Dave’s Whiteboard

This post is my contribution to the October edition of the Working / Learning blog carnival, hosted at the Xyleme Learning Blog.
(What’s a blog carnival? Details here. If you blog about learning in a work setting, or about working deliberately at learning, you should take part.  Don’t be shy.)

In a recent post, Beyond Training, Harold Jarche (in one of his comments) gives his rule of thumb: “Training is the last resort, when all other performance improvement alternatives (which are usually cheaper) have been discounted.”

Instead of “discounted,” I might have said “examined.”  Otherwise, Harold’s highlighting a dilemma that corporate and organizational training departments (by whatever name) have been struggling with decades.

Here’s the deal: there are all kinds of ways to instruct efficiently and effectively.  You can design (as Bob Mager and Peter Pipe said more than 30 years ago) criterion-referenced instruction so you don’t waste people’s time “teaching” them what they already know.  You can sequence, you can use increasing approximations of the real-life job, you can avoid war stories and nice-to-know.  You can avoid spoon-feeding.  You can emphasized hands-on, problem-based exercises.

But… a lot of the time you don’t have to do those things.  How much of “training” is a kind of corporate Clearasil applied to the zits of a counterproductive computer system or an alleged process that’s really the business equivalent of the cowpath that became a paved street?

How much of what some subject-matter expert or department head thinks people really oughta know (or, worse, really oughta wanna know) actually matters?

It may be that people don’t know this stuff (whatever “this stuff” is).  It’s less clear that traditional training is the way to change the outcomes.

For many people, the father of “performance improvement” was Tom Gilbert; I had the chance to meet him several times, and his thinking has permanently influenced my own.  Some time back I quoted his model for creating incompetence.  Consultants Joseph and Jimmie Boyett published a crisp article (PDF) explaining why the performance-improvement model makes sense.

It’s worth a look; it tracks with Harold’s point about training as a last resort.  In essence, Gilbert would approach a performance problem (a gap between the results you want and the ones you have) like this:

• Do people have the information they need?
  (Notice, that’s not “do they know?”  Gilbert is talking about information about how to perform and about how well you’re doing.)
• Do they have the instruments they need — tools, methods, technology, whatever?  You can train pharmaceutical workers in all kinds of good manufacturing practice, but if (as at one location I worked in) people have to walk from packaging line A to line B because line A doesn’t have the right kind of scale — and you’re measuring residue in fractions of a gram — you risk not getting the accuracy you claim you need.
• Do you have incentive systems to support the performance you need?  If the customer comes first, do you punish people for not completing their end-of-the-day paperwork by a set time?  If your speeches are about relationship selling, are the annual award winners the salespeople who pushed product?
• Only after examining these other influences on performance would Gilbert ask whether people have the skills and knowledge to perform.  As the Boyetts say,

By correcting deficiencies in information, instruments, and incentives first, you make sure you don’t end up training people to use tools that could be redesigned, or to memorize data they don’t need to remember, or to perform to standards they are already capable of meeting and would meet if they knew what these standards were.

I love working in this field; I get excited when people in client organizations produce better results on the job.  What has mystified me since I read Mager in grad school and Gilbert’s Human Competence in the late 1970s is why otherwise sensible organizations waste millions of dollars (and millions of worker hours) trying to talk or PowerPoint or click-enter or multiple-choice people into worthwile results.

Photo of criterion-based traffic test by Birger Hoppe.

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This post is part of September’s edition of the Working / Learning blog carnival.  This month’s host is Michele Martin of The Bamboo Project blog.  (And here’s info about the carnival in general.)

Cammy Bean is “auditing the auditor’s version” of a course on connectivism.  She referred to a post by Christy Tucker, “Does learning grow or is it built?”  The question’s based in part on Stephen Downes’s contention that understanding is “the process of making connections,” and that the “connectionist networks” are not built (like a model) but grown (like a plant).

Christy’s post, and the many comments, got me thinking about this build/grow concept.  It’s certainly true that whatever learning is, it happens in the brain — electrochemical processes leading to new brain cells, stronger connections, increased pathways — as in the old notion “the neurons that fire together, wire together.”

The drawback, from a learning-at-work standpoint, is that we don’t know and can’t do much at the level of the individual neuron, or even the level of a whole bunch of them.  I’m not saying Stephen’s wrong, but I’m thinking build-versus-grow is a bit of a distraction.

Especially since, as with most Metaphor Parties, we all bring our own recipes.

