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Clark Quinn’s Learnings about Learning

State of L&D Survey

30 July 2013 by Clark Leave a Comment

What is the current state of L&D, and where is it working (and not)?   Some are saying that things are largely okay, while others are suggesting that things must improve.   Where are we at?

The Learning & Performance Institute research suggests that L&D practitioners don‘t assess themselves as having all the skills they might need.   Charles Jennings‘ work with the 70:20:10 Forum is pushing the model that we could be focusing on a wider range of activities beyond courses.  Tony Bingham and Marcia Conner have pointed out the new roles we could be taking in their book The New Social Learning.  Are we on track?

I have previously written that the industry has to change. Rather than trust my instincts, however, I‘m fortunate in that ASTD itself is looking to have more up to date answers, and is partnering with me to ask some questions about the full suite of activities that are being undertaken. We‘ve collaborated to create a questionnaire to supplement their usual collections of research reports.   We do have an endgame on this; stay tuned.

We‘re asking a short suite of questions designed to understand a snapshot of how organizations are addressing learning needs.   These include questions about how effort is distributed across different activities, what pedagogical beliefs are being used, where the learning culture is at, and how outcomes are being measured.

We encourage you to both take it and promote it. We hope that through this, we can get a snapshot of where the industry believes itself to be and how we can continue to move it forward.

Please take the survey and encourage others to as well. Thanks!

2nd Loop Learning

24 July 2013 by Clark Leave a Comment

It used to be that the L&D model was to prepare people, then send them out to perform.  There would be some data collection from the result, including debriefing perhaps, and then the training and personnel would be reviewed.  In that sense, L&D was outside the performance loop, in a separate loop.  And that made sense is a world where couldn’t do on the job scrutiny, and things were more predictable. We’re not in that world anymore.

The world we’re in is changing faster: we’re getting more data, companies can move faster, and customers expect more.  And we now can have much more insight into what’s happening (and more’s on the way, courtesy of xAPI), and be much more closely coupled to performance.  What does this mean we can and should do?

I think it means a different loop relationship with performance, where a second loop is integrated on top of the loop of performance.  In this loop, L&D is more closely monitoring individual performance, looking for opportunities to support outcomes. L&D could be reviewing correlations between resource use and performance, finding those that are not performing as expected to remove or redesign, they can be looking at interactions to see how to facilitate, and they can be monitoring for emergent knowledge and skills that can be captured and possibly developed.

A concept from cybernetics is  double  loop  learning,  where you’re reviewing your goals as well as your methods, and it’s been a valuable contribution to thinking and action.  Here we’re reviewing our approaches to a goal, which is a synergistic concept.  And this is a role where L&D both gets more strategic in supporting business goals, more integrated into the operations by being more coupled to operations, and more facilitative in role by helping facilitate at the moment of need.  This, I will suggest, is a possible and necessary shift to the ways in which organizations can start being more nimble, and the way that L&D can be directly responsible for that shift. Does this make sense to you? And is this something you think can be done?

Performance Support isn’t (or shouldn’t be) cheap either!

23 July 2013 by Clark 4 Comments

A few posts ago I posited that formal learning should be expensive.  Then, as a consequence of my subsequent posts on social first and performance support second, I was in a discussion where the question was shouldn’t performance support be first.  It intrigued me, but my response was that while it’s not just about saving resources, using people is more appealing in general and given the expenses for developing performance support it should be a secondary response. So why do I say Performance Support (PS) shouldn’t be cheap?

First, there’s a lot that goes into good job aid design.  I visited a bank many years ago, and was investigating their processes.  During the course of it they mentioned a job aid, and after I examined it I pointed out that it did a good job of structuring the information process, and the employees I was talking to weren’t aware of how well it did.  However, it was structured to support getting the information, but not structured for effective use.  First, the employees were supposed to ask the questions by rote, which would lead to a bad customer experience. No one wants to interact with a person reading rote questions: that’s a role for tech.  Yet There wasn’t a lot of highlighting to help focus on the important points, and gradually support personalizing the communication.  It was graphically designed appropriately, with spacing and color, and informationally designed but not usably designed.

And that’s the point, there are nuances to usable design that you shouldn’t assume you can wing, so it takes time and skills to get it right.  You need to do the right analysis, right information design, graphic design, and usability design. You may also need to do the right information architecture, so it’s findable both by search and  browsing. If it’s not findable when needed, it’s not going to get used and won’t help.

