Learnlets
Clark Quinn's Learnings about Learning
(The Official Quinnovation blog)

25 February 2015

mLearning more than mobile elearning?

Clark @ 6:17 am

Someone tweeted about their mobile learning credo, and mentioned the typical ‘mlearning is elearning, extended’ view. Which I rejected, as I believe mlearning is much more (and so should elearning be).  And then I thought about it some more.  So I’ll lay out my thinking, and see what you think.

I have been touting that mLearning could and should be focused, as should P&D, on anything that helps us achieve our goals better. Mobile, paper, computers, voodoo, whatever technology works.  Certainly in organizations.  And this yields some interesting implications.

So, for instance, this would include performance support and social networks.  Anything that requires understanding how people work and learn would be fair game. I was worried about whether that fit some operational aspects like IT and manufacturing processes, but I think I’ve got that sorted.  UI folks would work on external products, and any internal software development, but around that, helping folks use tools and processes belongs to those of us who facilitate organizational performance and development.  So we, and mlearning, are about any of those uses.

But the person, despite seeming to come from an vendor to orgs, not schools, could be talking about schools instead, and I wondered whether mLearning for schools, definitionally, really is about only supporting learning.  And I can see the case for that; that mlearning in education is about using mobile to help people learn, not perform.  It’s about collaboration, for sure, and tools to assist.

Note I’m not making the case for schools as they are, a curriculum rethink definitely needs to accompany using technology in schools in many ways.  Koreen Pagano wrote this nice post separating Common Core teaching versus assessment, which goes along with my beliefs about the value of problem solving.  And I also laud Roger Schank‘s views, such as the value (or not) of the binomial theorem as a classic example.

But then, mobile should be a tool in learning, so it can work as a channel for content, but also for communication, and capture, and compute (e.g. the 4C’s of mlearning).  And the emergent capability of contextual support (the 5th C, e.g. combinations of the first four).  So this view would argue that mlearning can be used for performance support in accomplishing a meaningful task that’s part of an learning experience.

That would take me back to mlearning being more than just mobile elearning, as Jason Haag has aptly separated.  Sure, mobile elearning can be a subset of mlearning, but not the whole picture. Does this make sense to you?

11 February 2015

Rethinking Redux

Clark @ 9:04 am

Last week I wrote about Rethinking, how we might want and need to revise our approaches, and showed a few examples of folks thinking out of the box and upending our cherished viewpoints.  I discovered another one (much closer to ‘home’) and tweeted it out, only to get a pointer to another.  I think it’s worth looking at these two examples that help make the point that maybe it’s time for a rethink of some of our cherished beliefs and practices.

The first was a pointer from a conversation I had with the proprietor of an organization with a new mobile-based coaching engine.  Among the things touted was that much of our thinking about feedback appears to be wrong.  I was given a reference and found an article that indeed upends our beliefs about the benefits of feedback.

The article investigates performance reviews, and finds them lacking, citing one study that found:

“a meta-analysis of 607 studies of performance evaluations and concluded that at least 30% of the performance reviews ended up in decreased employee performance.”

30% decrease performance?  And that’s not including the others that are just neutral.  That’s a pretty bad outcome!  Worse, the Society for Human Resource Management is cited as stating  “90% of performance appraisals are painful and don’t work“.  In short, one of the most common performance instruments is flawed.

As a consequence of tweeting this out, a respondent pointed to another article that he was reminded of.  This one upends the notion that we’re good at rating others’ behavior: “research has demonstrated that each of us is a disturbingly unreliable rater of other people’s performance”.  That is, 360 degree reviews, manager reviews, etc., are fundamentally based upon review by others, and they’re demonstrably bad at it.  The responses given have reliable biases that makes the data invalid.

As a consequence, again, we cannot continue as we are:

“we must first stop, take stock, and admit to ourselves that the systems we currently use to reveal our people only obscure them”

This is just like learning styles: there’s no reliable data that it works, and the measurement instrument used is flawed. In short, one of the primary tools for organizational improvement is fundamentally broken.  We’re using industrial age tools in an information age.

What’s a company to do?  The first article quoted Josh Bersin when saying “companies need to focus very heavily on ‘collaboration, professional development, coaching and empowering people to do great things’“.  This is the message of the Internet Time Alliance and an outflow of the Coherent Organization model and the L&D Revolution.  There are alternatives that are more respectful of how people really think, work, and learn, and consequently more effective.  Are you ready to rethink?

