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Developing L&D

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One of the conversations I’ve been having is how to shift organizations into modern workplace learning. These discussions have not been with L&D, but instead targeted directly at organizational strategy. The idea is to address a particular tactical goal as  part of a strategic plan, and to do so in ways that both embody and develop learning and a collaboration culture. The topic was then raised about how you’d approach an L&D unit under this picture. And I wondered whether you’d use the same approach to developing L&D as part of L&D operations. The answer isn’t obvious.

So what I’m talking about here would be to take an L&D initiative, and do it in this new way, with coaching and scaffolding. The overall model involves a series of challenges with support.  You’re developing some new organizational capability, and you’d scaffold the process initially with some made up or pre-existing challenges.  Then you gradually move to real challenges. So, does this model change for L&D?

My thought was that you’d take an L&D initiative, and something out of the ordinary, an experiment.  Depending on the particular organization’s context, it might be performance support, or social media, or mobile, or…  Then you define an experiment, and start working on it. To develop the skills to execute, you give a team (or teams) some initial challenges: e.g. critique a design. Then more complex ones, so: design a solution to a problem someone else has solved. Finally, you give them the real task, and let them go (with support).

This isn’t slow; it’s done in sprints, and still fits in between other work. It can be done in a matter of weeks.  In doing so, you’re having the team collaborate with digital tools (even if/while working F2F, but ideally you have a distributed team). Ultimately, you are developing both their skills on the process itself  and on working together in collaborative ways.

In talking this through, I think this makes sense for L&D as well, as long as it’s a new capability that’s being developed.  This is an approach that can rapidly develop new tactical skills and change to a culture oriented towards innovation: experimentation and iterative moves. This is the future, and yet it’s unlike most of the way L&D operates now.

Most importantly, I think, is that this opportunity is on the table now for a brief period. L&D can internally develop their understanding and ability of the new ways of working as a step towards being an organization-wide champion. The same approach taken within  L&D then can be taken and used elsewhere.  But it takes experience with this approach before you can scale it.  Are you ready to make the shift?

Realities 360 Reflections

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So, one of the two things I did last week was attend the eLearning Guild‘s Realities 36o conference.  Ostensibly about Augmented Reality (AR)  and Virtual Reality (VR), it ended up being much more about VR. Which isn’t a bad thing, it’s probably as much a comment on the state of the industry as anything.  However, there were some interesting learnings for me, and I thought I’d share them.

First, I had a very strong visceral exposure to VR. While I’ve played with Cardboard on the iPhone (you can find a collection of resources for Cardboard  here), it’s not quite the same as a full VR experience.  The conference provided a chance to try out apps for the HTC Vive, Sony Playstation VR, and the Oculus.  On the Vive, I tried a game where you shot arrows at attackers.  It was quite fun, but mostly developed some motor skills. On the Oculus, I flew an XWing fighter through an asteroid field and escorted a ship and shoot enemy Tie-fighters.  Again, fun, but mostly about training my motor skills in this environment.

It was the one I think on the Vive that gave me an experience.  In it, you’re floating around the International Space Station. And it was very cool to see the station and experience the immersion of 3D, but it was very uncomfortable.  Partly because I was trying to fly around (instead of using handholds), my viewpoint would fly through the bulkhead doors. However, the positioning meant that it gave the visual clues that my chest was going through the metal edge.  This was extremely disturbing to me!  As I couldn’t control it well, I was doing this continually, and I didn’t like it. Partly it was the control, but it was also the total immersion. And that was impressive!

There are empirical results that demonstrate better learning outcomes for VR, and certainly  I can see that particularly, for tasks inherently 3D. There’s also another key result, as was highlighted in the first keynote: that VR is an ’empathy’ machine. There have been uses for things like understanding the world according to a schizophrenic, and a credit card call center helping employees understand the lives of card-users.

On principle, such environs should support near transfer when designed to closely mimic the actual performance environment. (Think: flight or medicine simulators.)  And the tools are getting better. There’s an app that allows you to take photos of a place to put into Cardboard, and game engines (Unity or Unreal or both) will now let you import AutoCAD models.  There was also a special camera that could sense the distances in a space and automatically generate a model of it.  The point being that it’s getting easier and easier to generate VR environments.