I make an analogy with the musculoskeletal system (though to look at me, you’d conclude that must be pure theory on my part). Here’s what I mean:

You can just go about your ordinary activities, and even without strenuous work or deliberate exercise, way down there at the cellular level, you’re going to get new muscle cells and you’re going to strengthen existing ones. Eventually that has an effect on the larger, organized systems we call muscles.

In infancy and childhood, we’re not doing much directing of that process; we’re not activity choosing which set of muscles to work on.  Yet in a fashion that parallels things like acquiring language, we gain in our musculoskeletal ability.

We know that we can, if not build, at least focus and concentrate our efforts.  We can set out to increase out physical ability — and it turns out that working enough with muscles has an effect on bone, too: strength training (working with weights) not only increases the capability of muscles (nice way to avoid “grows” or “builds,” huh?), it can increase the capability of related bones.

That’s why strength training is beneficial for elderly people: their bones get stronger — more so than if they continued only with everyday activity.

It’s just an analogy; the brain is far more complex.  I just see these potential parallels in the musculoskeletal system:

• Whether you just happen to do a lot of physical labor, or you work out, in certain circumstances you increase both cardiovascular capacity and  strength.
• Increased cardio and strength, in various combinations, lead to overall fitness and increased health (decreased anxiety, increased endorphines, lowered stress, etc., etc.).

The connection?  Learning may grow in a way we can’t do much about at the cellular level.  But, particularly in the world of work, it’s obvious that we can find ways to make concepts clearer, to organize information, to create sequencing or scaffolding that can help an individual learn better.

Can you learn French by being dropped in the middle of Aix-en-Provence with 5,000 euros and a suitcase?  Sure.  But you might learn faster by having someone who can model and demo (as Downes says).  You might also benefit from knowing that nearly all French nouns ending in <i>-tion</i> are feminine — something I only found out this year, despite years spent trying to improve my French.

I don’t mean for a moment that corporate training departments or learning organizations have the answer.  For one thing, there isn’t the answer.  For another, inertia is one of the strongest forces in the universe — and not just for the training/learning professionals.  How many managers and how many workers still see live classroom delivery as the preferred way to learn?  How many busy people resist formats that seem too open-ended because they’re unclear about the process or the outcome?

No answers from me here.  I’m glad to have even a small part in this wide discussion.

Both photos by tyfn.

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I once heard DNA co-discoverer James Watson speaking at a lecture. Referring to some research, he said, “We thought we were being stochastic, but we were just guessing.”

I’d like to think that I’m integrative, but mostly I just happen across unassociated things. Like, for instance:

Michael Feldstein at e-Literate has a guest post by Jutta Treviranus. You Say Tomato… looks at designing the user-experience interface for distributed learning. Treviranus notes that UI designed is often left to programmers and often happens at the end of the development process.

As part of her work with the Fluid project, Trivarnus and her colleagues “have found ourselves at odds with common or traditional notions integral to pedagogy, software design, user interaction design, usability, and accessibility.”

The Fluid approach to user experience design and usability testing is also at odds with standard or commercial UI design methods. These methods assume that the user really doesn’t know what is best or what they want. Users are not self-aware, what they report doing is not actually what they do and asking users what they might want does not lead to innovation because they extrapolate from what they know and are most likely to ask for a faster horse carriage than a car. Consequently the assumption is that any proposed design requires extensive user testing with objective observation and data gathering from a large number of representative users.

(I’ve always felt a bit sheepish about tinkering with my off-the-shelf software — I have created buttons In Word to prevent tables from breaking within rows, to insert section breaks, and to print just the current page. That’s pretty low-level customization, but a lot more than the average person tends to do.)

The apparently unrelated item that came to mind as I read this was John Tierney’s article in Monday’s New York Times blog, A New Frontier for Title IX: Science. (Title IX is the U.S. law barring sexual discrimination in education, and till now has applied mainly to sports. The article deals with the question of similar discrimination in science.)

Lots of things I didn’t know (it’s an ever-growing list):

• In the U.S., 50% of med students, 60% of biology majors, and 70% of psychology PhDs are women.
• Less than 20% of physics PhDs are women.

Tierney cites research by David Lubinski and Camilla Persson Benbow suggesting that the differences in choice of field may have more to do with an individual’s preferences than overt discrimination. Similar research by Joshua Rosenbloom and Ronald Ash made this less-than-astonishing conclusion:

…Information technology workers especially enjoyed manipulating objects and machines, whereas workers in other occupations preferred dealing with people.

Once the researchers controlled for that personality variable, the gender gap shrank to statistical insignificance: women who preferred tinkering with inanimate objects were about as likely to go into computer careers as were men with similar personalities. There just happened to be fewer women than men with those preferences.