#itashare

5 February 2015

Agile Bay Area #LNDMeetup Mindmap

Clark @ 8:05 am

I’ve been interested in process, so I attended this month’s Bay Area Learning Design Meetup that showcased LinkedIn’s work on Agile using Scrum for learning design. It was very nice of them to share the specifics of their process, and while there were more details than time permitted to cover, it was a great beginning to understand the differences.

Basically, a backlog is kept of potential new projects.  They’re prioritized and a subset is chosen as the basis of the sprint and put on the board.  Then for two weeks they work on hitting the elements on the board, with a daily standup meeting to present where they’re at and synchronize.  At the end they demo to the stakeholders and reflect.  As part of the reflection, they’re supposed to change something for the next iteration.

There’re different roles: a project owner who’s the ‘client’ in a sense (and a relation to who may be the end client).  There is a Scrum master who’s responsible for facilitating the group through the steps, and then the team, which should be small but at least represent all the necessary roles to execute whatever is being accomplished.

When I asked about scope, they said that they’ve found they can do about 100 story points (which are empirical) in a sprint, and they may distribute that across some elearning, some job aids, whatever.  They didn’t seem too eager to try to quantify that relative to other known metrics, and I understand it’s hard, particularly in the time they had.  Here’s the Mindmap:

(null)

 

Allen Interactions also discussed their SAM project (which I know and like), but the mind map didn’t match too well to their usual diagram (only briefly shown at the end), and I ran out of time trying to remedy. It’s better just to look at the diagram ;).

 

3 February 2015

Rethinking

Clark @ 7:58 am

(in the future)
Dr. Melik: You mean there was no deep fat? No steak or cream pies? Or hot fudge?

Dr. Agon: Those were thought to be unhealthy, precisely the opposite of what we now know to be true.

In Woody Allen’s Sleeper about someone who wakes up in the future, one of the jokes is that all the things we thought were true are turned on their head.  I was talking with my colleague Jay Cross in terms of why we’re not seeing more uptake of the opportunities for L&D to move out of the industrial age, and one of the possible explanations is satisfaction with the status quo. And I was reminded of several articles I’ve read that support the value of rethinking.

In Sweden, on principled reasons they decided that the model of prosecuting the prostitute wasn’t fair. She was, they argued, a victim. Instead, they decided to punish the solicitation of the service, a complete turn around from the previous approach.  It has reduced sex trafficking, for one outcome. Other countries are now looking at their model and some have already adopted it.

In Portugal, which was experiencing problems with drugs, they took the radical step of decriminalizing them, and setting them up with treatment.  While it’s not a panacea, it has not led to the massive increase in usage that was expected.  Which is a powerful first step.  It may be a small step toward undoing some of the misconceptions about addiction which may be emerging.

And in Denmark there was an experiment in doing away with road signs. The premise was that folks with regulations will trust the regulations to work. If you remove them, they have to go back to assessing the situation, and that they’ll drive safer.  It appears, indeed, to be the case.

I could go on: the food pyramid, cubicles… more and more ideas are being shown to be misguided if not out and out wrong.  And the reason I raise this is to suggest that complacency about anything, accepting the received wisdom, may not be helpful.  Patti Shank recently wrote about the burden of having an informed opinion, and I think we need to take ownership of our beliefs, and I think that’s right.

There are lots of approaches to get out of the box: appreciative inquiry, positive deviance, double loop learning, the list goes on.  Heck, there’s even the silly and overused but apt cliche about the definition of insanity. The point being that regular reflection is part of being a learning organization.   You need to be looking at what you’re doing, what others are doing, and what others are saying.  Continual improvement is part of the ongoing innovation that today’s organization needs to thrive.

Yes, we can’t query everything, but if we have an area of responsibility, e.g. in charge of learning strategy, we owe it to know what  alternative approach might be. And we certainly should be looking at what we’re doing and what impact it’s having.  Measuring just efficiency instead of impact?  Being an order taker and not investigating the real cause?  Not looking at the bigger picture?  Ahem.  I am positing, via the Revolution,  that L&D isn’t doing near what it could and should, and we are via the Manifesto that what it is doing, it is doing badly.  So, what’s the response?  I’ve done the research to suggest that there’s a need for a rethink, and I’m trying to foster it. So where do we go from here?  Where do you go from here?  Steak, anyone?

