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Clark Quinn’s Learnings about Learning

Signs of hope?

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Attending the SolutionsFest at the Learning Solutions conference last week, despite my earlier rant, I saw signs of hope.  A quick spot check revealed a number of approaches going above and beyond.

One direction I was pleased to see was a move to more performance support. I saw several solutions that were more focused on providing information as needed, or letting you  navigate to it, rather than thinking everything had to be ‘in the head’. This is definitely a promising sign.  They’re not hard to build, either.

The second promising sign was the use of scenarios. Several different solutions were focused on putting learners into contexts and asking them to perform. This is definitely the direction we need to see more of.  And, again, it’s not that hard to do!

One interesting takeaway was that the innovative solutions seemed to come more from small or internal groups rather than the big teams.  Which only reinforces my overall concern with the industry as a whole.  I wonder if it’s easier for small teams to adapt to advice of folks like Michael Allen (no more boring elearning), Julie Dirksen (Design for How People Learn) and Will Thalheimer than it is for big teams, who not only have to change processes but also educate their customers.

This is an unscientific sample; I did a quick tour of the displays, but couldn’t see all as there were some that were just too crowded.  I also looked at them relatively briefly and didn’t make comprehensive notes, so this is just a read of my state of mind as I finished.  It doesn’t ameliorate the overall concern, but it does provide some hope that things are changing in small pockets.

Yes, you do have to change

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Of late, I’ve seen a disturbing trend.  Not only are the purveyors of existing solutions preaching caution and steadiness, but it even seems like some of the  ‘names’ of the field are talking in ways that make it easy to think that the industry is largely doing ok.  And I do  not understand this, because it’s demonstrably wrong.  The elearning industry, and the broader learning industry, is severely underperforming the potential (and I’m being diplomatic).

We  know what leads to effective learning outcomes.  And we’ve known it for decades (just because MOOCs are new doesn’t mean their pedagogies are): clear models, annotated examples, and most importantly deep and meaningful practice focused on significant skill shifts (let alone addressing the emotional side of the equation).  Learners need to perform, repeatedly, with guidance, over more and more complex contexts until they achieve the level of performance they need.  However, that’s no where near what we’re seeing.

What we see are knowledge dump/test tarted up with trivial interactions.  People will pass a test, but they will  not have achieved the ability to affect any meaningful business outcomes.  If it’s knowledge that performers need, create a job aid, not a ‘spray and pray’.  And facilitate people in self-helping.  As things get more complex and moving faster, there’s no way everything  can be kept up with by new course development, even if it were a useful approach, and mostly it’s not.

We’re even  measuring  the wrong things.  Cost per seat hour is secondary (at best).  That’s ‘fine-tuning’, not the core issue.  What’s primary is business impact.  Are you measurably improving key performance indicators as outcomes?

And that’s assuming courses are all the learning unit should be doing, but increasingly we recognize that that’s only a small proportion of what makes important business outcomes, and increasingly we’re recognizing that the role needs to move from instructional designer to performance consultant.  More emphasis can and should be on providing performance resources and facilitating useful interactions rather than creating courses.  Think performance support first, and communities of practice, only resorting to courses as a last result.

Tools that make turning Powerpoint presentations into page-turning content aren’t going to fix this, nor are tools that provide prettified drill-and-kill, nor ones that let you host and track courses.  There are places for those, but they’re not the bulk of the opportunity, and shouldn’t be the dominant solutions we see.  There’s  so much more: deeply engaging scenarios and simulation-driven interactions on the formal side, powerful job aid tools for performance support (particularly mobile), coaching and mentoring as a better solution than courses in many (most) cases, performer-focused portals of tools, underlying powerful content management suites, and rich social environments to support performers making each other smarter and more effective.

I’m not quite sure why the easy tools dominate the expo halls, except perhaps because anyone can build them.  More worrisome is that it can let designers off the hook in terms of thinking deeper.  We need to focus first on rich outcomes, and put the tools secondary.

While the industry congratulates itself on how they make use of the latest technology, the lack of impact is leading a drive to irrelevancy.  Learners tolerate the courses, at best.  Operations groups and others are beginning to focus on the performance solutions available.  Executives are beginning to hear a message that the old approach is a waste of resources.

Hiding your head in the sand isn’t going to cut it. The industry is going to have to change.  And that means you will have to change.  But you’re a professional in learning, right?  So lead the way.  The best way to change is to take that first step.