Second, don’t assume you’re going to get it right the first time.  As Atul Gawande said in  The Checklist Manifesto, he iterated many times to refine simple checklists to support performance.  You’ll want to test and refine iteratively until you’ve documented that the design works and yields the desired reports.  Don’t assume (as we do with much elearning too) that  ‘if we build it, it is good’.  You need to test it in context, with real users, to see if it meets their needs. Really, the designer should ultimately be the user!

Yet often resources created by performers are useful. Why is that?  Because they’re in context, and are creating what they need.  It may still benefit from some support, but this shifts the L&D role to facilitation, not design. And this is good.

At the end, the more we can help people help themselves, the more overall help is being provided, so we’re optimizing our time and impact. And that’s what we want, right?

 

Supporting Work

18 July 2013 by Clark 2 Comments

A number of years ago, I discussed a useful model that talks about how we solve problems in the world.  In the piece, I talked about how when we can’t act, we try to find the answer (and if we do, we go back into action).  Then if we can’t find the answer, we have to go into a problem-solving mode: we need to do research, experiment, and generally discover the solution. If we find a solution we should update the resources to help other people find the answer rather than having to rediscover it.

ways to support workI was thinking about this in terms of the ways in which L&D can support this process, and started noting the ways in which we can help  besides courses.  I broke it up into two different forms of support: direct, and supporting the associated skills.

When we have an information need, we might need directories to people with various expertise (associated with Communities of Practice, presumably).  We might design or curate useful information resources (how-to videos, job aids), and occasionally, when a significant skill shift is needed, we might design courses.

There are associated skills here, so communicating successfully with the experts who have the answer, or information literacy to develop the performer’s ability to find the answers themselves.

If the answer doesn’t already exist, then we might support learner with tools about problem solving, and research and problem-solving skills, as well as communication skills again to deal successfully with collaborators.

Finally, when the answer is found,  might have tools to create resources and skills to edit existing resources.

First, this is by no means a complete list, as even in writing this I thought of design to create resources to support problem-solving, and information architecture to go along with information resources, and…you get the idea. The point is two-fold: we need to recognize how people actually act in the world, and we need to then find ways to support all the points of need, not just the ones we can design a course for.  There are  lots of opportunities!

Reshaping L&D

17 July 2013 by Clark 3 Comments

Jane Hart (one of my ITA colleagues) has laid out a proposal for the new services of the L&D department, and I think it resonates nicely with some thinking I’ve been having.  The point is that L&D has to shift, but the question is: “to where?”

So Jane posits 3 services:

  • Content production: designing and delivering courses and resources
  • Learning Concierge: address ad hoc or ongoing learning or performance problems
  • Connected Workplace: supporting continuous learning and performance improvement through knowledge sharing and collaboration

The first is most of what the L&D group does now, and overuses.  And the focus really  is on courses, though sometimes resources are developed.  The latter two, however, are real opportunities.

Increasingly, we can’t anticipate the unique needs our learners will have, and what we have to move towards supporting them ‘at will’.  It may be a pointer to a resource such as a book or person or video as opposed to designing a course.  We increasingly need to serve as curators.

Similarly, we need to serve as facilitators, helping people learn how to self-help by working ‘out loud’ when we find ways to help them, so they can start self-helping. We can and should be facilitating conversations, helping those who are having trouble being effective in communicating, and more.

As I suggested earlier, social learning may often be our first recourse (not off our radar), and performance support second. If formal learning is (or should be) expensive, it should only be used when we need a significant skill shift. Yes, there are times that it’ll be needed  (e.g. unskilled employees, highly regulated performances), but we need to have a much richer suite of support possibilities, and start more accurately targeting the assistance to the need (and measuring the impact).

Our goal should be to have a business impact, and a one-trick pony isn’t going to meet the rich complexity and rate of change we’re increasingly going to face.  So, as Jane concludes: “how ready are you to provide these new services?”

#itashare

Performance Support Second?

10 July 2013 by Clark 8 Comments

I previously argued that social should be our first recourse in addressing performance and learning needs.  Does that mean courses are then second? Let me suggest otherwise.

Once we’ve determined that social isn’t a solution to meeting the need, why wouldn’t we think of a course first?  Partly, because courses should be expensive.  But also, unless we absolutely need a course, we should look to performance support next.  Frankly, the learner ideally gets the minimal amount of help to get past their current gap, and if it’s a bit of information or decision support help, why would you make a course if you can avoid it?  It’s the least assistance principle  (or “what’s the least I can do for you” :), only providing what they need to get back to work.

Another way to look at it is to think that we’d rather put as much information in the world as possible.  We don’t  want to try to put information into people’s heads if we can avoid it.  It’s hard, and we’re not really good at it. We’re great pattern matchers and meaning makers, but really bad at remembering rote information or executing against rote procedures.  At these times, a job aid or wizard is just the ticket.

