement), the topic of content systems came up. Now this is something I’ve argued for before, in several ways. For one, separate content from how it’s delivered. And, pull content together by rules, not hardwired. And it’s also about the right level of granularity. It’s time to revisit the message, because I thought it was too early, but I think the time is fast coming when we can look at this.

This is in opposition to the notion of pre-packaged content. MOOCs showed that folks want to drill in to what they need. Yet we still pull everything together and launch it as a final total solution. We are moving to smaller chunks (all for the better; even if it is burdened with a misleading label). But there’s more.

The first point is about content models. That we should start designing our content into smaller chunks. My heuristic is the smallest thing you’d give one person or another. My more general principle is that resolves to breaking content down by it’s learning role: a concept model is different than an example is different than a practice.

This approach emerged from an initiative on an adaptive learning system I led. It now has played out as a mechanism to support several initiatives delivering content appropriately. For one, it was supporting different business products from the same content repository. For another it was about delivering the right thing at the right time.

Which leads to the second point, about being able to pick and deliver the right thing  for the context.  This includes adaptive systems for learning, but also context-based performance support. With a model of the learner, the context, and the content, you can write rules that put these together to optimally identify the right thing to push.

You can go further. Think of two different representatives from the same company visiting a client. A sales person and a field engineer are going to want different things in the same location. So you can add a model of ‘role’ (though that can also be tied to the learner model).

There’s more, of course. To do this well requires content strategy, engineering, and management. Someone put it this way: strategy is what you want to deliver, engineering is how, and management is overseeing the content lifecycle.

Ultimately, it’s about moving from hardwired content to flexible delivery. And that’s possible and desirable. Moreover, it’s the future. As we see the movement from LMS to LXP, we realize that it’s about delivering just what’s needed when useful. Recognizing that LXPs are portals, not about creating experiences, we see the need for federated search.

There’s more: semantics means we can identify what things are (and are not), so we can respond to queries. With chatbot interfaces, we can make it easier to automate the search and offering to deliver the right thing to the right person at the right time.

The future is here; we see it in web interfaces all over the place. Why aren’t we seeing it yet in learning? There are strong cognitive reasons (performance support, workflow learning, self-directed and self-regulated learning).  And the technology is no longer the limitation. So let’s get on it. It’s time to think content systems, not content packages.

 

How do you drive yourself?

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How do I drive myself? I was asked that in a coaching session. The question is asking how I keep learning. There are multiple answers, which I’ve probably talked about before, but I’ll reflect here. I think it’s important to regularly ask: “how do you drive yourself?”

As it’s the end of the year, my conversant was looking at professional development. It’s the time to ask for next year’s opportunities, and the individual was breaking out of our usual conversation to talk about this topic. And so he asked me what  I  did.

And my first response, which I’ve practiced consciously at least since grad school, is that I accept challenges. That is, I take on tasks that stretch me. (It might be that ‘sucker’ tattoo on my forehead, but note that my philanthropic bandwidth is pretty stretched. ;). This is professionally  and personally.

That is, I look to find challenges that I think are within my reach, but not already my grasp. Or, to put it another way, in my Zone of Proximal Development. Accepting assignments or engagements where, with effort, I can succeed,  but it’s not guaranteed.

Which means, of course, that there’s risk as well. Occasionally, I do screw up. Which I  really really hate to do. Which is a driver for me to push out of my comfort zone and succeed. Or, at least, learn the lesson.

There’s more, of course. One thing I did started with my first Palm Pilot (the Palm III, the accompanying case is still my toiletry bag!).  I had to justify to myself the expense, so I made sure that I really used it to success. This was part of the driver of the thinking that showed up in Designing mLearning,  how to complement cognition. IA instead of AI, so to speak.

I also live the mantra “stay curious, my friends”. I’m still all too easily distracted by a new idea, but I don’t think that’s a bad thing. Well, as long as it’s balanced with executing against the challenges.

That’s how I drive myself. So, how do you drive yourself?

Direct Instruction and Learning Experience Design

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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!

Theory or Research?

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There’s a lot of call for evidence-based methods (as mentioned yesterday): L&D, learning design, and more. And this is a good thing. But…do you want to be basing your steps on a particular empirical study, or the framework within which that study emerged? Let me make the case for one approach. My answer to theory or research is theory. Here’s why.

Most research experiments are done in the context of a theoretical framework. For instance, the work on worked examples comes from John Sweller’s Cognitive Load theory. Ann Brown & Ann-Marie Palincsar’s experiments on reading were framed within Reciprocal Teaching, etc. Theory generates experiments which refine theory.

