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The ITA Jay Cross Memorial Award for 2018: Mark Britz

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In honor of the colleague, mentor, and friend that brought us together, every year the Internet Time Alliance presents the Jay Cross Memorial Award. The award is for an individual who represents the spirit of continuing informal learning for the workplace. This year, Mark Britz is the deserving recipient.

Jay was a fierce champion of social and informal learning. He saw that most of how we learn to do what we do comes from interacting with others.  As a response to his untimely passing, the remaining members of the ITA decided to honor his memory with an award.  Jane Hart, Harold Jarche, Charles Jennings, & myself each year collectively decide an individual who we think best reflects Jay’s vision. And we announce the recipient on the 5th of July, Jay’s birthday.

Mark has resonated and amplified the message of ongoing learning since we first crossed paths. He has interacted with the ITA members regularly via tweets, blogs, and in person when possible.  And we’ve appreciated his engagement with the ideas and his contributions to our thinking.

I got to know Mark’s thinking a bit better when he wrote a case study based upon his work at Systems Made Simple for the Revolution book (Jay wrote the foreword).  And he’s continued to blog about workplace learning at The Simple Shift with short but insightful posts. Currently part of the team running events for the eLearning Guild, Mark manages to consistently touts views that illuminate thinking about the new workplace.

The situation he cites in that case study is exemplary of this type of thinking. Charged with starting a corporate ‘university’ in an organization that was composed of many experts, he knew that ‘courses’ weren’t going to be a viable approach. Instead, he championed and built a social network that pulled these experts together to share voices. The core L&D role was one of facilitating communication and collaboration, rather than presenting information.

For his continuing work promoting communication, collaboration, and continual learning, we recognize Mark’s efforts with the 2018 Internet Time Alliance Jay Cross Memorial Award.

 

 

Microlearning Malarkey

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Someone pointed me to a microlearning post, wondering if I agreed with their somewhat skeptical take on the article. And I did agree with the skepticism.  Further, it referenced another site with worse implications. And I think it’s instructive to take these apart.  They are emblematic of the type of thing we see too often, and it’s worth digging in. We need to stop this sort of malarkey. (And I don’t mean microlearning as a whole, that’s another issue; it’s articles like this one that I’m complaining about.)

The article starts out defining microlearning as small bite-sized chunks. Specifically: “learning that has been designed from the bottom up to be consumed in shorter modules.” Well, yes, that’s one of the definitions.  To be clear, that’s the ‘spaced learning’ definition of microlearning. Why not just call it ‘spaced learning’?  

It goes on to say “each chunk lasts no more than five-then minutes.” (I think they mean 10). Why? Because attention. Um, er, no.  I like JD Dillon‘s explanation:  it needs to be as long as it needs to be, and no longer.

That attention explanation?  It went right to the ‘span of a goldfish’. Sorry, that’s debunked (for instance, here ;).  That data wasn’t from Microsoft, it came from a secondary service who got it from a study on web pages. Which could be due to faster pages, greater experience, other explanations. But not a change in our attention (evolution doesn’t happen that fast and attention is too complex for such a simple assessment).  In short, the original study has been misinterpreted. So, no, this isn’t a good basis for anything having to do with learning. (And I challenge you to find a study determining the actual attention span of a goldfish.)

But wait, there’s more!  There’s an example using the ‘youtube’ explanation of microlearning. OK, but that’s the ‘performance support’ definition of microlearning, not the ‘spaced learning’ one. They’re two different things!  Again, we should be clear about which one we’re talking about, and then be clear about the constraints that make it valid. Here? Not happening.  

The article goes on to cite a bunch of facts from the Journal of Applied Psychology. That’s a legitimate source. But they’re not pulling all the stats from that, they’re citing a secondary site (see above) and it’s full of, er, malarkey.  Let’s see…

That secondary site is pulling together statistics in ways that are  thoroughly dubious. It starts citing the journal for one piece of data, that’s a reasonable effect (17% improvement for chunking). But then it goes awry.  For one, it claims playing to learner preferences is a good idea, but the evidence is that learners don’t have good insight into their own learning. There’s a claim of 50% engagement improvement, but that’s a mismanipulation of the data where 50% of people would like smaller courses. That doesn’t mean you’ll get 50% improvement. They also make a different claim about appropriate length than the one above – 3-7 minutes – but their argument is unsound too. It sounds quantitative, but it’s misleading. They throw in the millennial myth, too, just for good measure.

