Collaborative Learning 2013: In Search of Common Ground

In my last post on Collaborative Learning, I pondered synergies among practice areas that had traditionally been hallmarks for how we learn. Public Education quickly came to mind.  So did Higher Learning. But what about the commercial space?  Organizational Development (OD) and Knowledge Management (KM) have staked claims to learning too.  And don’t all entrepreneurs, especially in social change spaces, seek to discover ‘what is possible’?

I’ve been in at least 4 Twitter chats on this topic since that original post in December, and had a highly energized conversation every time. We’ve answered the question at a high-level:  YES, there should be synergies across practices.  The many comments on the previous post supported this, and provided numerous sources and examples from personal experience. Thank you Blake Melnick, Jon Husband, Bas Reus and Kira Campo for those contributions.

There’s something to be said about how we, as learners, can learn differently (and perhaps better) in groups with other people, as opposed to learning alone.  A solo effort might involve a book, a teacher, or a computer screen, but in all cases, the learner is generally on their own to discern the material, with only an instructor and visual content (words, pictures) to guide their learning.

Collaborative learning means learning in groups or teams, deriving deeper insights from discussion, alternative perspectives, and open dialog.

Call it social learning if you like.  That’s an interesting frame all it’s own, with important implications for social media, many of them covered in an excellent book, The New Social Learning by Tony Bingham and Marcia Conner.  In fact, by reading this blog post, you and I are using social media to connect the dots on this thinking, with the potential of further engaging in collaborative research ..

But as you will see in our framework, many more factors will influence our success, extending beyond social technology.  Areas like intention, culture, and our ability to think deeply in a variety of modes come into view.  We’re not just talking left-brain vs. right-brain here (though that enters in .. see Iain McGilchrist on RSA for a fascinating update).  We’re talking about critical thinking, empirical thinking, and design thinking, 21st Century frames from the 3 high-order Learning Dimensions in Bloom/Anderson.

From ECODNA 2009 - a discovery thread (detail)

From ECODNA 2009 – a discovery thread (detail)

In our 2/18 #CDNA chat, the group weighed-in in favor of a “spiral” path, not following rows or columns.  Is this possible?  How would be able to keep our bearings?  We’ll be discussing it at hashtag #CDNA on 2/25 at 8pET.  Watch for the transcript.

To get you thinking, the image at left is an excerpt from ECODNA, a reference framework which evolved via Twitter chat in October 2009, part of the genesis of #ECOSYS.

I hope and believe we can bring new energy on “learning to learn” in every direction possible .. the workplace, the classroom, and our daily lives.  We solve problems every day. That means we tap our ability to summon the right solution, or to call up the right set of factors to determine a new solution.  Are we successful?  Sometimes.  But I contend our ability to make sense of the 21st Century is going to be ever more difficult.  The problems are more complex and intertwined.  We will need both the rigor and depth that comes with “learning to learn” at a new level.

The commercial and education implications are significant.

In 2013 at hashtag #cdna we’re going to fill in the blanks on this framework.  At hashtag #ecosys (explained in the ECOSYS blog) we’re exploring Learning Models.

No high stakes testing or forced curricula in sight, folks.  We’re using collaboration to get to the next level of results.  Would love your thoughts as comments here or online using Twitter.  For a deeper dialog, stop by our new Collaborative Learning community at G+.

Don’t look now.  We’re learning to learn as we speak.

Learning to Learn: Can KM, OD and Education Find Synergies that Change What is Possible?

These days, the ability to achieve deep, meaningful learning seems more and more of a challenge.  Hamstrung as we are by an ever growing mountain of content, dwindling attention spans, fewer available hours of focused energy, and pressure to prove results, it’s a wonder anyone can truly learn anything anymore.

Some say we can’t, and that increasingly .. we aren’t.

Rather than piling more fuel on the pyre of discontent, I’ve begun to focus my energy on new ideas in the learning space.  For most of the last 4 years I have been reading, researching, and discussing the challenges.  Much of that has happened over at the #k12 #ecosys, where deep & insightful discussions continue.

The result?  It certainly remains a work in progress.  But I’ve begun to put increasing stock on how to drive a synthesis across professional practices that claim much of the high ground on what it means to learn:  KM, OD and Education in particular.  Here’s a discussion framework that has emerged out of these conversations.

What do I mean by these?  I’ll offer a working definition of each, in the context of “learning how to learn”:

  • KM – Knowledge management, a business practice from the 90’s that seeks to  define, capture, and reuse knowledge across an organization, helping its members to share and ultimately learn from past achievements
  • OD – Organizational development, a business discipline most commonly in HR (human resources) that seeks to increase the productive capacity of the people and teams within the organizations walls
  • Education – the immensely broad ecosystem of teaching professionals across K12, colleges and universities, deeply immersed in the art and science (mostly science) of helping our young people learn

Challenge me here. Is this a good foundation?