#itashare

28 January 2015

What I do, don’t do, and why

Clark @ 8:51 am

My background is in learning technology design, leveraging a deep background (read: Ph.D.) in cognition, and long experience with technology.  I have worked as a learning game designer/developer, researcher and academic, project leader on advanced applications, program manager, and more.  More recently, I’ve been working with many different types of organizations including not-for-profits, Fortune 500, small-medium enterprises, government, education, and more with workshops, project deliverables, strategic consulting, writing, and more.

This crosses formal learning, mobile learning, serious games, performance support, content systems, social and informal learning, and more.  I reckon there’s a benefit to 30+ years of being fortunate enough to be at the cutting edge, and I work hard to maintain currency with developments in learning, technology, and organizational needs.I like to think I’m pretty good at it, and I am for hire.  I’ve worked in most of the obvious ways: fixed-fee deliverables when we can define a scope, hourly/daily rates when it’s uncertain, and on a retainer basis to keep my expertise ‘on tap’.

What I have not done, is work on a commission basis. That is, I don’t push someone’s solution on you for a cut of the action. I’ve cut a few such deals in the early days, particularly for long-term clients/partners, but to no avail.  And I’m fine with that. In fact, that’s now my stance.

There are reasons for this both principled, and pragmatic. On principle, I want to remain able to say Solution X is the best, as I truly believe it to be true, and not be swayed that Solution Y would offer me some financial reward.  I believe my independence is in my clients best interests.  This holds true in systems, vendors, individuals, whatever.  I want you to be able to trust what I say, and know that it’s coming from my expertise, not some other influence.  When you get my expert opinion, it is to your needs alone.  And, pragmatically, I’m not a salesperson, it’s not in my nature.

I also don’t design solutions and outsource development. I have trusted partners I can work with, so I don’t need solicitations to show me your skills.  I’m sure your team is awesome too, but I don’t want to take the time to vet your abilities, and I certainly wouldn’t represent them without scrutiny. When I have needs, I’ll reach out.

So I welcome hearing from you when you want some guidance on reviewing your processes, assessing or designing your strategy, ramping up your capabilities, considering markets, looking for collateral, and more. This is as true for vendors as other organizations.  But don’t expect me to learn about your solutions (particularly for free), and flog them to others.   Fair enough?  Am I missing something?

27 January 2015

70:20:10 and the Learning Curve

Clark @ 8:09 am

My colleague Charles Jennings recently posted on the value of autonomous learning (worth reading!), sparked by a diagram provided by another ITA colleague, Jane Hart (that I also thought was insightful). In Charles’ post he also included an IBM diagram that triggered some associations.

So, in IBM’s diagram, they talked about: the access phase where learning is separate, the integration where learning is ‘enabled’ by work, and the on-demand phase where learning is ‘embedded’. They talked about ‘point solutions’ (read: courses) for access, then blended models for integration, and dynamic models for on demand. The point was that the closer to the work that learning is, the more value.

However, I was reminded of Fits & Posner’s model of skill acquisition, which has 3 phases of cognitive, associative, and autonomous learning. The first, cognitive, is when you benefit from formal instruction: giving you models and practice opportunities to map actions to an explicit framework. (Note that this assumes a good formal learning design, not rote information and knowledge test!)  Then there’s an associative stage where that explicit framework is supported in being contextualized and compiled away.  Finally, the learner continues to improve through continual practice.

I was initially reminded of Norman & Rumelhart’s accretion, restructuring, and tuning learning mechanisms, but it’s not quite right. Still, you could think of accreting the cognitive and explicitly semantic knowledge, then restructuring that into coarse skills that don’t require as much conscious effort, until it becomes a matter of tuning a finely automated skill.

721LearningCurveThis, to me, maps more closely to 70:20:10, because you can see the formal (10) playing a role to kick off the semantic part of the learning, then coaching and mentoring (the 20) support the integration or association of the skills, and then the 70 (practice, reflection, and personal knowledge mastery including informal social learning) takes over, and I mapped it against a hypothetical improvement curve.

Of course, it’s not quite this clean. While the formal often does kick off the learning, the role of coaching/mentoring and the personal learning are typically intermingled (though the role shifts from mentee to mentor ;). And, of course, the ratios in 70:20:10 are only a framework for rethinking investment, not a prescription about how you apply the numbers.  And I may well have the curve wrong (this is too flat for the normal power law of learning), but I wanted to emphasize that the 10 only has a small role to play in moving performance from zero to some minimal level, that mentoring and coaching really help improve performance, and that ongoing development requires a supportive environment.