Back to the original article, it cites a figure not on the secondary site, but listed in the same bullet list: “One minute of video content was found to be equal to about 1.8 million written words”.  WHAT?  That’s just ridiculous.  1.8 MILLION?!?!?  Found by who?  Of course, there’s no reference. And the mistakes go on. The other two bullet points aren’t from that secondary site either, and also don’t have cites.  The reference, however could mislead you to believe that the rest of the statistics were also from the journal!

Overall, I’m grateful to the correspondent who pointed me to the article. It’s hype like both of these that mislead our field, undermine our credibility, and waste our resources. And it makes it hard for those trying to sell legitimate services within the boundaries of science.  It’s important to call this sort of manipulation out.  Let’s stop the malarkey, and get smart about what we’re doing and why.  

A solid education platform

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In the past couple of days, I’ve come across two different initiatives to improve education. And certainly our education system can stand improvement. However, each one had the same major flaw, and leaves open an opportunity for improvement not to occur. Over a number of engagements I’ve developed the basis of what I think is a necessary foundation for a viable education platform. It’s time to toss it out and see what you all think.

So, one initiative had a proposal of 10 different areas they wanted people to contribute in. This included AI, and personalization, and ‘out of class’ credit, and more. Which is all good, make no mistake! However, nowhere was there the option of ‘a deeper pedagogy’. And that’s a problem. It’s all too easy to chase after the latest shiny object. It makes us feel like we’re both doing something constructive and keeping up with developments. (Not to mention how much fun it is to play with the latest things.) However, gilding bad design is still bad design! We need to make sure the foundation is strong before we go further.

The other initiative has three ways to contribute: lifelong learning, a marketplace, and emerging technology. And, again, the big gap is talking about the pedagogy to begin with.  With a marketplace, you might get some Darwinian selection process, but why not put it out there from the get-go? Otherwise, it’s just cool tinkering around a broken core.

Three partsSo here’s where I pitch my 3 part story. Note that curriculum is broken too (I’m channeling Roger Schank: ‘Only two things wrong with education, what we teach and how we teach it’), and yet I’m not addressing that. Well, only a second layer of curriculum (see below ;). I think the choice of the first level curriculum is a big issue, but that changes depending on level, goals, etc. Here I’m talking about a platform for delivering the necessary elements of a supportable approach:

  1. The first element is a killer learning experience. What do I mean here? I mean an application-based learning approach. Even for so-called theory classes (e.g. typical higher ed), you  do something with this. And the experience is based upon minimal content, appropriate challenge, intrinsic motivation, and more. My claim: this is doable, even when you want to auto-mark as much as possible. Of course, there are still people in the loop.
  2. Which leads to the second element, we as the provider are a partner in your success. It’s not ‘sink or swim’, but instead we’re tracking your progress, intervening when it looks like you’re struggling, and accessible at your time and place. We’re also providing the necessary resources to succeed. And we’re not interested in a curve, we’re competency-based and want everyone to get where they can be.  We’re also making sure you’re getting what you need.
  3. And that’s the third element, we  develop you. That is, we’re not just developing your knowledge of the field, we’re also developing key success skills. That means we’re giving you chances to practice those skills as well,  and tracking them and developing them as well. This includes things like communication, collaboration, design research, and more. So-called 21C skills.

I suggest that with such an approach, and the right curriculum, you’re providing a full suite of what education  should  be about. And, I suggest, we can do this now, affordably. Technology is part of the picture, learning science is part of the picture, and the commitment to do the right thing is part of the picture. Also, I think this is viable at all levels. K12, higher ed, and workplace.

And, I’ll suggest, anything less really isn’t defensible. We have the know-how, we have the tools, all we need is the will. Yet, despite some notable steps in the right direction, we’re really not there. It’s time to put a stake in the ground. Who’s up for it?