Assuming so, would cross-pollination of experts like this be unthinkable?  It seems daunting on the surface.  Getting experts working together is hard work, as I’ve explored throughout The DNA of Collaboration.  But to me, crossing these boundaries is precisely the challenge.  We must work together to redefine the problems in solvable ways.  It means changing the stakes so that all the generations around us .. Boomers,  X, Y, Z and beyond .. can embrace new ways to learn how to learn.

In the face of increasing pressures for results, seemingly ‘soft’ initiatives like these are often scaled back, reducing our capacity to learn and to innovate at precisely the wrong moment.

What are some of the requirements in gaining cross-disciplinary cooperation and teamwork?

  • Intention and focus – to define what it means to learn deeply, and to establish new benchmarks for what is possible and achievable
  • Cultures that evolve – fostering new levels of trust, risk-taking and collaboration, so they might earn a more venerable status: ‘cultures of learning’
  • Solution language – that help insights and ideas emerge and converge into fundamentally new possibilities
  • Releasing the flow of insight – surrendering structure to more organic and adaptive methods of exchange

Working across professional disciplines exposes visible fault lines.  Many are deeply entrenched in decades of research and practice, convinced that the only path to success is the one they learned in grad school.  For some, their deeply held convictions will need to be left by the door.

In terms of some key ideas, what might we be talking about?  Here’s just a starter list of topics, to spark the synapses ..

  • Social Capital – building skills, networks and resources to help ourselves to help others
  • Evolution of Teacher/Learner – teachers that learn; learners that teach
  • Learning Cultures – how do we foster them?
  • Weaving a Collaborative Learning Fabric – discussing 1Q13 at CDNA G+ Community
  • Self-Selection and Ownership – customization of the learning agenda
  • Motivation and Growth Mindset – removing fear of not-knowing
  • White space – exploring and exposing the creative urge
  • Social, Team & Project-based Learning – is all learning truly social?
  • Key Stakeholder Roles – including Community involvement, and the notion of Resilience
  • Open Knowledge Frameworks – via a 21st century read of Kant
  • Virtual Environments – the purposeful evolution of distance learning and e-Learning

Under the hashtag #cdna (for “collaboration DNA”) we have begun to explore what it means to learn deeply and learn together, across all the contexts described here.  To get at the issues more directly, we will use this space, related posts on the book site, and other spaces (join our CDNA G+ Community) to expand on what we mean by the practice of KM, OD and Education in the context of learning.

Change demands new thinking.  And as you likely know by now, that is the sort of discussion that  keeps me up at night.  I would love your input and ideas.

My fear is that increasing numbers will someday fail to learn how to learn.  It’s a slippery slope with serious implications.

We’ve got work to do.

KMWorld 2012 Workshop W5: Exploring the Flow of Insight, and the Future of the Learning Organization

By now you know I have lots of say about the future of KM.

I’m more excited than ever to be hosting a 3-hour workshop on TUES 10/16 at KMW12, in Washington.  It’s Pre-Conference Workshop W5, and seats are still available.  I’m on right before Dave Snowden, so perhaps you can come out to see us both.

In my last KM post, I shared my ideas on how KM might evolve.

That discussion, which became the outline of Chapter 19 in The DNA of Collaboration (now on Amazon), is also the foundation for my upcoming KMW12 Workshop.

What are the big ideas?

As I looked at how information moves in organizations, I found that it tends to get stranded more often than not.  The metaphor of a river loomed ever larger for me as I wrote. Senge cites David Bohm’s “leaves on the river” metaphor in The Fifth Discipline, and the more I reflected, the more it became a grounding concept for me.  John Hagel has contributed much re: moving from stocks to flows. And I was intrigued when Beth Noveck, former Deputy CIO at the White House, mentioned rivers in her recent TED Talk.

Potomac River, Leesburg VA

Ultimately the concept of flow is where we need to be, because it stands in stark opposition to the prevailing business paradigm, the hierarchical silo.

Flow opens the floodgates of possibility, so to speak.

We can move around barriers, choose new channels to follow, and adjust to the environment as needed. How can we make insight flow faster in organizations?  Here are some key themes:

  • Collaborative Cultures – that foster trusting behavior and learning, in all its dimensions
  • Room to Take Risk – as the path to learning (it’s ok to be wrong)
  • Framing and Messaging with Rigor – focusing on semantics and critical thinking to best define our problems and solutions  
  • Intention – as foundation for focusing our vision and the baseline for demonstrating integrity

We’ll touch on all of these themes in our workshop, and they flow (quite literally) throughout my book.  They are essential aspects of what it takes for KM to be successful. They are core enablers of learning, and central to effective collaboration.

We need to get better in all of these areas, if we hope to start solving tougher and tougher problems.

What’s most exciting of all?  When we apply our new metaphor … when we let our insights flow .. the feedback and new perspectives can be rapid and unexpected.  I’ve had this experience at #SMCHAT #ECOSYS and #CDNA.  As we begin to communicate and connect more easily, our ability to learn from our learning networks gets better. The pace of learning compounds at an accelerating rate.  It’s pretty exciting actually.

Here’s a quick look at some KMW12 W5 Highlight slides (PDF), pulled from my W5 master deck.