That, I think, is what’s holding AR back.  You can fairly easily use it for marker or location based information, but actually annotating the world visually is still challenging.  I still think AR is of more interest, (maybe just to me), because I see it eventually creating the possibility to see the causes and factors  behind the world, and allow us to understand it better.  I could argue that VR is just extending sims from flat screen to surround, but then I think about the space station, and…I’m still pondering that. Is it revolutionary or just evolutionary?

One session talked about trying to help folks figure out when VR and AR made sense, and this intrigued me. It reminded me that I had tried to characterize the affordances of virtual worlds, and I reckon it’s time to take a stab at doing this for VR and AR.  I believed then that I was able to predict when virtual worlds would continue to find value, and I think results have borne that out.  So, the intent is to try to get on top of when VR and AR make sense.  Stay tuned!

What is the Future of Work?

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which is it?Just what is the Future of Work  about? Is it about new technology, or is it about how we work with people?  We’re seeing  amazing new technologies: collaboration platforms, analytics, and deep learning. We’re also hearing about new work practices such as teams, working (or reflecting) out loud, and more.  Which is it? And/or how do they relate?

It’s very clear technology is changing the way we work. We now work digitally, communicating and collaborating.  But there’re more fundamental transitions happening. We’re integrating data across silos, and mining that data for new insights. We can consolidate platforms into single digital environments, facilitating the work.  And we’re getting smart systems that do things our brains quite literally can’t, whether it’s complex calculations or reliable rote execution at scale. Plus we have technology-augmented design and prototyping tools that are shortening the time to develop and test ideas. It’s a whole new world.

Similarly, we’re seeing a growing understanding of work practices that lead to new outcomes. We’re finding out that people work better when we create environments that are psychologically safe, when we tap into diversity, when we are open to new ideas, and when we have time for reflection. We find that working in teams, sharing and annotating our work, and developing learning and personal knowledge mastery skills all contribute. And we even have new  practices such as agile and design thinking that bring us closer to the actual problem.  In short, we’re aligning practices more closely with how we think, work, and learn.

Thus, either could be seen as ‘the Future of Work’.  Which is it?  Is there a reconciliation?  There’s a useful way to think about it that answers the question.  What if we do either without the other?

If we use the new technologies in old ways, we’ll get incremental improvements.  Command and control, silos, and transaction-based management can be supported, and even improved, but will still limit the possibilities. We can track closer.  But we’re not going to be fundamentally transformative.

On the other hand, if we change the work practices, creating an environment where trust allows both safety  and accountability, we can get improvements whether we use technology or not. People have the capability to work together using old technology.  You won’t get the benefits of some of the improvements, but you’ll get a fundamentally different level of engagement and outcomes than with an old approach.

Together, of course, is where we really want to be. Technology can have a transformative amplification to those practices. Together, as they say, the whole is greater than the some of the parts.

I’ve argued that using new technologies like virtual reality and adaptive learning only make sense  after you first implement good design (otherwise you’re putting lipstick on a pig, as the saying goes).  The same is true here. Implementing radical new technologies on top of old practices that don’t reflect what we know about people, is a recipe for stagnation.  Thus, to me, the Future of Work starts with practices that align with how we think, work, and learn, and are augmented with technology, not the other way around.  Does that make sense to you?

FocusOn Learning reflections

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If you follow this blog (and you should :), it was pretty obvious that I was at the FocusOn Learning conference in San Diego last week (previous 2 posts were mindmaps of the keynotes). And it was fun as always.  Here are my reflections on what happened a bit more, as an exercise in meta-learning.

There were three themes to the conference: mobile, games, and video.  I’m pretty active in the first two (two books on the former, one on the latter), and the last is related to things I care and talk about.  The focus led to some interesting outcomes: some folks were very interested in just one of the topics, while others were looking a bit more broadly.  Whether that’s good or not depends on your perspective, I guess.

Mobile was present, happily, and continues to evolve.  People are still talking about courses on a phone, but more folks were talking about extending the learning.  Some of it was pretty dumb – just content or flash cards as learning augmentation – but there were interesting applications. Importantly, there was a growing awareness about performance support as a sensible approach.  It’s nice to see the field mature.

