Learning in the Moment: Navigation Strategies for the Flow (or Flood?) of Insight

Can learners improve their skills at navigating in the sea of insights?

How can we learn when the flow of information seems overwhelming?

 

CHARLOTTE, NC. April 2014, by 

While common core standards draw the spotlight & ire of educators and parents alike, perhaps we are looking past a more practical and useful question:

“How might we improve our ability to learn in the moment?”

The human brain is a complex place, and there are many ways it processes new information. If we look beyond the “talking head” classroom model, we can already find a raft of alternative learning experiences, ranging from visual learning, team/design models used heavily for project-based scenarios, as well as situational and immersive learning offered by some public systems, GT programs and specialty schools.

What is common in all of these alternative models?

I believe they require .. and build .. competency in real-time processing of information. Quite simply they help us to focus, to interpret, and evaluate new inputs in the moment, using a variety of senses and external stimuli.  People.  Images.  Crossover concepts.  In the sea of information that is cable TV and the internet, that is no small achievement.  In fact,

“Building competency for real-time learning is increasingly critical. Students (of all ages) need to recognize, evaluate and prioritize new insights in the moment, pulling value and meaning from the tidal waves of information flowing past us.”

What does this imply in a practical sense?  I think it’s a significant change of thinking.  It could challenge our pre-conceived notions of how we, as individuals, learn best in 21st century conditions of information overload.

More and more, facts and dates seem less important than the causes of things, their trends, and emerging patterns.  Sure, facts and dates are key inputs.  Together, they can tell a story.  But without the ability to interpret them and apply them in context, we are simplify left with a sea of facts and dates.

In a combined #cdna and #ecosys this MONDAY 4/14 at 8pm ET, let’s explore the notion of “learning in the moment” and we’ll use the metaphor of splashing in water as our metaphor of choice.  Why?  Few would argue that information is crashing constantly around us.  It’s an endless flow, a frothing sea that many perceive to be overwhelming.  It’s time 21st century learners .. which is all of us .. become better at discernment and learning in real-time.

  • Q1. What factors have you seen block learning in real-time?
  • Q2. What limitiations does structured knowledge-based learning (facts, dates) place on us that critical thinking does not?
  • Q3. How should we define critical thinking (in this context?)
  • Q4. What value does a fluid insight have over fully-matured facts, data, or other crystallized knowledge artifacts, and why?
  • Q5. How can we make “learning in the moment” more immediate, accessible, and top of mind?

I hope you will join our real-time conversation using combined hashtags #cdna and #ecosys on MON 4/14 at 8pm ET. Twitter is one of my favorite immersive mediums for learning.  Depending on who you choose to follow, out twitter streams (!?) themselves can provide a steady flow of powerful insights.

You might just say we’re learning all the time.

We try to meet in this same time slot, every second Wednesday at 8pm ET.  We’ll be diving into the deep end (!!).  Bring your favorite flotation device.

See you online.

Chris aka @sourcepov


Additional reading

  • Anderson, Lorin W. et al. “Taxonomy for Learning, Teaching & Assessing: Revisions of Bloom” (2001)
  • Dweck, Carol S. PhD. “Mindset: The New Pscyhology of Success” (2006); provides foundational thinking re: “growth” vs. “fixed” learning mindset, I think a key factor here
  • Gladwell, Malcolm. “Blink” (2005)
  • Herbert, Wray. “On Second Thought” (2010); provides excellent insights on Mental Heuristics, a key aspect of this discussion
  • Jones, Chris. “The DNA of Collaboration” (2012); this post expands on my thinking re: collaborative and social learning; for more on these ideas, see Ch.6 on Metaphor, Ch.8 on Listening, Ch.9 on Mental Heuristics, and Ch.20 on Critical Thinking; see also related posts on the book’s website, http://collaborationdna.com
  • Kahneman, Daniel. “Thinking, Fast and Slow” (2011)
  • Lewin, Kurt. “Action Research” article, Journal of Social Issues 2(4) (1946)
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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.

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?

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

CHARLOTTE, NC. October 2011, by

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.