Hard Fun Projects

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As a basic premise of my book on designing engaging learning, I maintain that learning can, and  should, be ‘hard fun’. When you look at learning and engagement, you find this perfect alignment of elements. And, it occurred to me, that’s also true for good project work.  And here I don’t just mean coursework assignments (though that too fits), but organizational innovation should also be hard fun!

As I’ve stated before in various places, when you’re designing new solutions, problem-solving, trouble-shooting, doing research, etc, you don’t know the answer when you begin.  Therefore you’re learning when you do so!  It’s not formal learning, it’s informal, but it’s still learning.  So what works in learning should make sense for innovation too.

And in learning, the alignment I found between elements of effective education and engaging learning make sense.  Both require (amongst others):

  • clear goals
  • appropriate challenge
  • meaningfulness of the problem to the context
  • meaningfulness to the learners
  • experimentation
  • feedback

And those also define a meaningful project for solving in the workplace.

That is, first  you need to have a clear goal. The size and scope of the task should be within the reach, but not the grasp, of the team. The project has to have a clear benefit to the organization.  And the team should be appropriately constituted with skills and committed to the project. The methods required for the innovation will be experimentation and feedback.  Of course, you also need diversity on the team, safety to experiment, accountability for the results.  (Which is helpful for formal learning too!)

We can, and should, be setting up our projects to meet these criteria. We get better outcomes, research tells us. That not only includes the product of the work, but team engagement as well. This is also a possible start to creating a culture of experimentation and continual learning. Which also has long-term upsides.

This came to me because I was asked in an interview what were the most fun projects I’d done. I realized that working with folks together to address problems, like when I led a team to develop an adaptive learning system, fit the bill.  And that’s work I love, whether having a group together to collectively work out better design processes or performance and development strategy.  Folks who’ve worked with me similarly have found it valuable. So who’s up for some ‘hard fun’?

Possible versus practical

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Last week, I gave a presentation to the local chapter of ATD. And I was surprised that their request was for mobile learning. Now that  is something I can speak to, but given that my book on the topic came out seven years ago now, it seemed like a dated topic. And I was wrong.  And the difference is between what’s possible and what’s practical.

Ok, so I am somewhat out ahead of the curve.  My games book came out in 2005, but the market wasn’t quite ready.  I similarly think my L&D revolution book, in 2014, was ahead of the market (the topic is finally getting more traction, close to four years later), though closer. But I thought the mlearning book was timely (not least because my publisher asked for it more than it was my initiative ;).

However, the audience was eager.  And it was relatively large for the group.  And it took a comment from the organizer to raise my awareness.  He said (and I paraphrase): “you think that it’s old, but it’s not old for everyone”. And that was indeed a wakeup call.  Because while mobile to me is very practical, for many it’s still possible.

I  do tend to move on once I reckon I’ve figured something out. I’m interested when it’s still something to be understood or solved. Once I have my mind around it, my restless brain is on to something new.  That’s why I have this blog, for instance, to wrestle with new thoughts. If they get organized enough, it becomes a presentation or even a book.  (Though sometimes I do ones that are requested, e.g. my forthcoming one on myths, and I’m supposed to be reviewing the second round of proofs!)

But the interesting thing to me is to look beyond my own bubble (and what my colleagues are talking about).  We’re looking at what’s possible but not yet done, or what’s on the horizon. Yet I need to remember to continue to tout what’s now on the menu, and recognize not everyone’s yet started moving.  The things that I think are already practical to implement are still on the ‘possible’ list for others.

If you’re reading this blog, you’re probably with me, but feel free to let others know that the things in my past I’m still happy to help with!  In any way: consulting or workshops or even speaking.  For instance, I’ll be talking engagement for the Guild at Learning Solutions, and in a webinar for AECT’s Learner Engagement group.  Just as I talk new things, like myths.  What goes around comes around, I guess, and what’s been possible is now practical.  Ask me how!

 

The Dearth of Science in Learning Technology

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Over the years, I’ve looked at a lot of learning technology.  And I see a dispiriting trend. There seems to be little learning science of late.  What I see are marketing driven decisions, even when there are claims to science!  And I think this is a problem.