For games, there were positive and negative signs.  The good news is that games are being more fully understood in terms of their role in learning, e.g. deep practice.  The bad news is that there’s still a lot of interest in gamification without a concomitant awareness of the important distinctions. Tarting up drill-and-kill with PBL (points, badges, and leaderboards; the new acronym apparently)  isn’t worth significant interest!  We know how to drill things that must be, but our focus  should be on intrinsic interest.

As a side note, the demise of Flash has left us without a good game development environment. Flash is both a development environment and a delivery platform. As a development environment  Flash had a low learning threshold, and yet could be used to build complex games.  As a delivery platform, however, it’s woefully insecure (so much so that it’s been proscribed in most browsers). The fact that Adobe couldn’t be bothered to generate acceptable HTML5 out of the development environment, and let it languish, leaves the market open for another accessible tool. And Unity or Unreal provide good support (as I understand it), but still require coding.  So we’re not at an easily accessible place. Oh, for HyperCard!

Most of the video interest was either in technical issues (how to get quality and/or on the cheap), but a lot of interest was also in interactive video. I think branching video is a real powerful learning environment for contextualized decision making.  As a consequence the advent of tools that make it easier is to be lauded. An interesting session with the wise Joe Ganci (@elearningjoe) and a GoAnimate guy talked about when to use video versus animation, which largely seemed to reflect my view (confirmation bias ;) that it’s about whether you want more context (video) or concept (animation). Of course, it was also about the cost of production and the need for fidelity (video more than animation in both cases).

There was a lot of interest in VR, which crossed over between video and games.  Which is interesting because it’s not inherently tied to games or video!  In short,  it’s a delivery technology.  You can do branching scenarios, full game engine delivery, or just video in VR. The visuals can be generated as video or from digital models. There was some awareness, e.g. fun was made of the idea of presenting powerpoint in VR (just like 2nd Life ;).

I did an ecosystem presentation that contextualized all three (video, games, mobile) in the bigger picture, and also drew upon their cognitive and then L&D roles. I also deconstructed the game Fluxx (a really fun game with an interesting ‘twist’). Overall, it was a good conference (and nice to be in San Diego, one of my ‘homes’).

A learning meta-story

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Been thinking about how to generate meaningful learning in optimal (read: concise but effective) ways. And a lot of what I’ve been thinking about involves contextualized meaningful practice (no surprise there, eh?).  So how might this play out?  Thought I’d use a story to convey the experience I’m thinking of:

Pat logs on to the system, and notes that it’s time to take a crack at the next assignment.  In it is a setup  with a role for Pat to play.  The story details a business situation: the organization, it’s current status, and a situation that’s occurred that requires an action.  The details are exaggerated, so it’s a dire situation with a lot riding on the outcome. The instructions are phrased in the form of an email directly from the CEO, with pointers to some folks to talk to for assistance.

The necessity is for Pat to create a plan to address the need.  In this case, it’s a marketing plan for a new product that has been the focus of most of the organization’s effort.  With old products facing receding sales, this product  has to succeed.  The existing plan, legacy of a departed individual, is ‘old school’ and an up-to-date approach is needed.  The indicated need  is heavily aligned with this week’s topic of social-media marketing.

Pat starts work to create a document to send to the CEO. This includes  making ‘calls’ (viewing videos of quick messages from the various roles involved including the product manager, the financial officer) to find out the  parameters which are in play and to get expert knowledge.  There are also some marketing materials available.  

In  previous assignments there were support tools about creating documents and about marketing plans, but this time  such  support isn’t available.  Pat realizes  that this being a more advanced cut through the topic, it’s time to start taking ownership of the process.  The CEO has  asked for an interim plan report  before creating the entire marketing plan, and  Pat uses previous materials and adapts them to  create the  plan.

Pat will get feedback from the CEO to incorporate in the plan before putting together the final submission.  Ultimately, the success of the plan will be presented, and then feedback on the details of Pat’s submission.  The document creation will be  evaluated separately and in the context of previous documents required across this particular topic and previous ones, while the marketing plan itself will be evaluated in terms of it’s response to the context.  

