How I Learn

Learning from my connections on LinkedIn

About a month ago I posed a question on LinkedIn about how effective social software systems including LinkeIn are at supporting learning. This provoked much useful (to me anyway) discussion, which I summarized earlier. But one comment in particular stuck with me. Jon Husband, originator of the organizational design theory of wirearchy, pointed out that you get out of a learning network what you put in. So for the past month I have been working hard at using LinkedIn (and to a lesser extent FaceBook) as a learning network. It has been working.

I have done this primarily by seeding questions I am interested in into my network and provoking discussion. This has been successful in a number of ways, with success seeming to depend on the nature of the question and who I was able to draw in to the discussion.

I began with a somewhat technical question.

Is there a standard semantic model for business strategy frameworks?

"My new company LeveragePoint is built on a semantic platform (SMW+, triple store, etc.). Our business is to support the activation, embedding and evolution of strategies at organizations, at this point we focus on marketing strategies. The platform integrates the implementation and communication of strategies with learning and collaboration. We try to be as standards based as possible. We use DC and FOAF and are implementing SKOS and SIOC. Is there something similar for business strategies? If not is there anyone interested in developing one with us? This would need to cover the following types of strategies: Economic Value Estimation, Value Footprint, Segmentation (various approaches), Buying Process, Customer Portrait, Scenario Planning, Sustainable Business Strategies (Green to Gold, Cradle to Cradle)."

This is a more important question than it may appear at first glance. Public vocabularies are the key to the semantic web and if the semantic web is going to be useful for business the vocabularies need to address business needs. Existing vocabularies such as Friend of a Friend (FOAF) and Dublin Core (DC) are powerful in their own domains, but they don’t address business issues. Google’s recent announcement of RDFa support is an example of how not to go about building such a vocabulary. Google’s vocabulary at Data-Vocabulary.org manages to add little to the public domain while ignoring the already existing power of FOAF and DC. Hopefully Google will open up and realize that what they need to be doing is to providing an open index of semantic vocabularies, leveraging the work of other in the same way they use the effort people make to link websites as a way to improve search!

Anyway, on the surface this question had a poor response, only two public answers, but there were also a number of private responses that pointed me in the right direction. Especially useful were comments from my friends at Vulcan that pointed me towards the work that Tom Malone and his group at MIT are doing on vocabularies for organizing business information.

I followed up my business model question with one on RDFa.

How are (will) search engines leveraging RDFa?

"My company LeveragePoint is developing a simple model of how a company's offers (services and products) provide value to its clients and solve business problems. This is a subset of the semantics behind our applications. We may also provide a simple form driven tool to generate this information as RDFa for inclusion on a website. We would like to know if and how search engines would index this information and how they would use it. We are interested in meeting with semantic search companies at SemTech in San Jose this June to discuss."

This provided some very useful exchanges, although again most of these were private. The question drew answers from people at Yahoo, Microsoft and Google that were very encouraging. I think there will be a role for RDFa in the public web and the response to this LinkedIn question encouraged me to begin to develop a business vocabulary to map needs, offers and value to one and other. This is based on Tom Nagle and John Hogan’s work on Economic Value Estimation and links to emerging work on value networks and the economic and value exchanges that flow across these networks. I will share more about this approach in the future, which is being developed under the name NOVO (for Needs Offer Value Ontology).

Enough semantic web geekiness, I thought, let’s explore some ideas around virtual and mobile technologies, provoked by recent experiences with iPhones and Android.

Will mobile and virtual blend?

"I have been thinking a lot about how people use and will use mobile devices. A couple of days ago I began to read Edward Castronova's book Exodus to the Virtual World. Let's assume he is right and living in virtual worlds will become a large part of the economy. Will the mobile and virtual trends continue in parallel or at some point do they blend? If so how? One possibility is sketched in the new novel Daemon by Daniel Suarez where game style overlays give players a critical advantage in the 'real' world."

This question seemed to strike a chord. There were seventeen public answers and another twelve direct responses. The answers caused me to think more deeply about the question and identified some developments I was not aware of. Chuck Hamilton, who is involved in virtual world projects at IBM was especially helpful, pointing me to Bobba. Richard Smith pointed me to a great TEDs talk on the subject. There were many thought provoking responses, I encourage those who are inrested to read through clicking on the links. Thank you to all who contributed. I’ll give Jesse Wang at Vulcan the last word though “So, the real issue is that  the virtual and real world will blend, and mobile will be a key medium to accelerate it..” Wow. I just finished reading Brian Rotman’s excellent book Becoming Beside Ourselves: The Alphabet, Ghosts and Distributed Human Being and I think Jesse is right, the real and the virtual are blending, and changing our identities, our math and how we share and intermingle our ideas.