First, I generally resist the ‘let me show you our product and give us your opinion’. That’s free consulting, and a very rude ask!  (Though I’m contemplating it but all they’ll get for free is the number of comments in each category I’ve noted. ;)  Still  I  will investigate things of my volition at times.  I end up seeing a lot of technology by checking it out when someone talks about it, or wandering expo halls.  And what I see concerns me.

For one, there are too many tools that have suites of features that are oriented towards ‘information dump and knowledge test’.  Which we know isn’t going to lead to meaningful learning.  Yet when I try to push them to the next level of engagement (cognitive and emotional), they’re uninterested.  The response: “this is what our customers say they want”.  Which, of course, isn’t what they need.

It gets worse when supposedly more advanced tools are proselytized. I recently sampled one system promoting their advanced memory model.  And the free-to-air course  on learning science was broken!  It failed on a couple of dimensions beyond drilling rote memory about one thing. That’s not a good example to be showing.  Yet people who don’t know better might be enthused.

For a quick test, check to see if there’s anyone who understands learning on the executive team of a vendor. You’ll see all the business roles filled.  Some might have advisory boards composed of learning folks, but it’s not clear what role they play.

And I get it.  Unfortunately, as an industry, we’re not informed consumers. I see continual conceptually fuzzy promotion of ideas, and even societies offering white papers on the latest buzzwords.  It’s business, and with business folks in charge (and shareholders to assuage), they’ll do what people want.  Yet this isn’t the professionalism we need.

Ok, so this rant doesn’t taint all companies, but it’s too true for many or most. It’s all too easy to look at the typical offerings and point out the fundamental flaws in what they’re doing, if you know how we learn. And you should.

So, I’ll continue on my crusade for us as an industry to lift our game. I hereby offer to assist any learning technology that wants to put it’s money where it’s mouth is to help them understand learning science, build it into their products, and help them promote the benefits. And I likewise offer any organization  using learning technology to help them lift their game and be better consumers.  I’ve done both before, and am ready to assist others. Because our learners need us to represent their true interests.

 

Listening

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Listening, as I mentioned, in this case to  Guy Wallace.  As one of the premier promoters of evidence-based design, he responded to my question  about what to post on with:

Any “How Tos” using methods, tools and techniques that you‘ve found to work in L&D and Performance Improvement.

Since I am a fan of Guy’s work, I thought I should answer!  Now, obviously I don’t work in a typical L&D environment, so this list is somewhat biased. So I mentally ran through memorable projects from the past and looked for the success factors. Besides the best principles I usually advocate, here are a few tips and tricks that I’ve used over the years:

  • Engage.  Obviously, I wrote a book about this, but some of the quick things I do include:
    • embed the decisions they should be making in contexts where they make sense
    • as Henry Jenkins put it: “put the player in a role they  want to be in”
    • exaggerate the context
    • minimize the distractions
    • hook the learners in emotionally from the start
  • Decisions. I find that working with the objectives for learning projects, it’s critical to focus on the decisions that learners will ultimately be making.  I argue that what will make the difference for organizations, going forward, will be better decisions. And it keeps the discussion from focusing on knowledge. Knowledge is needed, but it’s not central.
  • Brainstorming. When working a strategy session with clients, I seed the discussion before hand with the challenges and background material, and ask that everyone think on their own before we begin collaboration.
  • Better ‘Pair and Share’.  If, in brainstorming, you should think individually before collectively, so should you do so in all forms. So I trialed a ‘pair and share’ where I asked everyone to:
    • think on the questions (asking for 2 things) first,
    • then share with another,
    • and try to reach agreement
    • (I polled the first audience I trialed it on, and they said that the discussion was better, FWIW).
  • Shared language. I have found it valuable, when starting a new project, to run a little ‘presentation’ where I present some of the models that I’m bringing to the table (that’s why I‘m there ;), so we’re starting from a shared understanding. And of course I’ve reviewed materials of theirs beforehand so I can use their terminology.  Educating clients is part of a Quinnovation engagement!
  • Test.  In making the Workplace of the Future project with Learnnovators,  we were barreling along full tilt, working on the second module, and I was getting increasingly worried about the fact that we hadn’t tested the first.  We finally did, relatively informally, but still got valuable feedback that changed our design somewhat. Similarly on other projects, get feedback early and often.
  • Visualize. My diagramming bent had me map out the workflow of a client’s production process, to identify opportunities to tweak the process to bring in better learning science with minimal interruption.  In general, I will often jump up to the whiteboard and try to represent what I’m hearing to see if it’s shared.
  • Prototype.  Similar to the above, I will often mock up what I’m thinking about (in sort of a ‘ape with a crayon’ level of fidelity), to help communicate the idea; e.g. some sort of walkthrough.  I find that only a percentage of the audience can imagine what the experience will be without getting somewhat concrete. (And, yes, they do then complain about the production values, despite the tradeoff of cost versus value.  Sigh.)
  • Get the context.  I generally try to understand the whole ecosystem (ala ‘the revolution‘) before I engage in specifics.  What are the goals, stakeholders, what’s already being done and by whom, etc. It’s important to re-contextualize ‘best principles’, and that requires  knowing the context.
  • Architecture. Thinking through things using a design thinking approach and a systems-thinking perspective, I’ve tried to think of platforms, not just solutions. It might be content architectures, ecosystem elements, but it’s thinking in terms of systems, not just tactics.
  • Pragmatism. One final approach that has been beneficial is thinking about how to approximate the best with a budget.  I used to talk about ‘what would you do if you had magic’, and then see how close you can get with the resources to hand. It’s a heuristic that often has led to an innovative yet viable solution.