Several things to note here. The contextualized performance requirement isn’t unique, of course.  This very much draws upon similar work seen in Roger Schank’s Story-Centered Curriculum and Goal-Based Scenarios. It differs in that subsequent assignments might use totally separate story settings.  It’s similar also to work like Bransford, et al’s Anchored Instruction.  The notion of embedding performance in context reflects research that shows abstract instruction doesn’t transfer as well. My own proposal (research, anyone?) is that the story should complete before the conceptual feedback is presented, or indeed that the story outcome includes the conceptual feedback in an intrinsic way.

The second important thing is that the document creation details are assessed separately, and tracked across other such assignments that might appear anywhere. The point is to develop meta-skills like digital document creation (and others such as presentations, working in groups, research, etc) as well as the domain skills.

I believe that we need learners to create complex work products that are challenging to auto-mark, because the outcomes are necessary.  This means that you need people in the learning loop; totally asynchronous isn’t going to work to develop rich capabilities. I’m trying to figure out ways to approximate that with as little human intervention as possible because pragmatically we have more learning to achieve than we have resources to achieve that (at least until we get our priorities right ;).

 

Human Learning is Not About to Change Forever

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In my inbox was an announcement about a new white paper with the intriguing title  Human Learning is About to Change Forever.  So naturally I gave up my personal details to download a copy.  There are nine claims in the paper, from the obvious to the ridiculous. So I thought I’d have some fun.

First, let’s get clear.  Our learning runs on our brain, our wetware. And that’s not changing in any fundamental way in the near future. As a famous article once had it: phenotypic plasticity triumphs over genotypic plasticity (in short, our human advantage has gained    via  our ability to adapt individually and learn from each other, not through  species evolution).   The latter takes a long time!

And as a starting premise, the “about to” bit implies these things are around the corner, so that’s going to be a bit of my critique. But nowhere near  all of it.  So here’s a digest of the  nine claims and my comments:

  1. Enhanced reality tools will transform the learning environment.  Well, these tools will  certainly augment the learning environment  (pun intended :). There’s evidence that VR leads to better learning outcomes, and I have high hopes for AR, too. Though is that a really fundamental transition? We’ve had VR and virtual worlds for over a decade at least.  And is VR a evolutionary or revolutionary change from simulations? Then they go on to talk about performance support. Is that transforming learning? I’m on record saying contextualized learning (e.g. AR) is the real opportunity to do something interesting, and I’ll buy it, but we’re a long way away. I’m all for AR and VR, but saying that it puts learning in the hands of the students is a design issue, not a technology issue.
  2. People will learn collaboratively, no matter where they are.  Um, yes, and…?  They’re already doing this, and we’ve been social learners for as long as we’ve existed. The possibilities in virtual worlds to collaboratively create in 3D I still think is potentially cool, but even as the technology limitations come down, the cognitive limitations remain. I’m big on social learning, but mediating it through technology strikes me as just a natural step, not transformation.
  3. AI will banish intellectual tedium. Everything is  awesome.  Now we’re getting a wee bit hypish. The fact that software can parse text and create questions is pretty impressive. And questions about semantic knowledge aren’t going to transform education. Whether the questions are developed by hand, or by machine, they aren’t likely on their own to lead to new abilities to do. And AI is not yet to the level (nor will it be soon) where it can take content and create compelling activities that will drive learners to apply knowledge and make it meaningful.
  4. We will maximize our mental potential with wearables and neural implants. Ok, now we’re getting confused and a wee bit silly. Wearables are cool, and in cases where they can sense things about you and the world means they can start doing some very interesting AR. But transformative? This still seems like a push.  And neural implants?  I don’t like surgery, and messing with my nervous system when you still don’t really understand it? No thanks.  There’s a lot more to it than managing to adjust firing to control limbs. The issue is again about the semantics: if we’re not getting meaning, it’s not really fundamental. And given that our conscious representations are scattered across our cortex in rich patterns, this just isn’t happening soon (nor do I want that much connection; I don’t trust them not to ‘muck about’).
  5. Learning will be radically personalized.  Don’t you just love the use of superlatives?  This is in the realm of plausible, but as I mentioned before, it’s not worth it until we’re doing it on  top of good design.  Again, putting together wearables (read: context sensing) and personalization will lead to the ability to do transformative AR, but we’ll need a new design approach, more advanced sensors, and a lot more backend architecture and semantic work than we’re yet ready to apply.
  6. Grades and brand-name schools won‘t matter for employment.  Sure, that MIT degree is worthless! Ok, so there’s some movement this way.  That will actually be a nice state of affairs. It’d be good  if we started focusing on competencies, and build new brand names around real enablement. I’m not optimistic about the prospects, however. Look at how hard it is to change K12 education (the gap  between what’s known and what’s practiced hasn’t significantly diminished in the past decades). Market forces may change it, but the brand names will adapt too, once it becomes an economic necessity.
  7. Supplements will improve our mental performance.  Drink this and you’ll fly! Yeah, or crash.  There are ways I want to play with my brain chemistry, and ways I don’t. As an adult!  I really don’t want us playing with children, risking potential long-term damage, until we have a solid basis.  We’ve had chemicals support performance for a while (see military use), but we’re still in the infancy, and here I’m not sure our experiments with neurochemicals can surpass what evolution has given us, at least not without some pretty solid understanding.  This seems like long-term research, not near-term plausibility.
  8. Gene editing will give us better brains.  It’s  alive!  Yes, Frankenstein’s monster comes to mind here. I do believe it’s possible that we’ll be able to outdo evolution eventually, but I reckon there’s still not everything known about the human genome  or the human brain. This similarly strikes me as a valuable long term research area, but in the short term there are so many interesting gene interactions we don’t yet understand, I’d hate to risk the possible side-effects.
  9. We won‘t have to learn: we‘ll upload and download knowledge. Yeah, it’ll be  great!  See my comments above on neural implants: this isn’t yet ready for primetime.  More importantly, this is supremely dangerous. Do I trust what you say you’re making available for download?  Certainly not the case now with many things, including advertisements. Think about downloading to your computer: not just spam ads, but viruses and malware.  No thank you!  Not that I think it’s close, but I’m not convinced we can ‘upgrade our operating system’ anyway. Given the way that our knowledge is distributed, the notion of changing it with anything less than practice seems implausible.

Overall, this is reads like more a sci-fi fan’s dreams than a realistic assessment of what we should be preparing for.  No, human learning isn’t going to change forever.  The ways we learn, e.g. the tools we learn with are changing, and we’re rediscovering how we really learn.

There are better guides available to what’s coming in the near term that we should prepare for.  Again, we need to focus on good learning design, and leveraging technology in ways that align with how our brains work, not trying to meld the two.  So, there’re my opinions, I welcome yours.

The change is here

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For a number of years now (at least six), I’ve been beating the drum about the need for organizations to be prepared to address change. I’ve argued that things are happening faster, and that organizations are going to have to become more agile.  Now we’re seeing the evidence that the change has arrived.

a change purseTwo recent reports highlight the awareness. Gallup released a report  on The State of the American Workplace recently that talks about the lack of engagement at work.  Deloitte also released a report,  Rewriting the rules in the digital age,  that documents trends shifting the office environment.  With different perspectives, they both overlap in discussing the importance of culture.  It’s about creating an environment where people are empowered and enabled to contribute.

The Gallup  report concludes with new behaviors for leaders and managers.  The first point for leaders is to use data and focus on culture. This, to me, involves leveraging technology and creating an environment. L&D could be leading using performance data captured through the  ExperienceAPI, and facilitating the culture shift in courses and developing coaching. Their prescription for managers is  to move to be coaches (and again, L&D should be both developing the skills and facilitating the processes).  And employees need to take ownership of their own development, which means L&D should focus on both meta-learning and ensuring resources (curation  and creation) as well.

The second report is the more interesting one for me, because it’s about the trends and the ways to adapt.  The top two trends are the Organization of the future (c.f. The Workplace of the Future  :) and Careers and learning.  The former is about redesigning organizations to become agile.  The latter is about a redefinition of learning.  They are a wee bit old-school, however, as while they do discuss innovation throughout, it isn’t a core focus and their definition of learning doesn’t include informal learning.  It’s still a top-down model.  But again, clear opportunities for L&D.