Again, I’d love to see you in DC at KMW12.  If you can’t make it, watch for takeaways at the event hashtag #kmw12 or at the workshop stream #w5insight.  As I say in my book, we’ve got lots to cover, and the current is strong. Let’s get started.

Chris

The Value Stream of 140c: The Why and How of Sharing Good Ideas

In NYC this week, #140conf is pulling back the covers on “meaning” in the social context.  Over at #e2conf in Boston, they’re taking a hard look at Enterprise Social, aka #e20.  It’s a unique opportunity to take a checkpoint.

What is our intention for engaging via social media?  Why are we here?

Sometimes it can feel like a very large echo chamber, but I think that’s self-inflicted. In short, we’re not focusing on the value in front of us. Here’s my take:

The value of social is linked directly with our content equity .. our ability to recognize, expand and share good ideas in the marketplace.

Sounds like a mouthful, but its easier done than said.  The best way to accomplish this in Twitter is to be focused and intentional in what we tweet about, putting thought to what we’re saying and who we’re trying to reach.  And it starts with a well designed tweet.  A powerful tweet has 5 primary elements, to drive maximum value:

  • Your opinion. This is the value add that you provide to the content. It’s the essence of social media. Without this, you’re simply passing the raw idea on “as is” without benefit of your experience.  You play a HUGE role in interpreting the content.  I think it should appear first in the tweet, for maximum impact. Often saying “YES” or “AGREE” or “+1” is enough.
  • Idea Frame (aka the Headline). What is the big idea?  Be creative.  Succinct.  Relevant.  If you’re RTing a poor headline from another source, now’s your chance to fix it.  I try to put it in quotes, so it’s clearly the main focus.
  • Link to long-form content (use a shortener, like bit.ly). There must be a link to valuable content, even if (and often especially if) it comes from someone else. It’s possible to deliver meaning in 140c, but it’s easier to deliver it in a 350-word blog or white paper, then amplify/discuss it in 140c.
  • Credits. Who is behind this great idea?  Use their Twitter-IDs.  I use “by” for the author and “via” if its a referral.
  • Context (aka the Hashtag). Without relevant connection points, the content in question lacks context. Who cares about this idea? What communities or thought streams need to know? A tweet without a hashtag has a significantly shorter half-life. This is perhaps the single most under-utilized aspect of effective #140c engagement.

And you’ve got 140-characters to do all that.  Get to work :)

As T.S.Eliot said, constraints force the mind to its maximum creativity.  All these elements matter.  This is both art and science, really.  The most valuable and meaningful tweets reflect the DNA of good ideas.

In the social space, many, many smart people are out there, and they’re eager to share their great ideas.  That means we have an almost limitless opportunity to drive/extract/expand value by participating in the exchange.  Our role in the social marketplace is about connecting on quality content and bringing it forward, enhancing it, making it better, more relevant, more useful .. and yes, #140conf folks, ultimately making our collaborations more meaningful.

I’m in the back channel for #140conf (NYC) and #e2conf (BOS) this year, but that doesn’t mean I’m not a part of the fray. If you want to discuss this further, you’ll find me at the event hashtags as well as my home collaboration tag: #cdna.

See you online.

KM’s Evolution: the “Connected Organization” and the Emergence of Knowledge Networks

CHARLOTTE, NC. April 2012, by 

Knowledge Management can flourish in organizations where the interplay of ideas is valued, where insights are prized as critical raw materials. Unfortunately, that’s not in enough places.  KM, as a practice, remains mired in old thinking.

Let’s take a fresh start:

It’s time for KM practitioners to start sketching out a new collaborative paradigm for the enterprise ..

No small strokes here. So let’s put some stakes in the ground.

For a foundation, let’s return to Ikujiro Nonaka (2001) who gives us 3 major themes that have more relevance today than ever:

  • Flow of Insights, as Process.  The most fundamental change in the KM paradigm must be moving from structure to one of flow as the prevailing metaphor. Insights flow through organizations, they don’t live in hierarchical boxes. When they live in silos, they’re often trapped there. KM must foster flow across silos, and sometimes (with appropriate policy and security) across the firewall. I believe KM’s convergence with social networks helps us think about how insight truly flows, representing a key inflection point for what is possible ..
  • “Ba” as Time, Space .. and Opportunity.  A Japanese term, “ba” can be thought of  (in my words, attempting to apply Nonaka’s) as “favorable conditions in time and space for knowledge emergence to occur”. It could be a conference room, an office, or space by the water cooler, but regardless of place, the chance for emergence is heavily influenced by culture and values. KM practitioners need to facilitate the creation of ba, and I’ll argue that in the 21st century, such places can be either physical or virtual ..
  • Care.  Many (people, organizations) have lost sight of their core values, the deeply felt imperatives that motivate and inspire us to act; in cases where they’re stated, they often fail to enter into our day-to-day use. Ownership and compassion make a difference in KM. Unlocking the value of KM requires a return to priorities, motivators, and intention ..