Looking at them, I see that they generally reflect my overall focus on aligning what we do with how we think, work, and learn. Your thoughts?

Reflections on 2017

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The end of the calendar year, although arbitrary, becomes a time for reflection.  I looked back at my calendar to see what I’d done this past year, and it was an interesting review.  Places I’ve been and things I’ve done point to some common themes.  Such are the  nature of reflections.

One of the things I did was speak at a number of events. My messages have been pretty consistent along two core themes: doing learning better, and going beyond the course.  These were both presented at TK17 that started the year, and were reiterated, one or the other, through other ATD and Guild events.

With one exception. For my final ATD event of the year, I spoke on Artificial Intelligence (AI). It was in China, and they’re going big into AI. It’s been a recurrent interest of mine since I was an undergraduate. I’ve been fortunate to experience some seminal moments in the field, and even dabble.  The interest in AI does not seem to be abating.

Another persistent area of interest has been Augmented Reality (AR) and Virtual Reality (VR). I attended an event focused on Realities, and I continue to believe in the learning potential of these approaches. Contextual learning, whether building fake or leveraging real, is a necessary adjunct to our learning.  One AR post of mine even won an award!

My work continues to be both organizational learning, but also higher education. Interestingly, I spoke to an academic audience about the realities of workplace learning!  I also had a strategic engagement with a higher education institution on improving elearning.

I also worked on a couple of projects. One I mentioned last week, a course on better ID.  I’m still proud of the eLearning Manifesto (as you can see in the sidebar ;).  And I continue to want to help people do better using technology to facilitate learning.  I think the Quinnov 8 are a  good way.

All in all, I still believe that pursuing better and broader learning and performance is a worthwhile endeavor. Technology is a lovely complement to our thinking, but we have to do it with an understanding of how our brains work.  My last project from the year is along these lines, but it’s not yet ready to be announced. Stay tuned!

The Quinnov 8: An online course

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Ok, so I told you the story of the video course I was creating on what I call the Quinnov 8, and now I’ll point to it.  It’s available through Udemy, and I’ve tried to keep the price low.  With their usual discounts, it should be darn near free ;).  Certainly no more than a few cups of coffee.

It’s about an hour of video of me talking, with a  few diagrams and text placeholders.  I’ve included quizzes for each of the content sections. Also, I have assignments to go away and apply the principles to your own work.  Finally, I created a page or several for each section showing some ideas, models, and more.

I do  not recommend going through it in one run. I can’t control it, but as I mention in the course, you want to space it out. We know that that leads to better outcomes. Instead, I recommend spacing it out a section a week or so perhaps, and doing the work and coming back to reactivate before moving on.