Job aids should be easier to keep up to date, and wizards too ideally are editable.  Eventually, they may become social too, as the Community of Practice takes responsibility for keeping them up to date, but I think that will likely always benefit from L&D facilitation.  Facilitation increasingly will be the role of L&D, I claim, and this is part of that path.

If you can’t find a way that the network might provide the solution, and you can’t find a performance support solution, then you should consider a course. If it’s a skill shift that’s needed.  But for agility, efficiency, and effectiveness, performance support should trump courses.  Done right.

So, I’m claiming that our design process in many instances should be social first, performance support second, and formal courses last.  What say you?

 

Social First!

9 July 2013 by Clark 5 Comments

I’m convincing myself that as performance consultants assisting our organizations moving forward, we need to start thinking differently.  And as an extreme version of this, let me start by saying we need to start thinking ‘social’ first.  When we’re facing a performance problem in the organization, our first resort should be to ask: “would a social solution solve this”?  Let me explain.

Social solutions basically suggest that we either tap into user-generated solutions, or reach out to people on the fly.  It might be recorded video or user-generated job aids.  It might be asking a SME via an expertise directory. Or it just might be tossing it out to our network.  It may even be asking for some collaboration on a unique situation.

Here’s the thing: social networks are more likely to be up-to-date, and better able to deal with one-off questions and unique situations than our formally designed solutions.  In situations where things are changing rapidly, formally designed solutions are not likely to be up to date with where things are, owing to the time to capture, process, and generate appropriate content. And unusual situations aren’t worth trying to anticipate. They’re likely to be too many to address.  And, as the rate of change accelerates, these situations are more likely.

Of course, this requires infrastructure, an appropriate culture, and facilitation, but that should be already accomplished if not underway.  We know that continual innovation is the only sustainable differentiator, and that this comes from creative friction (the myth of individual innovation is busted). The  important  outcomes are going to come from the social network, not from L&D.

Finally, formal is (or should be) expensive.  If we’re doing it right, the effort to help change someone’s skill set sufficiently is a prolonged effort.  We need to be looking for effective, agile, and efficient.  Formal isn’t the latter two (and too frequently not the former either).  We should hold formal as a last resort!

There  will be times when social isn’t the answer, but for a number of reasons social should be your first solution if possible. It’s effective, it’s agile, and it’s very efficient.  Anticipating quite the  social  reaction to this ;).

#itashare

Formal Learning is (or should be) Expensive!

2 July 2013 by Clark 7 Comments

It’s becoming clear to me that we’re making a big mistake in our thinking. We seem to think that formal learning is relatively cost-effective, and may even think that performance support and social are more costly.   Yet we need to realize that formal learning is likely our most costly approach!

To start with, we should be doing sufficient analysis to ensure that the need is indeed a skill shift. If it’s an information problem, it should be solved with a job aid. Courses are more expensive.  And we need to take the time that the skill shift really is needed; it’s not a motivation problem or some other problem. In other words, we need to take the time to identify what business problem this is solving that a course will affect, and the associated metric.  That takes time.

Then we need to design an intervention that will address that skill shift: we need to determine what the change in the workplace behavior needs to be to impact that metric, and then design an objective that reflects that needed behavior change.  This is not trivial: a poorly formed objective about knowledge, not behavior, isn’t going to have an impact on the business.

Then, to do formal learning well, you need appropriate and sufficient practice.   That takes time to design properly, ideally with scenarios or simulation-driven interactions.  And the practice needs to be aligned with the learner; it has to be meaningful to them.  Enough of them. This takes time.

Then we need to create an appropriate model to guide their behavior, and introduce it appropriately. And find meaningful examples that illustrate the concept being applied in context, across sufficient contexts.  This takes time, though no more time (once you determine a course is the answer) than other learning design once you get experienced in this more advanced way of designing.  And it takes development resources.

And, of course, if you’re not doing the above, why are you bothering? It’s not going to hit the mark.  We don’t, frankly, and to the extent we don’t, we undermine the  likelihood  that our interventions will have the desired impact.  The point being that courses should not be our first line of defense!

Rapid elearning is cheap and fast, but it’s not going to have any impact.  Most of what we do doesn’t have any impact. If we want to have impact, we have to do it right, and that’s not a cheap proposition.  We need to worry about measuring more than cost/bum, and worry about hitting the business goal.  Then we can truly determine whether we should go this route, rather than another.  But, seriously, you shouldn’t be throwing formal learning at a problem unless you’re willing to do it right. There are times it  will be the right answer, but right now we’re throwing too much money away.  Let’s stop, and do it right  when  it’s right.  And that will be both expensive  and worth it.