For a leg up on business context and the value of KM to the enterprise, I like going to Thomas Stewart (2001) with his clear perspective on challenges of how ideas are viewed in the enterprise space:

Value of ideas isn’t taught in traditional economics; it’s treated as a mysterious, outside force .. (but) a company in the information age is really a beehive of ideas, impacting how they should be setup, and run, and how they should compete.

An evolved, future-state KM needs more grounding in business and the business process, as envisioned by Nonaka and contextualized by Stewart. Sharing knowledge (first as insights, then ideas) must become second nature.

The adoption of this thinking has, in many ways, remained painfully slow. Andrew McAfee (2009) helped to set a new baseline for what’s possible, but he’s quick to point out that tech adoption often takes much longer than we’d prefer.

But it doesn’t stop us from charting a course.

Framing KM as a new paradigm allows us all to rethink what happens when insight truly begins to flow more freely through organizations. Hold this mental model:  insights are the raw material of new ideas. New knowledge is the downstream outcome, the catalyst and source of innovation.

We need accessible semantic framing for KM to have a chance.

I like to think of a new, emergent KM as “Getting Smarter, Faster” .. a more conversational, real, and tangible frame for KM and the flow of insights. Many of the terms and concepts in traditional KM (include some used in this post) won’t resonate with C-Levels, including, unfortunately, “ba” and “social” ..

As we rethink the framework, let’s try this:

Enterprise 2.0 may ultimately transform KM .. so that what emerges will be the “Connected Organization” .. creating new chances and spaces for people to exchange ideas and redefine possibilities ..

Connections like these happen at many levels, often spontaneously and in the moment. Email is not effective for this. Encounters at the water cooler leave too much to chance.

Ultimately, we are social creatures. We have an innate desire to connect with each other, and at some level, to help each other. But such thinking doesn’t go far in our commercial spaces.  This is where we need to rethink and apply Nonaka’s “care” as a focus, a priority, a core “intention.” My take on the challenge:

Corporations, in general, have failed to recognize the tremendous generative power in fostering white space and open linkages ..

Let’s take a confident step in the direction of E2.0, taking McAfee’s lead (in my words):

Social technologies offer the potential to serve as a KM catalyst, helping people connect in intuitive ways, when the need becomes apparent .. and we need to find ways to leverage them ..

Collaboration DNA (2012) .. my first book .. is where I’ve assembled the scaffolding for these ideas over the past 3 years. It will be out on Kindle soon. I’ve acquired a deep appreciation of linkage between KM and the collaboration process, and the role that technology can play to transcend historic barriers.

Both KM and collaboration depend on the exchange of insight; both aspire to create synergy from the engagement of independent thinkers; both struggle to function across organizational silos.

Steven Johnson has had many powerful things to say about the flow of ideas of late, but I think it was Peter Senge who first pointed out that KM and collaboration are two sides of the same coin.

Let me tie all this together:

KM needs to traffic in the flow of insight, building formal and informal Knowledge Networks as foundations of the Connected Organization ..

Exchange of insights, in the end, is the catalyst that makes innovation happen. Yes, there must be a process, and KM can help us invent the new one. It needs to be embedded in operations. And ultimately, it must have time, space .. and intention .. to flourish.

We’ll be expanding on these ideas here, and elsewhere.

Many of you have helped shape and validate my thinking, each insight a catalyst for the next. Thank you for your many contributions. But we’re only just getting started ..

As always, there’s still much work ahead, and as always, I’d love your insights.

***

Notes: see Suggested Reading side bar re: Goleman (1995, 2005), Kuhn (1962), Senge (1990), Wheatley (1996), Johnson (2010); links to books by Nonaka, Stewart and McAfee are in-line above. 

21st Century Kant: Learning to Frame Knowledge Anew (w/ help from Aristotle & Wittgenstein)

Some have spent years studying Kant and his Categorical Framework for knowledge, first published in 1781.  I am absolutely fascinated by the implications of Kant’s maddeningly simple chart.

Can it be a framework for all knowledge?

Can we somehow bring this structure into our modern, 21st century understanding of how we think about knowledge itself?  I think we can.

Kant argued that his 12 “intuitions of the pure understanding” existed a priori, ie., prior to any observable experience, and as such, were fundamental precursors to any knowledge framework.

What appears below emerged from research I’ve been doing on the history of philosophy and science, summarized on a prior post on Divergence.  In that earlier graphic, it’s no coincidence that Aristotle is at the top and Kant is in the center, flanked by left-brain dominated science, and right-brain dominated philosophy, modern distinctions that weren’t evident back then.

(c) 2012 Chris Jones @sourcepov

I’ve attempted to accurately capture commonly used key words for each element of Kant’s Framework. Below each of these, in blue, I’ve provided some more modern phraseology.  And I’ve indexed Kant’s 4 Categories (columns A-D) and 3 Dimensions (rows 1-3) for discussion.  Click on the chart to view it larger.

New thinking? That appears in the far right column, also in blue.

Think of each phrase as a semantic symbol for each of 12 categorical dimensions that Kant offered us in his 1781 “4×3” framework.  Keep in mind, translation from German can introduce some ambiguity.  So can the mountain of doctoral dissertations on this topic in the intervening 230 years.  [Note: as I’m likely trodding on well-worn ground of others, please alert me to appropriate authoritative attributions that are due; I will add citations.]