The content is organized around what I’m terming the Quinnov 8, the eight elements I think are core to making the step to better elearning design.  While the ideal is to push to a robust iterative and prototyping model, I’m focusing mostly on the small steps that will give you the greatest leverage. The elements are:

  1. Performance consulting: what to do  before you decide to course
  2. Objectives: making the  right decisions about what to focus on
  3. SMEs: working with them for objectives and more
  4. Practice: making practice meaningful
  5. Models: the conceptual frameworks that guide performance
  6. Examples: the link between concepts and application.
  7. Engagement: wrapping the front and back to create  experiences
  8. Process: the extra steps to make this work

I’m trying to go  deep, that is to unpack the levels of cognitive depth to explain how the Quinnov 8 elements work.  I’ve identified the challenges I’ve faced, and I may well update it over time, but it’s at a stage I think I can at least give you the chance to explore.  I welcome your feedback, but I reckon this is one way you can further your understanding on a significant budget.

Transparency

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I believe that transparency is a good thing. It builds trust, as it makes it hard to hide things.  And trust is important. So, in the spirit of transparency, it occurred to me to share a little bit about me and this blog. Here I lay out who I am, why I write it, and what I write about.

You can find out more via the ‘about Clark Quinn’ link in the right column, but in brief, I saw the connection between computing and learning as an undergraduate, and it’s been my career ever since. It’s not just my vocation, but it’s my avocation: I  enjoy exploring cognition and technology. And while I’ve done the science and track it, what I revel in (and have demonstrable capability for), is applying cognitive and learning science to create new approaches and fine-tune existing ones.  Learning engineering, if you will.

And, for a variety of reasons, I do this as a consultant. I make my living providing strategic guidance for clients.  I speak at events, and write books, but my main income is from consulting. Which means you  should hire me.  I assist organizations to improve their processes and products, both tactically and strategically. My clients have been happy, and find it’s good value. What you get are unique ideas that are practical and yet effective. Ideas you aren’t likely to have come up with, but are valuable. I really do Quinnovate! Check out the Quinnovation site for more.    Of course, I do have to live in the real world, and so I need to find ways to do this that are mutually beneficial.

Yet generating business isn’t why I write this blog.  I started writing this blog as an experiment and originally tried to write 5 days a week (but was happy if that ended up being 2-3 times a week).  My commitment now is 2 per week (which rarely yields 1 or 3).  And I haven’t monetized it: there’s no advertising, and while I occasionally talk about where I’m speaking or the like, I haven’t used this as a way to sell things. Hopefully that can continue.

So, the reason I write is to think ‘out loud’.  It’s largely for me: it makes me think. I’m just always curious!  I’ve previously recounted the story about how I was on a panel answering questions from the audience, and one of my fellow panelists commented that I had an answer for everything. And the reason is in the ongoing attempt to populate the blog, I’ve looked at lots of things. As my client engagements have been in many different areas, I also have wide-ranging experience to draw upon.  And I just naturally reflect, but getting concrete: diagramming and/or writing, provides additional benefits.

Thus, the process of continually writing (for over 10 years now) means I’m looking at lots of things, reflecting on them, and sharing my thoughts. I also make a point to look at related fields, and look for connections. I also look at what’s happening with technology. In general, I look with a critical eye, as I was trained as a scientist.  I think that’s valuable as well, because there still is a lot of nonsense trotted out, and there’s always some new buzzword that’s being loosely tossed about. Blogging’s given me cause to continue to tune my thinking, and at least some folks have commented that they’ve found it useful.

Mostly I write about things related to technology, learning, and individual and organizational implications. It includes diversions to innovation, design, wisdom, performance support, and the like, because they’ve implications for practice. In many ways I see approaches that aren’t well aligned with how we think, work, and learn, and that strikes me as both a shame, and an opportunity to improve. And that’s what I enjoy, finding ways to improve what we do.

So that’s it: I blog to facilitate my understanding, because cognitive science and technology  is my passion. It isn’t a direct business move.  I do need to make a living, and prefer to do it in the area of my passion, and fortunately have been successful so far.  (Which isn’t to say you shouldn’t find a reason to use me, there are never enough opportunities to assist in improvement, and I’m not a sales person ;).  And yes, this life is a learning experience all in itself!  I hope this is clear, but in the interests of transparency I welcome your inquiries and comments. Stay curious, my friends.