The individual experiments illuminate aspects of the broader perspective. Researchers tend to run experiments driven by a theory. The theory leads to a hypothesis, and then that hypothesis is testable. There  are some exploratory studies done, but typically a theoretical explanation is generated to explain the results. That explanation is then subject to further testing.

Some theories are even meta-theories! Collins & Brown’s Cognitive Apprenticeship  (a favorite) is based upon integrating several different theories, including the Reciprocal Teaching, Alan Schoenfeld’s work on examples in math, and the work of Scardemalia & Bereiter on scaffolding writing. And, of course, most theories have to account for others’ results from other frameworks if they’re empirically sound.

The approach I discuss in things like my Learning Experience Design workshops is a synthesis of theories as well. It’s an eclectic mix including the above mentioned, Cognitive Flexibility, Elaboration, ARCS, and more. If I were in a research setting, I’d be conducting experiments on engagement (pushing beyond ARCS) to test my own theories of what makes experiences as engaging and effective. Which, not coincidentally, was the research I was doing when I  was  an academic (and led to  Engaging Learning). (As well as integration of systems for a ubiquitous coaching environment, which generates many related topics.)

While individual results, such as the benefits of relearning, are valuable and easy to point to, it’s the extended body of work on topics that provides for longevity and applicability. Any one study may or may not be directly applicable to your work, but the theoretical implications give you a basis to make decisions even in situations that don’t directly map. There’s the possibility to extend to far, but it’s better than having no guidance at all.

Having theories to hand that complement each other is a principled way to design individual solutions  and design processes. Similarly for strategic work as well (Revolutionize L&D) is a similar integration of diverse elements to make a coherent whole. Knowing, and mastering, the valid and useful theories is a good basis for making organizational learning decisions. And avoiding myths!  Being able to apply them, of course, is also critical ;).

So, while they’re complementary, in the choice between theory or research I’ll point to one having more utility. Here’s to theories and those who develop and advance them!

Skating to where L&D needs to be

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“I skate to where the puck is going to be, not where it has been.” – Wayne Gretsky

This quote, over-used to the point of being a cliché, is still relevant. I was just reading Simon Terry’s amusing and insightful  post on ‘best practices’ (against them, of course), and it reminded me of this phrase. He said “Best practices are often racing to where someone used to be”, and that’s critical. And I’ve argued against best practices, and I want to go further.

So he’s right that when we’re invoking best practices, we’re taking what someone’s already done, and trying to emulate it. He argues that they’ve already probably iterated in making it work,  in their org. Also, that by the time you do, they’ve moved on. They may even have abandoned it!  Which isn’t, directly, my complaint.

My argument against best practices is that they worked for them, but their situation’s different. The practice may be antithetical to your culture. And thinking that you can just graft it on is broken. Which is kind of Simon’s point to.    And he’s right that if you do get it working, you find that the time it hass taken means it’s already out of date.

So my suggestion has been to look to best principles:  why  did it work?  Abstract out the underlying principle, and figure out how (or even whether) to instantiate that in your own organization.  You’d want to identify a gap in your way of working, search through possible principles, identify one that matches, and work to implement it.  That makes more sense.  And, of course, it should be a fix that even if it takes time, will be meaningful.

But now I want to go further. I argue for comprehending the affordances of new technology to leapfrog the stage of replicating what was done in the old. Here I’m making a similar sort of argument. What I want orgs to do is to define an optimal situation, and then work to that! Yes, I know it sounds like a fairytale, but I think it’s a defensible approach. Of course, your path there will differ from another’s (there’s no free lunch :), but if you can identify what a good state for your org would be, you can move to it. It involves incorporating many relevant principles in a coherent whole. Then you can strategize the path there from your current content.

The point is to figure out what the  right future is, and skate there, not back-filling the problems you currently have. Beyond individual principles to a coherent whole. Proactive instead of reactive. That seems to make sense to me. Of course, I realize the other old cliché, “when. you’re up to your ass in alligators”, but maybe it’s time to change the game a bit more fundamentally. Maybe you shouldn’t be in the swamp anyway?  I welcome your thoughts!

 

Redesigning Learning Design

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Of late, a lot of my work has been designing learning design. Helping orgs transition their existing design processes to ones that will actually have an impact. That is, someone’s got a learning design process, but they want to improve it. One idea, of course, is to replace it with some validated design process. Another approach, much less disruptive, is to find opportunities to fine tune the design. The idea is to find the minimal set of changes that will yield the maximal benefit. So what are the likely inflection points?  Where am I finding those spots for redesigning?  It’s about good learning.

Starting at the top, one place where organizations go wrong right off the bat is the initial analysis for a course. There’s the ‘give us a course on this’, but even if there’s a decent analysis the process can go awry. Side-stepping the big issue of performance consulting (do a reality check: is this truly a case for a course), we get into working to create the objectives. It’s about how you work with SMEs. Understanding what they can,  and can’t, do well means you have the opportunity to ensure that you get the right objectives to design to.