Wittgenstein has been an important voice in my thinking.  In rationalization of knowledge frameworks or, really, anything as abstract as knowledge itself, the semantics are extremely important – especially with Kant.  Two other frameworks I wanted to throw in the mix here:  (a.) Aristotle’s 4 Causes, and (b.) the structure of western language itself, using English (my mother tongue) as a basis.

(c) 2012 Chris Jones @sourcepov

With that as an input, let’s tap Wittgenstein-thinking re: language in hopes we might identify some semantic connections lurking in Kant’ framework.  Let’s convert the conceptual symbols in the framework into sentences, to see what happens.

Walking the 4 columns.  First, we’ll test Kant’s framework as viewed through our updated, 21st century semantics to examine Kant’s 4 Categories (the columns) more deeply.  As we do, focus on my verbs (bold) that I’m using to evaluate each row in that column (underlined).  This allows us to see what’s happening analytically at each level of intuitive comprehension.

This forms the outline of a new analytical model based on Kant’s framework.

  • COL A. CREATE A CONCEPTUAL FRAME.  “I comprehend one archetype, I observe many examples in reality, but I can only imagine the complexity inherent in totality of the real world”
  • COL B. ESTABLISHING EPISTEMOLOGICAL CONTEXT.  “I recognize one state of actual reality, I hypothesize an ability to disprove events in such a reality, but I can infer that a true reality is constrained by a hybrid mix of limitations and constraints”
  • COL C. EXPLORE CHOICES. “I understand that there is an atomic, self contained archetypical concept, I may be able to prove the causal relationship of objects (the instantiations of concepts), but I can only attempt to interpolate the complex interdependency that exists among them in the real world”
  • COL D. SYNTHESIS (REAL-WORLD, COMPLEXITY). “I realize conceptually that something is possible, I conclude that empirical testing may prove it to be true, but I learn that true interactive dynamic is to be highly contingent on context, initial conditions, and other real-world factors”

The first verb in each sentence has a Philosophical heritage, the second is Scientific, and the third is new, deriving from real-world complexity.  From this construct, I saw a pattern.  Here are the verbs in table form, mapped onto Kant’s Framework, with conclusions at right and at bottom, so this is more clear.  I switched rows and columns around (3×4, instead of 4×3) to force a different perspective.  I am learning that such changes in point of view are essential to fully realize critical thinking.

(c) 2012 Chris Jones @sourcepov

Walking the 3 rows.  For one last test, we’ll check for coherence of the model, essentially applying the representative triggers for each node of Kant’s framework.  Again, the operative notion from Kant’s model is underlined in each case, using symbols derived from the first table above, read left to right.

  1. “One reality is possible” (philosophic context – the archetype, ideal case)
  2. “Many experiments will validate a truth” (scientific context – the dynamic, empirical case)
  3. “All constrained interdependencies result in contingent adaptations” (real world context – the complexity case)

There’s a certain logic emerging here.  For me, viewed in this light, Kant’s framing hangs together a bit better now, with a little help from Aristotle (on intention) and Wittgenstein (on semantics).  The traditional 4 category names – “quantity”, “quality”, “relation” and “modality”, as translated from the German – didn’t resonate with me when I first came across them.

I see Kan’t early ideas on complexity in the bottom row of his model, the ultimate dimension in which the effect of the real-world takes hold;  science runs through the middle; philosophy is at the top.  Context?  It is shifting throughout, as we move through various modes of abstraction.

That’s the magic of how we think.

[Note: Another framework that I believe is relevant for further study is Bloom’s 1956 Taxonomy for Learning, updated by Anderson, et al, in 2001.  The table dimensions have interesting similarities, but that’s a comparison for another day.]

I’m hopeful this is a foundation for the epistemic convergence that I was mulling in my prior “divergence” post.  Have we unpacked Kant after all?  Is all knowledge represented?  We certainly gave it the good old college try.

Challenge me.  What do you think?

Ahead in 2012: Intention & value systems in our culture. And a book.

New Years Day, 2012.  What better time for a checkpoint?

My research has begun to converge.  I’ve posted a recap of key themes at about.me but for now, I’ll follow custom (very retro, I know!) to recap my 2012 resolutions:

  • R1. Intentionality in all things is the new reality of our busy lifestyles, and a grounding principle for heavy multi-taskers who still care about following-through and doing quality work;
  • R2. Examine culture in the context of values & ethics to advance our work from 2010 in the culture series; frankly, we’re way past time for critical thinking in our value systems, especially where there are deep, systemic challenges like the K12, E20 and GOV ecosystems;
  • R3. Publish my book which is a deep dive in the collaboration space; stretch goal: March.

Pretty excited about the last item, as you might imagine.