The key leverage points, to me, are learning and technology.  And here I mean more self-directed and collaborative learning conducted not formally, but facilitated. Social learning really can’t be top-down!  Important technologies are for communicating and collaborating, as well as tools to search and find resources.

And while the focus is on HR, including recruitment and leadership, I reckon that L&D should have a key place here, as indicated. The world’s changing, and L&D needs to adapt.  It’s time to innovate L&D to support organizational innovation. Are you ready?

Learning Strategy Issues

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Online Educa logoThe other thing that I was involved in  at Online Educa in Berlin was a session on The Flexible Worker.  Three of us presented, each addressing one particular topic.  One presentation was  on collaborating to produce an elearning course on sleeping better, with the presenter’s firm demonstrating expertise in elearning, while the other firm had the subject matter expertise on sleep health. A second presentation was  on providing tools to trainers to devolve content development locally, addressing a problem with centrally-developed content.  My presentation was on the gaps between what L&D does and how our brains work, and the implications. And, per our design, issues emerged.

The format was interesting: our presentations were roughly 10 minutes each.  And we were using a tool (sli.do) to collect and rank questions. Then we had the audience work at their tables (in the round) to come up with their answers to the top questions, which we then collected and the panelists riffed on the outcomes.  We got through three questions as a group, and I thought the outcomes were quite interesting. In short, as a rapporteur at the closing business session, I suggested  that the topic ended up being about flexible work, not flexible working.

The top  question that emerged had to do with how to support effective search (after I expounded on problem with the notion that it all had to be in the head).  The sourced answers included crowd-sourcing the tags for finding objects, using a controlled vocabulary, and auto-analyzing the content to determine tags.  I suggest a hybrid solution, in general. The interesting thing here was the audience picking up on the need to go beyond courses and start looking at resources.

The next question was how to move from a training to a performance culture.  And it was another exciting development to hear them thinking this way. The solutions offered included coaching, supporting the importance of self-learning (meta-learning, yay!), and working both top-down  and bottom-up. I also suggested that measuring was a likely catalyst that could begin to draw attention to outcomes  (just as  I reckon  competencies are the lever  in higher-ed).

The third question was about ensuring quality in a localized learning environment (e.g. user-generated content).  The concern was that the knowledge of learning design wouldn’t necessarily be widespread.  Suggestions included making the content editable for collaborative improvements, or using rankings, and scaffolding of improvement through the community. Here too, a focus on learning itself could assist.

What’s encouraging  to me is that each of these questions was really about moving to a transformative viewpoint.  The audience was clearly thinking ‘beyond the course’.  They were focusing on supporting performers in learning, and resources, and leveraging the community, all activities consonant with the revolution.

An interesting aside came in the closing session. Several folks were mentioning a need for change, and an audience member asked “why?”  He was a consultant, and his clients already seemed to be moving forward. I suggested he was seeing the best, and that many folks were not there (mentioning the Towards Maturity data as well as the problems I identified in the beginning of the Revolution book.  And it’s a problem that too many people don’t yet see the missed opportunities and don’t feel the pain (and are frankly not looking).

So, there are opportunities to start taking small steps in the direction of taking on a bigger perspective and making the role of L&D more strategic.  It first takes an awareness of the problems (my old line: “L&D isn’t doing near what it could and should, and what it  is doing it is doing badly, other than that things are fine” :), and then a strategy to move forward. The strategy depends on where the organization is to begin with, but there are systematic principles to guide progress.  That’s what I  do, after all!  It’s nice to see awareness growing. So, are you ready to start taking some positive steps?

 

Thoughts on Learning Design Strategy

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learning design strategy questionsAt the DevLearn conference, I ran a Morning Buzz on Learning Design Strategy. I’m happy to say that the participants threw in lots of ideas, and I thought they were worth capturing. I started with a set of questions to address, so I’ll go through their comments in roughly that order (though we didn’t exactly follow this structure):

What  is learning design strategy?