 

Daniel Coyle #LSCon Keynote Mindmap

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Daniel Coyle gave a wonderfully funny, passionate, and poignant keynote, talking about what leads to top performance. Naturally, I was thrilled to hear him tout the principles that I suggest make games such a powerful learning environment: challenge, tight feedback, and large amounts of engaging practice. With compelling stories to illustrate his points, he balanced humor and emotional impact to sell a powerful plea for better learning.

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Barrier to scale?

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I was part of a meeting about online learning for an institution, and something became clear to me.  We were discussing MOOCs (naturally, isn’t everyone?), and the opportunities for delivering quality learning online.  And that’s where I saw a conflict that suggested a fundamental barrier to scale.

When I think about quality learning, the core of it is, to me, about the learning activity or experience.  And that means meaningful problems with challenge and relevance, more closely resembling those found in the real world than ones typically taught in schools and training.  There’s more.

The xMOOCs that I’ve seen have a good focus on quality assessment aligned to the learning goal, but there’s a caveat. Their learning goals have largely been about cognitive skills, about how to ‘do’. And I’m a big fan of focusing on ‘do’, not know.  But I recognize there’s more, there’s to ‘be’.  That is, even if you have acquired skills in something like AI programming, that doesn’t mean you’re ready to be employed as an AI programmer. There’s much more.  For instance, how to keep yourself up to date, how to work well with others, what are the nature of AI projects, etc.

It also came up that when polled, a learned committee suggested top things to learn were to lead, to work well on a team, communicate, etc.  These are almost never developed by working on abstract problems.  In fact, I’d suggest that the best activities are meaningful, challenging, and collaborative.  The power of social learning, of working together to receive other viewpoints and negotiate a shared understanding, and creating a unique response to the challenge, is arguably the best way to learn.

Consequently, it occurs to me, that you simply cannot make a quality learning experience that can be auto-assessed.  It needs to be rich, and mentored, scaffolded, and evaluated.  Which means that you have real trouble scaling a quality learning experience.  Even with peer assessment, there’s some need for human intervention with every group’s process and product.  Let alone generating the beneficial meta-learning aspects that could come from this.

So, while there are real values to be developed from MOOCs, like developing perhaps some foundation knowledge and skills, ultimately a valuable education will have to incorporate some mechanism to handle meaningful activities to develop the desirable deep understanding.  A tiered model, perhaps?  This is still embryonic, but it seems to me that this is a necessary step on the way to a real education in a domain.

Leadership for Complexity

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The other meme from the retreat event  last weekend was the notion of leadership for complexity.   A few of us decided to workshop a topic around performance, leadership, and technology.   We realized technology was only a means to an end, and the real issue was how to move organizations to optimal performance (e.g. the Coherent Organization).

We talked through how things are moving from complicated to complex (and how important it is to recognize the difference), and that organizations need to receive the wake-up call and start moving forward.   Using the Cynefin model, the value will not come from the simple (which should be automated) nor the complicated (which can be outsourced), but from dealing with the complex (and chaotic).   This won’t come from training and top down management. As I’ve said before, optimal execution will only be the cost of entry, and the differentiator (and hence the value) will be continual evaluation. And that comes from a creative and collaborative workforce.   The issue really is to recognize the need to seize new directions, and then execute the change.

One concern was whether we were talking evolution or revolution.   Rather than taking an either or, I was inclined to think that you needed revolutionary thinking (I like Kathy Sierra’s  take on this), but that you fundamentally can’t revolutionize an organization short of total replacement (“blood on the streets” as one colleague gleefully put it :).   I reckoned a committed change initiative to the place the revolutionary thinking pointed was what was needed.

The issue, then, is the vision and guidance to get there.   What’s needed is leadership that can lead the organization to be able to leverage complexity for success.   This will be about equipping and empowering people to work together on shared goals: sharing, commenting, contributing, collaborating, and more.   It will be inherently experimental in an ongoing way.

What that means practically is an exercise I (and we) are continually working on, but we’ve coalesced on the top-level frameworks to form the basis of tools, and what’s needed are some organizations to co-develop the solutions.   Design-based research] if you will. So who’s up for working on the path to the future?

#itashare

Leaving Trails

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So I was away for the weekend at a retreat with like-minded souls, Up to All of Us, thinking deeply about the issues that concern us. I walked away with some new and renewed friendships, relaxed, and with a few new thoughts. Two memes stuck with me, and the first was “leaving trails”.