And what of that last “Divergence” post?  I’ve been reflecting on the implications of that stream, and the many ideas that emerged from my last post on knowledge frameworks.  I’m very excited that it spawned so many comments – on here, Twitter, G+ and several other blogs.  The next post in the critical thinking stream will be an aggregation of key Divergence takeaways.  My recent Kant post (with subsequent discussion on G+) is attracting great inputs too; to me, to me, it’s so darned interesting :)

Upcoming posts show up in the side-bar at right, serving as an editorial calendar.  Specific dates will need to float, but at least there’s a sequence.  I’m always interested in your feedback on where we should focus next.

Expect more major innovations at ECOSYS, with a new blog now online.

A method to the madness?  I’m working on it!

Can’t thank you guys enough for your time, insight and ongoing engagement.  I think it was Jefferson, writing on the power of expanding knowledge and education, who used the metaphor of the candle (then called a ‘taper’) with the unique ability to spawn a new flame without diminishing the old.

That is happening each and every day in social spaces. Exciting stuff.

Stay tuned for more here, and I’ll see you online.

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The Divergence of Thought in Science & Philosophy: Could “Complexity” be New Common Ground?

CHARLOTTE, NC. October 2011, by Chris Jones

“Where does my world start and end?” asked the bird outside the cage.

Knowledge is a gift best appreciated when we don’t try to think about it. As a topic of focus, it frequently defies words. It grows more elusive as we attempt to draw closer to its source.

And, though we make complex decisions every day, we routinely fail to grasp what it means to truly understand something. For many reasons (outlined elsewhere in this thread) we fail to engage what’s presented in a discerning way.

My research on critical thinking is making one fact crystal clear: it’s high time we raised the bar on how well, and how deeply, we dare to think.

So let’s unpack the concept of epistemology. To most, it’s hopelessly obscure, a word dying to stay hidden in text books. Yet it’s a vital to understanding a foundational divide in Western thinking. I define it like this:

An epistemology is a holistic framework for knowledge, giving us a set of consistent, simple rules for how we should describe that knowledge and apply it in practice.

Looking back over the centuries, 8 famous epistemologies dating to Aristotle, Bacon and DesCartes mark clear fault lines between science and philosophy. It is a separation between those who think in terms of empirical ’cause and effect’ vs. those who tend to think more intuitively, in ‘patterns’.

Evolution of Knowledge Frameworks (c) 2011 Chris Jones

Both modes of thinking have, in the long run, proven fertile. The problem that developed was an all-or-none orientation. The rift was widest during the 19th century, as Hegel and Mill battled for mind share. In the wake of this, sadly, a long standing respect among academic schools of thought was all but gone. And the lingering cultural effects continue to impede progress across many domains, ranging from business to government to public education.

In the 21st century, we can only look back at the damage that’s been done, and ask “why”?

Thankfully, neuroscience is proving a potent field of discovery, and it’s helping us better unpack how the human brain works, yielding important insight on the psychology of thinkers. Back in the 1970’s, in the earliest stages of discovery, we thought we could isolate reason to one region, or imagination to another. But our first steps were tentative, and sometimes wrong. More recently, a more coherent picture is beginning to take shape. Here’s what’s being concluded now:

  • Our left brain is our associative center, the home of “cause and effect” thinking, the place where we focus and categorize and label every detail. It is where we refine what we already know. Think science. Think public education.
  • Our right brain is the hub of our pattern matching capability, where we seek new information that arrives in diverse or unfamiliar forms; it’s where we scan the environment, search for clues, and try to relate ourselves to the world around us. Think philosophy. Think ethics. Think culture.

It would appear that key thinkers of our time, and whole schools of thought that emerged under their guidance, have a strong bias in their cognitive models.

Perhaps it’s not surprising then that the pursuit of knowledge over the last 2,500 years has been split into two camps: the left brain camp of empirical science, and the right brain camp of the intuitive philosopher. Thanks to the industrial revolution, science has generally won most of the debates. Philosophy has not fared well, losing anything resembling critical mass.

But all that can change, and I do think there’s hope.

Ultimately, it’s a question of restoring balance. Where science struggles for context and where philosophy struggles for anchoring, the two worlds share a common ground that, ironically, has always been there. Often shrouded in it’s own complexity, I present to you:

The real world.

Rather than argue the point, I’ve shown the two divergent branches of knowledge in the graphic, above. I’ve identified 4 leading thinkers and their knowledge frameworks aka epistemologies in each branch. As we near the present day, you’ll notice fewer discrete frameworks, and a dearth of contributions from the philosophical ranks. But there’s also a convergence of sorts. The real world lies in the middle, balanced, as it were, between two cognitive extremes that, by themselves, cannot describe our reality in a holistic way.

We need both halves of our brains to function. To reason. To imagine. To understand.

As I was finalizing the graphic that helped me bring this post to words, I came across an intensely fascinating, and highly relevant TED talk by Iain McGilchrist. Thanks to Jennifer Sertl for teeing it up on G+.