 

Designing Learning is a Probabilistic Exercise

26 June 2013 by Clark Leave a Comment

At the Guild’s recent mLearnCon, I was having a conversation in which I was reminded that designing performance interventions is a probabilistic exercise, and it occurred to me that we’re often not up front enough about it.  And we need to be.

When we start our design process with a performance vision, we have an idea of what ideal performance would be.  However, we make some assumptions about the performer and their ability to have comprehended our learning interventions and any resources we design or are available in the context.  We figure our learning was successful (if we’re doing it right, we’re  not letting them out of our mitts until they’ve demonstrated the ability to reliably perform what we need), and we figure our performance solutions are optimal and useful (and, again, we should test until we know).  But there are other mitigating factors.

In the tragic plane crash in the Tenerife’s – and pilots train as much as anybody – miscommunication (and status) got in the way.  Other factors like distraction, debilitating substances, sleep deprivation and the like can also affect performance.  Moreover, there’s some randomness in our architecture, basically.  We don’t do everything perfectly all the time.

But more importantly, beyond the actual performance, there’s a probability involved in our learning interventions.   Most of our research based results  raise the likelihood of the intervention affecting the outcome.  Starting with meaningful objectives, using model-based concepts, contextualized examples, meaningful practice, all that increases the probability.

This holds true with performance support, coaching/mentoring, and more.  Look, humans don’t have the predictable properties of concrete or steel.  We are much more complex, and consequently variable. That’s why I went from calling it cognitive engineering to cognitive design. And we need to be up front about it.

The best thing to do is use the very best solutions to hand; just as we over-engineer bridges to ensure stability (and, as Henry Petrovski points out in To Engineer is Human, on subsequent projects we’ll relax constraints until ultimately we get failure), we need to over-design our learning.  We’ve gotten slacker and slacker, but if it’s important (and, frankly, why else are we bothering), we need to do the right job.  And tarting up learning with production values isn’t the same thing.  It’s easier, since we just do it instead of having to test and refine, but it’s unlikely to lead to any worthwhile outcomes.

As I’ve argued before, better design doesn’t take longer, but there is a learning curve. Get over the curve, and start increasing the likelihood that your learning will have the impact you intend.

Defining Mobile

25 June 2013 by Clark 11 Comments

At the recent Guild mLearnCon  mobile learning event, I had a thought that seems to answer a long time debate.  The debate centers on the definition of a mobile device.  The feature/smart phone is obviously a candidate, and tablets seem pretty clearly included too, but the ongoing issue has been whether a laptop counts. And I may have finally discovered a way of looking at it that answers the question.

Eschewing the more abstract and academic definitions, the one that has most resonated with me has been Judy Brown’s.  As I recall it, her characteristics are:

  • small enough to fit in a pocket or purse,
  • you’re familiar with it,
  • instant on,
  • and a battery that will last all day.

And this has been pretty good, because most laptops don’t fit the latter criteria, their batteries didn’t used to be able to go all day.  However, this is a characteristic-based definition, e.g. about inherent properties of the device, and this can change. The new MacBook Airs, for instance, now have a battery that will last all day. And, even if the 13″ is too big, the 11″ or some other might soon fit the criteria. That is, we’re hitting a moving target.

What struck me the other day, however, was looking at it not from inherent properties of the devices, but from usage affordance, i.e. how one uses the device.  Because it struck me: to me, it’s not really a mobile device unless you can use it with two hands, standing up or in motion. More importantly, it has to be a natural usage: holding up a netbook with one hand and hunt-and-peck with one hand doesn’t qualify.  In short, if you can’t use it with two hands while moving, it’s not really mobile.

This strikes me as a way that will inherently allow new devices and new capabilities, yet still clearly distinguish what’s mobile and what’s not.  So, for instance, devices with keyboard that turns around and becomes a tablet?  A tablet’s mobile: hold with one hand, touch with the other.  A two-handed keyboard is not. Will this fall apart?  Probably, as the ultimate mobile test is whether it’s a device that goes with you  everywhere: to the market, to a party, even to the bathroom.  And some may be able to, but which ones really  do? Regularly?  If I had a small enough tablet, or iPod touch, probably, but the phone, yes!  However, in some contexts, e.g. work, a tablet might go with me to all my work contexts, and then it qualifies  if it meets the criteria: of being able to used  naturally,  standing up.

This, to me, seems to provide a better criteria, at least for now.  What say you?

 

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