I think it’s important to understand how we learn, so we can align our uses of technology to support them in productive ways. As this suggests, if you care about organizational performance, you are going to want to support more than the course, as well as doing the course right.  (Hence the revolution. :)

#itashare

20 January 2015

Getting strategic means getting scientific

Clark @ 8:13 am

I’ve been on a rant about learning design for a few posts, but I ended up talking about how creating a better process is part of getting strategic.  The point was that our learning design has to embody what’s know about how we learn, e.g. a learning engineering.  And it occurs to me that getting our processes structured to align with how we work is part of a bigger picture of how our strategies have to similarly be informed.

So, as part of the L&D Revolution I argue we need to have, I’m suggesting organizations, and consequently L&D, need to be aligned with how we think, work, and learn. So our formal learning initiatives (used only when they are really needed) need to be based upon learning science. And performance support similarly needs to reflect how we process information, and, importantly, things we don’t do well and need support for.  The argument for informal and social learning similarly comes from our natural approaches, and similarly needs to provide facilitation for where things can and do go wrong.

And, recursively, L&D’s processes need to similarly reflect what we do, and don’t, do well.  So, just as we should provide support for performers to execute, communicate, collaborate, and continue to improve (why L&D needs to become P&D), we need to make sure that we practice what we preach.  And a scientific method means we need to measure what we’re doing, not just efficiency, but effectiveness.

It’s time that L&D gets out of the amateur approach, and starts getting professional. Which means understanding the organization’s goals, rejecting requests that are nonsensical, examining what we do, using technology in sophisticated ways (*cough* content engineering *cough*), and more.  We need to know about how we think, work, and learn, and apply it to what we do. We’re about people, after all, so it’s about time we understood the science in our field, and quit thinking that our existing practices (largely from an industrial age) are inherently relevant. We must be scrutable, and that means we must scrutinize.  Time to get to work.

#itashare

14 January 2015

It’s the process, silly!

Clark @ 8:32 am

So yesterday, I went off on some of the subtleties in elearning that are being missed.  This is tied to last weeks posts about how we’re not treating elearning seriously enough.  And part of it is in the knowledge and skills of the designers, but it’s also in the process. Or, to put it another way, we should be using steps and tools that align with the type of learning we need. And I don’t mean ADDIE, though not inherently.

So what do I mean?  For one, I’m a fan of Michael Allen’s Successive Approximation Model (SAM), which iterates several times (tho’ heuristically, and it could be better tied to a criterion).  Given that people are far less predictable than, say, concrete, fields like interface design have long known that testing and refinement need to be included.  ADDIE isn’t inherently linear, certainly as it has evolved, but in many ways it makes it easy to make it a one-pass process.

Another issue, to me, is to structure the format for your intermediate representations so that make it hard to do aught but come up with useful information.  So, for instance, in recent work I’ve emphasized that a preliminary output is a competency doc that includes (among other things)  the objectives (and measures), models, and common misconceptions.  This has evolved from a similar document I use in (learning) game design.

You then need to capture your initial learning flow. This is what Dick & Carey call your instructional strategy, but to me it’s the overall experience of the learner, including addressing the anxieties learners may feel, raising their interest and motivation, and systematically building their confidence.  The anxieties or emotional barriers to learning may well be worth capturing at the same time as the competencies, it occurs to me (learning out loud ;).

It also helps if your tools don’t interfere with your goals.  It should be easy to create animations that help illustrate models (for the concept) and tell stories (for examples).  These can be any media tools, of course. The most important tools are the ones you use to create meaningful practice. These should allow you to create mini-, linear-, and branching-scenarios (at least).  They should have alternative feedback for every wrong answer. And they should support contextualizing the practice activity. Note that this does not mean tarted up drill and kill with gratuitous ‘themes’ (race cars, game shows).  It means having learners make meaningful decisions and act on them in ways like they’d act in the real world (click on buttons for tech, choose dialog alternatives for interpersonal interactions, drag tools to a workbench or adjust controls for lab stuff, etc).

Putting in place processes that only use formal learning when it makes sense, and then doing it right when it does make sense, is key to putting L&D on a path to relevancy.   Cranking out courses on demand, focusing on measures like cost/butt/seat, adding rote knowledge quizzes to SME knowledge dumps, etc are instead continuing down the garden path to oblivion. Are you ready to get scientific and strategic about your learning design?