I’m seeing a harmony of thinking made possible when a greater share of our left-brain and right-brain mental resources are tapped. There is much negative thinking to undo; we must move outside some exceedingly strong professional paradigms. But as we do, I see us replacing conflict and stalemate with a genuine hope for new possibilities. I openly wonder what might happen when we embrace empirical facts and rational insights in their full, raw, hopelessly unrealized potential. Stephen Johnson says great ideas come from other great ideas. So it’s time .. high time .. we get scientists and philosophers talking again. There will be a richness in the diversity of their epistemologies that will foster the new ideas we need.

The topics?

  • New epistemological frameworks for complexity.
  • New common ground for a world that is hopelessly in need of it.
  • A fundamental rethinking of how we frame public education.

For the scientists needing proof? Look no further than the K12 Ecosys.

Pencils down, folks. Let the deep conversations begin again.

Lakoff on Metaphor: Rethinking how we Frame and Unpack Complex Problems

Our critical thinking series continues in the language space, focusing now on perhaps the most powerful tool of all: the metaphor.

Like the words and grammar of language itself, metaphor is a crucial, foundational aspect of effective communication, and it’s one we tend to take for granted.

Metaphor is a way to create common ground. It pulls from what is ultimately shared or sharable human experience. And it serves us well not only as a literary device, but also as a versatile, robust element of our cognitive thought processes. We use metaphorical frames when we think, when we speak, and importantly, when we collaborate. And because of their versatile reach to bridge our thinking across diverse subject areas, they may well emerge as a new approach for grappling with problem complexity.

To explore these possibilities, let’s start with a working definition:

Metaphor is a mental/linguistic technique that helps us understand a complex concept by relating it to our more concrete, observable experiences; by comparing two discrete ideas, we expose similarities and can infer logical relationships.

While we employ metaphors frequently in everyday speech, the mechanics of the technique often remain a mystery. Metaphors have the power to clarify and enlighten, but we seldom use them intentionally to make a point, or work to find ways to leverage their full potential.

In “The Metaphors We Live By” (1980), George Lakoff and Mark Johnson lay down a rigorous argument for why metaphors matter, laced with interesting and compelling examples. They build on Wittgenstein’s concern (from a half a century earlier) that academics, philosophers and scientists have tended to talk past one another, speaking from their own paradigms and being generally unwilling to recognize – let alone embrace – frameworks in use among other camps.

Some examples are in order.

First, let’s introduce several commonly used cultural metaphors that are core to our Western way of thinking. I’ll state the metaphor then I’ll provide some related ideas that might flow from it:

“Time is Money” – how do you spend your time? – I’ve invested lots of energy on that project – I can’t waste any more time on that
“Organizational Politics is War” – he defended the point – her criticisms were on target – his ideas were shot down – let’s develop a plan of attack
“Public Education is a Factory” – is the system working? do we need common curriculum standards to ensure compliance and quality? – are we forcing students to fail when they don’t match a specification or comply with schedule, as if they were defective parts?

Clearly, our history flows deeply through our culture and our language.

Sometimes using more than one metaphor to analyze the same abstract concept is useful. Per Lakoff, when held up side by side, the various metaphorical comparisons may not be consistent because they describe different aspects, but to be effective, metaphors should be coherent, that is, without spawning conflicting views.

Consider these examples:

“Problems are Puzzles” – we need to take it apart – how do the pieces fit?
“Problems are Journeys” – we’re on the wrong path – we’ll add more elements along the way – do you think we will discover a solution? – that idea could drive us in an entirely new direction
“Problems are Containers” – that idea is out of scope – we need to pull in more expertise – your concern is at the core of a very strong argument
“Problems are Buildings” – that issue is foundational – we need to build some case studies for this – we need to architect a different approach – that point could help us unlock further dialog

These metaphors are both consistent and coherent. We can use virtually all of the descriptive phrases interchangeably. Each helps to address specific perspectives of what a problem is and how web might attack it, with generally intuitive results. As we do this, listeners will tend to subconsciously resonate (sometimes emotionally) with one aspect or another.

Here we expose a cultural challenge. Though metaphor is present in everyday speech, the injection of subjectivity and emotional response into problem solving has historically sparked concerns for scientists, academics, whole schools of philosophers, and many in the business world. Why? Because we live in a Western culture that prides itself on its highly rational objectivity. A presumption of factual certainty has overtaken our thinking, and made metaphor an enemy of precision.

Case in point? Let’s circle back:

“Public Education is a Factory” has become an increasingly popular metaphor (employed by both Clay Christensen and Sir Kenneth Robinson) that sparks widely different responses from educators, academics and parents. Many practitioners, for example, will have an immediate negative reaction. Arguably, from a professional vantage, this clearly can’t be true; it is in conflict with a deeply held vision of education. But if approached with an open mind, metaphors like this one can start a useful dialog. In what ways are schools like factories? What are the implications? What can be done to about it? Deeper, more highly invested conversations tend to energize a serious, intentional discovery exercise. Metaphor can literally get people to think outside their silo’d mental models. When we encourage subjectivity in thinking, we can open minds (our own, and those of others) to new ideas. When collaborating, we provide stakeholders multiple ways to relate, sparking deeper engagement. By tapping personal experiences, a broader portfolio of relevant ideas can emerge.

Doesn’t this help us with critical thinking in general? I say yes.