I had in mind the approach taken by an organization to their learning design.  Attendees suggested it’s your goals and approach, ensuring you are delivering effectively.  It’s also your review approach, and metrics.  These are all elements that indeed contribute to strategy.

What gaps are we seeing in  learning design strategy?

The participants  offered up a suite of places that were problems, including aligning with organizational goals and access to support measuring impact, both of which are indeed strategic issues.  They also raised problems with prioritization of the demands, the need to move beyond just courses, and the  lack of learning design knowledge. All are real problems.

What do we need to be able to improve?

The audience offered up a number of suggestions.  For one, there was a desire for strategies (probably more tactics) for doing beyond ‘the event’.  Support for selling changes in the way of doing things was mentioned as well.  The shift to self-learning was mentioned, leading to concern over how to support this.  Attendees also mentioned a need of awareness in designing ‘backwards‘. Finally, a culture of learning was expressly discussed.

What are possible solutions?

The participants  offered a suite of suggestions. One was adopting a learn-apply-perform model, which another termed a learn-practice-demo. Both were getting at the need for active practice and an ability to actually demonstrate performance.  There was also a mention of looking to social networks and peer recommendations to lower the demand and facilitate self-learning.  A culture shift was suggested, supported by the methods used to teach! A final solution was to move quickly to mentoring, which implicitly suggests including mentoring  in the design.

Steps to take to move forward?

I also wanted to know what how they might move forward, and what they needed.  Two clear suggestions emerged.  One was for examples, and I reckon both of better learning designs, and approaches to implement those learning designs in organizations.  The other was for tools. Here it was clear that they weren’t talking about tools to develop learning, but tools to support them doing good design, and following processes.

At the end I left with mixed feelings. It’s good to know that the problems I see are reflected in what the practitioners reports; we see the same problems  It’s also sad that these problems exist.  I do believe that the Serious eLearning Manifesto is one piece of support.  And I’ve written on practices (e.g. with SMEs), but it’s clear that some practical scaffolding would help. I’ve worked with a few organizations, but I’m struggling to find ways to help more.  (Maybe this is the topic of my next book?)  So, what ideas do  you  have?

(I’m offering a webinar next week that will address these issues, if you’re serious about making changes.)

Measuring Culture Change

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Someone recently asked how you would go about measuring culture change, and I thought it’s an interesting question.  I’ll  think ‘out loud’ about what might be the possibilities.  A  learning culture is optimal for organizational innovation and agility, and it’s likely that not all elements are already in place.  So it’s plausible that you’d want to change, and if you do, you’d like to know how it’s going.

I think there are two major categories of measures: direct and indirect. Direct measures are ones that are impacting the outcomes you’re looking for, and indirect ones are steps along the way. Say, for instance, one desirable outcome of a learning culture would be, well, learning!  In this case, I mean the broad sense of learning: problems solved, new designs generated, research answering questions.  And indirect would be activity likely to yield that outcome. It could be engagement, or social interaction, or…  If we think of it in a Kirkpatrickian sense, we want to generate the indirect activity, and then measure the actual business impact.

What direct measures might there be?  I can see time to solve customer problems or problems solved per time.  And/or I might look at the rate of research questions answered.  Or the rate of new product generation.  Of course, if you were expecting other outcomes from your culture initiative, you’d naturally want aligned methods.   You could just be concerned with employee engagement, but I’m somewhat inclined (and willing to be wrong) to think about what the outcome of increased engagement would be.  It could also be retention or recruitment, if those are your goals.

These latter – engagement, recruitment, retention – are also possible indirect measures.  They indicate that things are better. Another indirect but more targeted measure might be the amount of collaboration happening (e.g. the use of collaboration tools) or even activity in social networks.  Those have been touted as the benefits of building community in social media, and those are worthwhile as well.

As a process, I think about what I might do  before, during, and after any culture change initiative.  I’d probably want a baseline to begin with, and then regular (if not continual) assessments as we go.  I’d take small steps, perhaps in one unit to begin, and monitor the impact, tuning as I go along.  Culture change is a journey, not an event, after all ;).

 

So ok, that’s off the top of my head, what say you?