Experimenting with LinkedIn has been disappointing in one regard. So far most of the questions have resulted in answers to me rather than in conversations with and between my friends. Things went a bit better on my most recent question, which has resulted in more dialog.

Is there such a thing as "design thinking" that applies across disciplines?

"Many people refer to themselves as architects. There are product architects, software architects, network architects, social architects ... And many people refer to themselves as designers. Is there a common set of ideas, heuristics, algorithms and codes that apply across the different design disciplines? Can there be? Should there be?"

This question resulted in eighteen public answers and a number of e-mail conversations between people. It also drew answers from everyone from prominent software engineering savants like Philippe Kructhen (the articles he points to are well worth reading for anyone interested in design), to practicing architects, interface designers and information architects. The only things missing was an old relational database bear (I am still looking to provoke one). There is a consensus that there is such a thing as design thinking and that it needs to be better researched. I am looking forward to doing some design thinking on how to represent design thinking, and I hope to attend and if necessary to host some conferences in this area over the next few years.

So, is LinkedIn a good tool for supporting learning conversations? Maybe. My network is certainly a good place to have these conversations, and by using LinkedIn as a vehicle I have been able to learn from people that were not my direct contacts. This is very good. But, so far anyway, I have not been able to get the kinds of deep multi-directional exchanges I am hoping for (even if the Design Thinking question and answer was a step in the right direction). Is this because of LinkedIn and how it is organized? Or perhaps it is the nature of my friends (we are an opinionated bunch, and not always as good at listening as we could be). Maybe I just need to learn to phrase the questions better and to guide the conversation. All things to think about, and maybe to ask on LinkedIn!

Blends

I sometimes have a bit of a purist streak to me, preferring things straight and unalderterated. But I am slowly realizing that this is just an affectation, and that most things are in fact blends of one sort or another, and that bringing out the blend is one of the most creative things we do. Much learning is based on the blending of two or more concepts or experiences. Several years ago, when I was deep in my puritanical phase, I had a conversation with a French wine maker about the virtues of the single vairetal wines that have been quite popular with many of the better wineries in North America. His comment, "asking a wine maker to use just one grape to bring out the terroir (the way that the soil and climate are reflected in the wine) is like asking a painter to portray a landscape using only one colour." He stopped me short, and I have noticed that over the past few years more and more of the best North American wines are blends.

Linguists and cognitive scientists have made great progress in understanding how human thought depends on conceptual blending and in uncovering the various mechanisms by which blending is carried out. The roots of this work come from the 'blending" of George Lakoff and associates ideas about the foundational role that metaphor plays in all human thought and a large body of thought around embodied cognition.

Metaphor is sometimes disparaged as a lightweight mode of thinking, not to be compared with the rigors of deductive or inductive reasoning. But in fact most human thought is metaphorical, including most mathematics and logic. Take set theory for example, the foundation of much of modern mathematics. Set theory has grown from basic intuitions about what it means to group things together and what things have in common. Apples and pears are each sets in their own right, and belong to the more general set of fruit. Sets can be joined together, all apples and pears, using what is often known as the 'or' operator (all things that are apples or pears). One can also look for the intersection, the 'and' operator (all things that are fruits and are red would include many apples and some pears). Most sets are actually quite fuzzy and are easily extended by metaphor. In fact, sets are metaphors. We can't really think about sets without using concepts such as 'container' or 'feature'. This is covered in depth in the George Lakoff and Mark Johnson book Philosophy in the Flesh (see below).

Embodied cognition refers to a way of thinking about cognition that recognizes that we have bodies that exist in a world and that the way we think depends on this. Sounds obvious, but in fact this goes counter to a long strand of Western Philosophy that goes all the way back to Plato and his Platonic forms (ideal forms that exist independent of any physical incarnation) or Rene Descartes' notion that the conscious mind is all there is to thought. This position is demonstrably wrong. The mind is (i) in a body, (ii) that is situated in world, and (iii) communicates with other bodies, (iv) in ways that it is often not aware of. There are many excellent books on this, the most enjoyable to me being Ed Hutchins' classic Cognition in the Wild. Hutchins looks at how teams of people expose their thought processes when communicating, using the example of how the US Navy conducts coastal navigation and then contrasts this with Melanesian navigation. Hutchins also shows how ideas about navigation get embedded into instruments like the compass or sextant.

These ideas about metaphor and embodied cognition have come together in the model of conceptual blending. Before diving into this (note the metaphor) I want to put this in the context of learning. Most of what we call learning is actually the act of (i) creating new blends within our own minds and with the people we live and work with (there is a social dimension to both blending and learning) (ii) unfolding blends to understand what ideas have been blended together to begin with, and (iii) embedding blends in the things we work with - tools, instruments, drawings, patterns, conversations.