From there, the most meaningful and valuable step is to focus on the practice. What are you having learners  do, and how can you change that?  Helping your designers switch to good  assessment writing is going to be useful. It’s nuanced, so the questions don’t  seem that different from typical ones, but they’re much more focused for success.

Of course, to support good application of the content to develop abilities, you need the right content!  Again, getting designers to understand what the nuances of useful examples from just stories isn’t hard but rarely done. Similarly knowing why you want  models and not just presentations about the concept isn’t fully realized.

Of course, making it an emotionally compelling experience has learning impact as well. Yet too often we see the elements just juxtaposed instead of integrated. There  are systematic ways to align the engagement and the learning, but they’re not understood.

A final note is knowing when to have someone work alone, and when some collaboration will help.  It’s not a lot, but unless it happens at the right time (or happens at all) can have a valuable contribution to the quality of the outcome.

I’ve provided many resources about better learning design, from my 7 step program white paper  to  my deeper elearning series for Learnnovators.  And I’ve a white paper about redesigning as well. And, of course, if you’re interested in doing this organizationally, I’d welcome hearing from you!

One other resource will be my upcoming workshop at the Learning Solutions conference on March 25 in Orlando, where we’ll spend a day working on learning experience design, integrating engagement and learning science.  Of course, you’ll be responsible for taking the learnings back to your learning process, but you’ll have the ammunition for redesigning.  I’d welcome seeing you there!

The pain of learning

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My dad, in his last years, lost the use of his hands and most of his hearing. It seemed like he then gave up. I finally challenged him on it, and he said “when you’re in constant pain…”.  And I got it.

So, turns out I’ve a misbehaving disk in my back, and it started pressing on the nerve over the summer. Pain scales are 1-10; this ultimately got to an 8 when I was trying to walk or even stand (from my lower back down my leg to my toes). Tried physio, non-steroidal anti-inflammatories, and then a steroid pack; nope. The ‘big hammer’ option was a cortisone injection, and that happened. Better yet, it knocked it back; down to 1). Er, for some six – eight weeks, then it came back. They gave me another one sooner than they were supposed to, but it hasn’t worked (ok, it’s knocked it to a 6 on average, but…this isn’t tolerable).  And my point here isn’t that I’m looking for sympathy, but to (of course) talk about the learnings. Because, despite the physical pain, there are learnings (good and bad).

Because there’re a physiological basis (pressing on the nerve), I’ve stuck with treatments likely to minimize the inflammation. I haven’t looked at a chiropractor nor acupuncture. Given that the current approaches are failing, those may come up, though I’m expecting surgery as the nuclear option. Not that I’m eager (to the contrary!). One learning is how close minded I can be about exploring alternative solutions. On the other hand, as it shoots down the leg into my foot, I’ve learned a lot more about physiology!

In the course of navigating airports and the like while in the throws of this (long story), I  also  found that the milk of human kindness can be diluted by pain. When you’re muttering obscenities under your breath because of the knives that accompany every step, clueless actions on the part of others – like stopping suddenly, blocking access, or even just bad signage – can earn muffled imprecations and aspersions on parentage and intelligence.  I’ve always tried to maintain ‘situational awareness’ (and know I’ve failed at times), but I highly recommend it!

On the other hand, when sitting (the only time it settles down), I’m expanding on my growing recognition over the past years that I have no idea what anyone else may be going through.  I’m sure my limping through parking lots and stores can be perceived as congenital damage or wear and tear. There’s no real way for anyone to know how much someone else hurts. We don’t have meters over our heads or icons.

And I’m increasingly grateful!  That may sound odd, but this experience is teaching me (and I am trying to find the positive).  Finding ways to minimize it is an ongoing experimentation. The support of my family helps, and I’ve learned (some) to ask for help.  But even an involuntary and undesirably challenging experience still is an experience.

Also, as much as it may be hard to struggle to find time and motivation for exercise, you learn to miss it. It seems every time I start taking a serious stab at diet and exercise, something goes wrong!  It’s almost like I’m not supposed to; and I know that’s wrong.  (I’ve also learned to secretly suspect my pain doctor is a closet sadist, but that’s the pain talking. :)

This is definitely  not ‘hard fun‘, to be clear. This is much more lemonade.  Fingers crossed that this, too, will pass. And if you do see me limping around, cut me some slack ;).  But also, please understand that it’s hard to know what other people are going through, and do your best to be sympathetic. Which seems like the right message for this time of year anyway. Wishing you and yours all the best for the holidays and the new year!