31 December 2014

Reflections on 15 years

Clark @ 7:32 am

For Inside Learning & Technologies 50th edition, a number of us were asked to provide reflections on what has changed over the past 15 years.  This was pretty much the period in which I’d returned to the US and took up with what was kind of a startup and led to my life as a consultant.  As an end of year piece, I have permission to post that article here:

15 years ago, I had just taken a step away from academia and government-sponsored initiatives to a new position leading a team in what was effectively a startup. I was excited about the prospect of taking the latest learning science to the needs of the corporate world. My thoughts were along the lines of “here, where we have money for meaningful initiatives, surely we can do something spectacular”. And it turns out that the answer is both yes and no.

The technology we had then was pretty powerful, and that has only increased in the past 15 years. We had software that let us leverage the power of the internet, and reasonable processing power in our computers. The Palm Pilot had already made mobile a possibility as well. So the technology was no longer a barrier, even then.

And what amazing developments we have seen! The ability to create rendered worlds accessible through a dedicated application and now just a browser is truly an impressive capability. Regardless of whether we overestimated the value proposition, it is still quite the technology feat. And similarly, the ability to communicate via voice and video allows us to connect people in ways once only dreamed of.

We also have rich new ways to interact from microblogs to wikis (collaborative documents). These capabilities are improved by transcending proximity and synchronicity. We can work together without worrying about where the solution is hosted, or where our colleagues are located. Social media allow us to tap into the power of people working together.

The improvements in mobile capabilities are also worth noting. We have gone from hype to hyphens, where a limited monochrome handheld has given way to powerful high-resolution full-color multi-channel always-connected sensor-rich devices. We can pretty much deliver anything anywhere we want, and that fulfills Arthur C. Clarke’s famous proposition that a truly advanced technology is indistinguishable from magic.

Coupled with our technological improvements are advances in our understanding of how we think, work, and learn. We now have recognition about how we act in the world, about how we work with others, and how we best learn. We have information age understandings that illustrate why industrial age methods are not appropriate.

It is not truly new, but reaching mainstream awareness in the last decade and more is the recognition that the model of our thinking as formal and logical is being updated. While we can work in such ways, it is the exception rather than the rule. Such thinking is effortful and it turns out both that we avoid it and there is a limit to how much deep thinking one can do in a day. Instead, we use our intuition beyond where we should, and while this is generally okay, it helps to understand our limitations and design around them.

There is also a spreading awareness of how much our thinking is externalized in the world, and how much we use technology to support us being effective. We have recognized the power of external support for thinking, through tools such as checklists and wizards. We do this pretty naturally, and the benefits from good design of technology greatly facilitate our ability to think.

There is also recognition that the model of individual innovation is broken, and that working together is far superior to working alone. The notion of the lone genius disappearing and coming back with the answer has been replaced by iterations on top of previous work by teams. When people work together in effective ways, in a supportive environment, the outcomes will be better. While this is not easy to effect in many circumstances, we know the practices and culture elements we need, and it is our commitment to get there, not our understanding, that is the barrier.

Finally, our approaches to learning are better informed now. We know that being emotionally engaged is a valued component in moving to learning experience design. We understand the role of models in supporting more flexible performance. We also have evidence of the value of performing in context. It is not news that information dump and knowledge test do not lead to meaningful skill acquisition, and it is increasingly clear that meaningful practice can. It is also increasingly clear that, as things move faster, meaningful skills – the ability to make better decisions – is what is going to provide the sustainable differentiator for organizations.

So imagine my dismay in finding that the approaches we are using in organizations are largely still rooted in approaches from yesteryear. While we have had rich technology opportunities to combine with our enlightened understanding, that is not what we are seeing. What we see is still expectations that it is done in-the-head, top-down, with information dump and meaningless assessment that is not tied to organizational outcomes. And while it is not working, demonstrably, there seems little impetus to change.

Truly, there has been little change in our underlying models in 15 years. While the technology is flashier, the buzz words have mutated, and some of the faces have changed, we are still following myths like learning styles and generational differences, we are still using ‘spray and pray’ methods in learning, we are still not taking on performance support and social learning, and perhaps most distressingly, we are still not measuring what matters.

Sure, the reasons are complex. There are lots of examples of the old approaches, the tools and practices are aligned with bad learning practices, the shared metrics reflect efficiency instead of effectiveness, … the list goes on. Yet a learning & development (L&D) unit unengaged with the business units it supports is not sustainable, and consequently the lack of change is unjustifiable.