Learning as the Creation of Blends

Most os us learn most easily if we can relate what we are learning to something that we already know. This is the most basic form of blending. When I wanted to learn about American politics (I am writing this as a Canadian living in the United States during a presidential election year) I began by mapping from Canadian notions of democracy, representation, political parties, delegates, platforms, political advertising and so on to what I could understand of US notions. Of course there are many differences, and these sometimes misled me (the US Electoral College that actually elects the president is a complex beast) but there were enough points of comparison to give me my bearings. And as I began to understand how things work in the US, my understanding of Canadian democracy also changed. This is an important point: metaphors that support true learning seldom go just one way, they are dynamic and each of the perspectives blended together can change the other as well as generating a third, deeper perspectives that combines aspects of both.

Unfolding Blends for Deeper Understanding

Learning is not just about creating new blends. Most of what we know, or think we know, is already based on blends. Moving from politics to mathematics, Rene Descartes created the Cartesian geometry that we learned in high school by blending the ideas of the number line and the plane, and then writing algebraic equations into this blend. There are three blends working on the surface here, number lines, the plane and algebra, and of course each of these are already complex blends in their own right. Not that this is how I normally think when I calculate a function on a graph. The blend is now embodied in our language, tools and conversations. "The slope of a curve" sounds perfectly natural to many people, but it actually blends many experiences and concepts: a line inscribed on a plane ('line' and 'plane' are already blends), change, a straight line touching a curved one at a single point, and so on. To really learn about Cartesian geometry, and be able to think about it to do new things, one needs to decompose the blends it is based on and then build them back up. This is hard work, but it is part of the work of learning. A similar approach of taking apart a blend and then building it back up is used by many sports coaches. A golf swing, a tennis serve, or even something as seemingly simple as turning the crank on a bicycle can be broken down into steps, each of which is practiced and perfected, and then put back together as a stronger whole.

Embedding Blends

Connecting the old to the new, unfolding assumptions and clarifying the underlying metaphors, these are just steps along the path. To really learn something one needs to be able to apply it. The concepts, perceptions, behaviours need to get embedded in one's life. Embedding takes place on several levels. The most common is language. We have learned something when it is embedded in our language systems. This requires a community and conversations. Common phrases, abbreviations, even acronyms are the seeds of a languages system, that are fed by common questions, assciations and perceptions. Even something as physical as learning how to ski or ride a bicycle involves a shared language system. Learning to cycle one began with the seat, the handle bars, the pedals and a notion of balance dependent on speed - "go faster or you'll fall over". Over time, if you go on long rides, you talk about hydration and nutrition, cadence, gears and boinking (when you run out of fuel in your blood). Riding as a group one learns to "hold the line", "close up" and various hand signals to warn of danger or encourage speed.

Language systems are just one of the tools we use to express and apply learning. Just as important are the many physical artifacts that encode what we learn. I currently work for a management consulting firm where a great deal of learning gets encoded into Powerpoint slide, themselves a blend of visual representations (boxes, arrows, colours) and words. A compass rose embeds a tremendous amount of learning about the world - that there are directions, on a two dimensional grid, that directions remain constant (OK, so the magnetic poles drift, and the compass needle can be misled by surrounding metals or spun by an electric charge, but its power lies in its constant pointing towards the north). Learning how to embed learning into things is at the heart of design. Think of the dashboard and controls of a car - learning how to use these is learning how to drive, learning how to design them so that they provide an interface between driver and car is central to automotive design.

Learning also gets embedded in the body as one lays down and reinforces networks of nerve and muscle, linking perception to action. Riding home from the office in Cambridge, across Harvard Bridge and into Boston my body knows to relax, open up peripheral perception, watch for car doors and busses brushing up beside me, where to twitch away from potholes, accelerate over the I90 highway, make eye contact with drivers wanting to turn right and run over me. Embodied learning goes beyond this to even abstract systems. I have a friend who relaxes by unfolding n-dimensional objects in n-1 dimensions (a simple example, unfold a 3D cube into a 2D cross). How is this embodied? It links our physical experience of 2D and 3D space, of unfolding paper and opening boxes to abstract notions of space and transitions. These abstract notions are imagined by a body acting in the world with others.

This cycle is sketched below.