For context, the event featured designers – graphic, industrial, visual – but mostly learning designers. In a session on supporting the growth of design awareness, we were being led through an exercise on body-storming (using role plays to work through issues), and one of the elements that surfaced was posting your designs on the walls in places where it’s hard to see others’ work. And I had two reactions to this, the first being that the ability to share work was a culture issue, but the other was a transparency issue.

The point that I brought up was that just seeing the work wasn’t enough, ideally you’d want to understand what was the thinking behind it (not just working out loud, but thinking out loud). That can come from a conversation around the work, but that’s not always possible (particularly if it’s a virtual wall).

And I thought the leader of the exercise, an eloquent and experienced designer, said that you couldn’t really annotate your thoughts about the work. Which I fundamentally disagreed with, but he then went on to talk about showing interim work, specs, etc (and I’m filling in here with some inferences because memory’s not perfect).

What emerged in my thinking was the phrase leaving trails, not just your work, but the trajectories, constraints, and more. As I’ve argued before, I think showing the thinking behind decisions is going to be increasingly important at every level. At workgroup level, individuals will be better able to collaborate if their (prior) work is detailed. Communities of practice similarly need such evidence. Another colleague also presented work on B Corps, benefit corporations, in which businesses will move from shareholder returns to missions, and such transparency will be necessary here as well as for eGovernment. I reckon, what with ClueTrain, any org that isn’t being transparent enough will lose trust.

Of course, the comfort level in sharing gets back to the culture issue: people have to be safe to share their work and give and receive feedback in constructive ways to move forward. Which is really the subject of the next meme.

(NB: one of the principles of the event is Chatham House Rule, which basically says you can’t share personal details without prior approval, and I didn’t ask, so the perpetrators and victims shall remain nameless.)

Games do teach

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I think Ruth Clark’s provides a great service in presenting what the research says on elearning, starting with her highly recommended book  eLearning and the Science of Instruction.  So it’s hard to want to quibble, but she put out what I think is a somewhat irresponsible post on games with the provocative title “Why Games Don’t Teach“.  So it’s only fair that I raise my objections, though the comments do a great job also  of pointing out the problem.

As many have pointed out, the title is needlessly confrontational.  It’s patently obvious games teach, simply by trying a popular game yourself and realizing quickly that there’s no way you’re going to achieve a competitive level of play without substantial practice.  As Raph Koster’s fun and valuable book  A Theory of Fun for Game Design aptly points out, the reason games succeed is that they do require learning.

So the real point Ruth is making is that research doesn’t show the value of games for learning, and that there are no guidelines from research for design.  And yet she continues to be wrong.  As Karl Kapp (author of Gamification)  points out in his thoughtful and comprehensive comment, there are quite a few studies demonstrating this (and further elaborates on a study Ruth cites, countering her point).  As far back as the 80’s, frankly, Lepper and Cordova had a study demonstrating improvement from a game version of a math practice application.  The evidence is there.

What’s more insidious, as Koreen Olbrish points out in her comment, is that the definition of learning is open.  Unfortunately, what Ruth’s talking about seems to be rote memorization, by and large.  And we do know that tarting up drill and kill makes it more palatable (although we need to be quite certain that the information does have to be ‘in the head’ rather than able to be ‘in the world’).  But I maintain that rote fact remembering isn’t what’s going to make an organizational successful, it’s making better decisions, and that’s where games will shine.

Games, properly used, are powerful tools for meaningful practice.  They’re not complete learning experiences, but next to mentored live practice, they’re the best bet going.  And principles for design?   Going further,  I believe that there are sound principles for design (heck, I wrote a book about it). It starts with a laser focus on the objectives, and the important ways people go wrong, and then creating environments where exercising those skills, making just those decisions that learners need to be able to make, are made in a meaningful context.

Yes, it requires good design. And, essentially the same basics of good learning design as anywhere else, and  more, not other.  The problem with research, and I welcome more and a taxonomy, is that research tries to whittle things down into minute elements, and games are inherently complex, as are the decisions they’re training.  There are long-term projects to design environments and conduct the small elements of research, but we’ve good principles now, and can and should use a design-based research approach.

Overall, I think that it’s safe to say that:

  • games can and do teach
  • we have good principles on how to design them
  • and that more research wouldn’t be bad

However, I think the article really only makes the latter point, and I think that’s a disservice.  Your mileage may vary.