And the need is now more than ever. The rate of change is increasing, and organizations now have more need to not just be effective, but they have to become agile. There is no longer time to plan, prepare, and execute, the need is to continually adapt. Organizations need to learn faster than the competition.

The opportunities are big. The critical component for organizations to thrive is to couple optimal execution (the result of training and performance support) with continual innovation (which does not come from training). Instead, imagine an L&D unit that is working with business units to drive interventions that affect key KPIs. Consider an L&D unit that is responsible for facilitating the interactions that are leading to new solutions, new products and services, and better relationships with customers. That is the L&D we need to see!

The path forward is not easy but it is systematic and doable. A vision of a ‘performance ecosystem’ – a rich suite of tools to support success that surround the performer and are aligned with how they think, work, and learn – provides an endpoint to start towards. Every organization’s path will be different, but a good start is to start doing formal learning right, begin looking at performance support, and commence working on the social media infrastructure.

An associated focus is building a meaningful infrastructure (hint: one all-singing all-dancing LMS is not the answer). A strategy to get there is a companion effort. And, ultimately a learning culture will be necessitated. Yet these components are not just a necessary component for L&D, they are the necessary components for a successful organization, one that can be agile enough to adapt to the increasing rate of change we are facing.

And here is the first step: L&D has to become a learning organization. Mantras like ‘work out loud’, ‘fail fast’, and ‘reflect’ have to become part of the L&D culture. L&D has to start experimenting and learning from the experiments. Let us ensure that the past 15 years are a hibernation we emerge from, not the beginning of the end.

Here’s to change for the better.  May 2015 be the best year yet!

17 December 2014

Why L&D?

Clark @ 8:33 am

One of the concerns I hear is whether L&D still has a role.  The litany is that they’re so far out of touch with their organization, and science, that it’s probably  better to let them die an unnatural death than to try to save them. The prevailing attitude of this extreme view is that the Enterprise Social Network is the natural successor to the LMS, and it’s going to come from operations or IT rather than L&D.  And, given that I’m on record suggesting that we revolutionize L&D rather than ignoring it, it makes sense to justify why.  And while I’ve had other arguments, a really good argument comes from my thesis advisor, Don Norman.

Don’s on a new mission, something he calls DesignX, which is scaling up design processes to deal with “complex socio-technological systems”.   And he recently wrote an article about why DesignX that put out a good case why L&D as well.  Before I get there, however, I want to point out two other facets of his argument.

The first is that often design has to go beyond science. That is, while you use science when you can, when you can’t you use theory inferences, intuition, and more to fill in the gaps, which you hope you’ll find out later (based upon later science, or your own data) was the right choice.  I’ve often had to do this in my designs, where, for instance, I think research hasn’t gone quite far enough in understanding engagement.  I’m not in a research position as of now, so I can’t do the research myself, but I continue to look at what can be useful.  And this is true of moving L&D forward. While we have some good directions and examples, we’re still ahead of documented research.  He points out that system science and service thinking are science based, but suggests design needs to come in beyond those approaches.   To the extent L&D can, it should draw from science, but also theory and keep moving forward regardless.

His other important point is, to me, that he is talking about systems.  He points out that design as a craft works well on simple areas, but where he wants to scale design is to the level of systemic solutions.  A noble goal, and here too I think this is an approach L&D needs to consider as well.  We have to go beyond point solutions – training, job aids, etc – to performance ecosystems, and this won’t come without a different mindset.

Perhaps the most interesting one, the one that triggered this post, however, was a point on why designers are needed.  His point is that others have focuses on efficiency and effectiveness, but he argued that designers have empathy for the users as well.  And I think this is really important.  As I used to say the budding software engineers I was teaching interface design to: “don’t trust your intuition, you don’t think like normal people”.  And similarly, the reason I want L&D in the equation is that they (should) be the ones who really understand how we think, work, and learn, and consequently they should be the ones facilitating performance and development. It takes an empathy with users to facilitate them through change, to help them deal with fears and anxieties dealing with new systems, to understand what a good learning culture is and help foster it.

Who else would you want to be guiding an organization in achieving effectiveness in a humane way?   So Don’s provided, to me, a good point on why we might still want L&D (well, P&D really ;) in the organization. Well, as long as they also addressing the bigger picture and not just pushing info dump and knowledge test.  Does this make sense to you?

#itashare #revolutionizelnd

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