What struck me (for this post of my own) was not the gender gap per se, but the connection between the object-manipulators in IT, and the end-users of software that Treviranus discussed in her user-interface post.

And I figured a post combining user interface, open source, and potential on-the-job discrimation might stir up a thing or two.

Photo of Rosalind Franklin (whose X-ray images helped lead Watson and Crick to their model for the structure of DNA)
from the National Library of Medicine.

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This month’s Working/Learning blog carnival is hosted by Tony Karrer at WorkLiteracy. The questions he poses:

• Does a knowledge-work skills gap exist?
• If so, what are examples of where to help knowledge workers?
• Is this receiving appropriate attention?

In talking about a framework, Tony has an initial list of possible task categories:

• Scan: stay up to speed on a topic
• Find: this includes evaluate, narrow, adjust
• Keep / Organize / Refind: I like the word “retrieve” as a shortcut
• Leverage / Present
• Network
• Collaborate
• Learn
• Improve (evaluate and build your work and learning skills)

That framework post has an overwhelming amount of other looks at the topic (as well as topics living on the same block).

One difficulty I’ve been having with the label “work literacy” is the implication that everybody knows what the “common knowledge work tasks” are, and that these tasks manifest themselves in the same way regardless of setting.  (I’m fully aware that Tony, Michele, and others aren’t implying this, but the inference seems there for the making.)

Another problem is one that Richard Hoeg raises in a comment:

The BIG “learning� I’ve taken away from my failures, is that any initiative I lead I must always first analyze the present work flows of my company’s employees. Any tool which does not easily integrate into one’s normal daily work will never be adopted. My employees have no desire for new tools, but they do want to have their tool set be more effective.

“My employees have no desire for new tools” may be a little hyperbolic, but not much. I have a hunch (a bias?) that many people who are highly networked, highly connected, highly 2.0 just plain like tools. Especially new ones.

But not everybody does. The average person, by definition, isn’t an early adopter — he’s average. Even the average knowledge worker is average. His job is “knowledge work” mostly because he’s not waiting tables and not loading cowl sides into boxcars: “knowledge work” is a category. I think the worker himself sees his job as its main outcome-producing processes. In other words:

“I manage my food-company inventory for our grocery-chain client.”
“I resolve supply problems for the retailers who sell our printers and copiers.”
“I review health claims for former atomic-weapons workers or their survivors.”
“I train our sales force in features, benefits, and competitive positioning for our EDI software.”

So what?

So, I don’t think I’ll get far starting a conversation that implies folks are not literate. I know that’s not what’s intended, but I see it as a potential barrier.

The conversation can’t be about “literacy” — unless you’re talking to the CEO, who of course will figure you mean other people.

If you’re talking to the workers themselves, the conversation might start with information. Ignoring (or at least not focusing on) content details (what IBM used to call speeds and feeds), what information do you need to get to do your job? What information do you need to have? What information do you need to share? (And when, with whom, et cetera…)

Stealing freely from Tony’s grid, but sliding things around a bit, the conversation deals with questions like:

• What do you need (to know, to get, to do…)?
  • This isn’t “what’s missing?” This is, “what do you need to get your job done?”
  • It’s also not about physical objects, though they’ll come into the conversation.  The key is the knowledge/informational aspects of the physical objects.
    
• How do you do that now?
• What works well? What doesn’t?
• Could you / would you like to do the “well” better?
• Would you like to do the “doesn’t” better?

I’m rummaging around for a term. It’s something similar to metacognition, but that has a lot of polysyllabic baggage, and people outside of the training/learning profession don’t light up with joy when you start talking about “learning how to learn.” I haven’t found that term yet, but it connects to this useful debate on ways to help people who want help to find, retain, apply, share, and strengthen their knowledge-work skills

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Tony Karrer is hosting the June 2008 edition of the Working/Learning Blog Carnival (about the carnival) at WorkLiteracy.  (WorkLiteracy is “a network of individuals, companies, and organizations” looking to address “a growing gap between the work practices and skills that most knowledge workers possess and the resources available to them.”)

You’re invited to share your opinions:

• Is there a gap between how knowledge workers to their work, and how they could if they harnessed different methods, tools, resources?
• If your answer’s yes, where do you see the opportunities?
• Is the issue of work literacy receiving enough attention?

In a departure from the usual blog carnival format, you can participate by posting on your own blog and sending Tony a link, or by sharing your thoughts as comments to the “host post” (where you can see more of the thinking behind this issue.

The invitation’s open through the end of June.

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