Dave’s Whiteboard

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.

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

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.

Series: The brain rules!

This post is part of the Working/Learning blog carnival for April, 2008, hosted this month by Manish Mohan, who blogs at Life, the Universe, and Everything about eLearning and Content Development. It’s the second run of the carnival; the first was in March 2008.

I’ve been reading John Medina’s Brain Rules. I’m also trying to relate them to learning and to things that affect my work. In other words, using his rules as a framework, what can I do with them?

I’ve decided to start with rule six, “remember to repeat.” Why this one? Because last Wednesday was the 262nd anniversary of the Battle of Culloden.

‘Twas love of our prince drove us on to Drumossie
But in scarcely the time that it takes me to tell
The flower of our country lay scorched by an army
As ruthless and red as the embers of hell…

Although I don’t weep over the defeat of Bonnie Prince Charlie, neither do I let April 16 pass unnoticed. Why is that?

Medina writes about how we move information from short-term to long-term memory. Nothing much new: repetition and restatement. One of the principles that we know (but don’t always capitalize on) is spacing out the input. Or as I like to call it, three times 20 is more than 60.

If you’ve got a a given amount of time to learn something, you’ll almost certainly learned better and more thoroughly by spacing out your exposure. Instead of cramming for two hours, try four sessions of 30 minutes each. As the descendant of Scottish Highlanders, I’ve certainly spaced out my exposure to stories of the Jacobite rebellions and songs about “The ‘45.”

Medina also says that when information is retrieved from long-term memory, it’s not fixed as if it were a book pulled from a library shelf. It’s almost a repetition of the initial learning — the information is once again labile, malleable, something we can re-work.

That means when it’s re-stored, it’s been changed. Not always leading to greater accuracy.

Which brings in my great uncle. Actually, Gillies Mhor MacBain is my great-great-great-great-great-great-grand-uncle, if I can trust a genealogical history called The Mabou Pioneers. Gillies fought for Prince Charlie and died at Culloden.

Google his name, and you’ll find dozens of accounts saying that he was 6 foot 4, that he killed at least 13 redcoats, and that an English officer tried in vain to have Gillies spared because of his bravery.

Who knows what really happened? The story of Gillies MacBain has been told and retold. Details were lost on the battlefield and over the years; without a doubt, new details have been supplied. They’ve altered the cultural memory the way recall and reconsolidation can alter your personal memory.

Over time new information in the brain reshapes what’s already there. We can “remember” things that never happened.

That suggests things we can do, in the world of learning at work, to increase the value of that reworking and reconsolidation. Focus the learning on what’s important to the job, for example. Create support and structures to ease recall and increase accuracy.

Think hard about questions like:

• What’s our rationale for a three day workshop?
  • Does it make sense to firehose information this way?
• If we must have one, how do we design for spaced input?
  • Can we break up topics and interweave them?
• Are we focusing on tasks rather than on content?
  • Even (or especially) for concepts and principles, can we provide opportunities to work with them, apply them in job-relevant contexts?
• How do we design, create, or organize information externally to make it easy to retrieve and apply as needed?

I spent more time than expected thinking through this post as I was writing it. While I don’t see Medina’s brain rules as the fulcrum of all knowledge, I like the idea of trying to apply them to the blog carnival themes of “work at learning; learning at work.” So I think this post will be a first in a series based on Medina’s rules. Feel free to chime in.

Old book photo by alpoma / Alejandro Polanco.
Brain funnel image by Beth Kanter.

I like anthologies. How could I go to the beach without Gardner Dozois? And while I might be financially better off without Green Linnet’s Celtophile series of CDs, my shelves and my heart would be emptier in more ways than one.

Blog carnivals are a kind of anthology-on-the-fly, a collection of posts from several blogs. For each issue of a carnival, participants post on their own blogs, and a host posts links to all the participating posts. Like with Encephalon, the cognitive-science carnival.

I invited a few people to kick off a carnival under this particular tent: “Work at learning; learning at work.” I was thinking that posts and participants would connect in some way to training or learning in the workplace (as opposed to school or higher education). And I encouraged the invitees to suggest another blogger people might not have read.

Herewith, the first Working/Learning Blog Carnival:

• Michele Martin at The Bamboo Project shares strategies for supporting personal learning environments, nicely tying together the “work at learning” (you have to hone your craft) with “learning at work.”
• Cathy Moore at Making Change explains how to fit the entire world into a multiple choice question. How can you require the learner to think more deeply about on-the-job implications of the information at hand?
• Harold Jarche writes at his eponymous blog about learning at work, offering three easy steps to making sense out of the information that floods past you — as he says, moving from “this is an interesting idea” to “this is what I know.”
• Janet Clarey writes on her blog about working at learning. And she does mean working.
• …and my own contribution, SME? Not for Me, in which I ever so gently nudge people who design training, hoping to move them from subject-matter to practice.

Some other folks weren’t able to contribute in time for this first carnival. I think we’ll do it again and help widen the range of thoughts that people share about working and learning.