Though many see critical thought as a reductive exercise (harkening back to the world of objective science), I think we need to train our minds for expansive thought as well. Effective use of metaphor exposes diverse aspects of our ideas. Besides shedding light on how we think, we understand better how we relate to each other. Do we agree? Do we disagree? Why? And all the while, we’re developing an ever richer solution language, steeped in metaphorical insight.

Again, intentional collaboration ultimately seeks to establish and expand upon our common ground.

Metaphor can help us get there.

Lakoff says a metaphor works if it advances our understanding. I’m seeing some compelling possibilities. Are you?

Words That Matter: Wittgenstein and Senge on the Power of Language in Critical Thinking

Language, like the culture it derives from, plays a subtle but powerful role in how we interact with others. Yet we are so completely immersed in it, we scarcely give it a second thought.

Early in the 20th century, Ludwig Wittgenstein brought focus to the critical importance of language in the context of knowledge, philosophy, and science. One of the more powerful and accessible claims he framed was this one:

“The limits of my language mean the limits of my world.” Wittgenstein, Tractatus, 5.6 (1921).

It may seem overstated at first glance, but let’s unpack it.

If we reflect on how we think about, evaluate, and come to understand virtually anything, we realize that the running voice of our conscious thought sets practical boundaries. We can contemplate problems and solutions in our mind only to the extent we have words to describe them. Our vocabulary either limits or unlocks our ability to describe what we see. Our command of grammar and ability to construct descriptions of abstract concepts works the same way.

Our command of semantics is a central to critical thinking.

Language literally bounds our possibilities.

Wittgenstein thus underscores a compelling argument for mastery of the original liberal arts of grammar, rhetoric, and logic – skills that we might better grasp today in the modern context of reading and writing – but his message is clear: the tools of language are essential to the thinking person.

Now let’s apply those ideas in the social and collective contexts.

What happens in a team setting?

Carefully articulating a new idea for ourselves is only half the battle. As collaborators we face the more difficult but critically essential task of explaining this idea to others. What words do we use? What language will our audience understand? And if we’ve followed good practice by ensuring a diverse group of collaborative stakeholders, the bar has been raised even further: what subset of our shared language will be most effective to ensure common understanding across a diverse team?

From my experience, the most common failure in team settings is mis-communication of ideas, most readily observed when group members freely, often unwittingly, talk past each other. In a fervent effort to make a point, we default to arguments grounded in our semantics of origin. So what happens? IT folks will talk technology. Accounting will talk about margins. Sales will talk about customer problems. Educators will talk about pedagogy. Academics will talk about epistemologies. With heightened energy, the vocabulary grows increasingly parochial and inaccessible, and the steeper the organization’s silo walls, the more entrenched the participants tend to be, and the more difficult language barriers are to cross.

No wonder finding common ground can seem like a pipe dream.

So intentional collaboration places clear demands on semantic foundations. Defining key terms often helps. Project glossaries can go a long way.

Another strong approach (referenced previously in this blog, and elsewhere) is that of a solution language. The idea is to create common ground on the output side. We can define terms for the proposed solution set(s) that are literally grounded in a new language that is embraced by all. It is an extraction from the contributors’ source languages, an amalgamation of pieces and parts to create a viable whole. As the solution language is built, common ground is established in the process. In so doing, collaborators become more aware of their context of origin, better described as their comfort zone. With time and energy, many will see how cultural and linguistic boundaries can impact their collaborative engagement.

Peter Senge in the 5th Discipline, observes:

In dialog, people become observers of their own thinking.

then cites the work of the late physicist David Bohm, who researched collective learning among scientists. Bohm believed that we, as individuals engaged in collaborative dialog, can:

“… begin to correct incoherence in our own thinking. A kind of sensitivity develops that goes beyond what is familiar … (exposing) subtle meanings that lie at the root of real intelligence.”

Senge and Bohm share a deep sense for the requirements for team-based learning. Senge himself devotes many pages to language, and the evolutionary steps through which individuals must navigate to achieve value from a shared, collective learning model. Often, it means suspending bias inherent from professional education and what is often years working within a given specialty.

Thomas Kuhn’s thinking on the challenges and demands of paradigm shifts peers from these lines.

Wittgenstein’s foundational messages ring true throughout.

It’s easy to imagine ourselves standing before the locked door of critical thinking. We hold the keys in our hands, but remain dumbfounded about how to use them. When we attempt to collaborate, we stand before the same door with others, but we’re still at a loss; perhaps it’s even worse, arguing the course of action.

Language, like culture, is a profoundly rich, integral aspect of our social existence. I’ll summarize it like this:

Language is the master key to unlocking effective collaboration, opening the door to possibilities of what we can accomplish via intentional, purposeful dialog with others.

We can cast all this aside, broadcasting our views to the world at will. We can choose empty words with casual intent to impress, or use caustic words that serve only to bully, blame and obscure.

People do it every day.

The price? It’s a fundamental failure to be understood, preempting an exchange of ideas that could have emerged into something more. That spells disaster for progress in any language.