A General Model of Blends

Fauconnier and Turner provide a useful model of blends in their book The Way We Think: Conceptual Blending and the Mind's Hidden Complexities. In their model there are two input spaces, which combine into a blended space and are abstracted into a generic space. Concepts (and by extension any structure - emotional, social and physical as well as conceptual) are mapped between the input spaces. There are several forms of mapping: direct, opposition or difference, various types of transformation, and the recognition that for parts of the blend there is no mapping. Indeed, if every concept can be mapped the blend is likely to bog down, blends (and learning) are selective. The mapping between the two input spaces is projected to the blended space and applied to new content. Emptied of content, the mapping is projected onto a generic space of relations.

An example from The Way We Think (page 271 in my edition). The concepts of traditional marriage and same-sex couple are mapped and key relationships called out. The blend inherits key concepts from both spaces to create a new concept of same-sex marriage. This concept can then become embedded in language, social practices, laws and financial treatment. It also invites us to unfold the original Traditional Marriage blend and think about it more deeply. Where did this blend come from and how does it blend in other concepts such as ownership or kinship?

In my team at work we have been making explicit use of blends to guide design decisions. We consciously search for the blends that we can make that will inform design, and try to unfold the concepts This is hardly new of course. The compass rose blends a circle, space is infinitely divisible and one can go in any direction, with a two-dimensional axes, that privileges north and south, east and west, giving us our bearings. Or more recently, the desktop user interface blends the control of a computer with a desktop.

Some Useful Books on Conceptual Blending

The core text is

The Way We Think: Conceptual Blending and the Mind's Hidden Complexities by Giles Fauconnier and Mark Turner, Basic Books, New York, 2002.

This is based in part on

Philosophy in the Flesh: The Emboddied Mind and its Challenge to Western Thought by George Lakoff and Mark Johnson, Basic Books, New York, 1999.

Where Mathemetics Comes From: How the Emboddied Mind Brings Mathematics Into Being by George Lakoff and Rafael Nunez, Basic Books, New York, 2001.

And on the embodied cognition school of thought, of which my favourite book is

Cognition in the Wild by Edwin Hutchins, MIT Press, Cambridge MA, 1996.

Some books that apply conceptual blending are

A Clearing In The Forest: Law Life and Mind by Steven L. Winter, University of Chicago Press, Chicago, 2003.

Semantic Leaps: Frame Shifting and Conceptual Blending in Meaning Construction by Seana Coulson, Cambridge University Press, Cambridge UK, 2006.

Making Sense of Life: Explaining Biological Development With Models Metaphors and Machines by Evelyn Fox Keller, Harvard University Press, Cambridge MA, 2003.

Conceptualizing Music: Cognitive Structure Theory and Analysis by Lawerence M. Zibikowski, Oxford University Press, Oxford, 2005.

Application of these ideas to design is discussed in

Designing With Blends: Conceptual Foundations of Human-Computer Interaction and Software Engineering by Manuel Imaz and David Benyon, MIT Press, Cambridge MA, 2007.

Learning Styles and Strengths

In the previous post I looked at learning styles generally and my own in particular. And in the post before that the focus was on understanding one's strengths and using them as a way to leverage personal growth. Learning styles were defined as a person's preferred approach to accessing, organizing and applying information, with information understood widely to include things like motor and perceptual skills as well as cognitive skills and organized collections (maps) of information.

In this post I would like to blend my strengths and learning styles together to see how strengths support learning styles and learning style can be leveraged to enhance strengths.

The notion of blending is a crucial one, and one I will come back to many times. It is worth a post of its own. Blending occurs when two different concepts and experiences are brought together to create a third, new level of experience. Blending is the mental (and physical) operation that lies behind metaphor and synthesis, and is the key to how humans evolve new understandings of the world. The key texts on Blending are Philosophy in the Flesh: The Embodied Mind and Its Challenge to Western Thought by George Lakoff and Mark Johnson and The Way We Think: Conceptual Blending and the Mind's Hidden Complexities by Gilles Fauconnier and Mark Turner.

So how do my strengths and my learning styles play together?

My strengths, according to the last time I went through Strengthsfinder, are

• Strategic
• Achievement
• Ideation
• Input
• Learning

My learning styles, from my own self assessment and introspection are

• Abstract
• Historical
• Written
• Modeling
• Social

I actively engage all three modes of information access - visual, verbal, motor - in all five of these learning styles. (Some people think of a visual, verbal or motor bias as a learning styles in themselves, but I have not found this construction to be useful.)

• Strategic thinking requires high-level models and an understanding of how and why things are as they are. This is necessary to effect change. My abstract, historical and modeling learning styles underlie and support my strength in strategic thinking: abstract by helping me to detect the most salient patterns in events; historical by helping me to understand the threads that led things to be as they are, and just as important, to see the ways in which they have been, could have been, and will be different; modeling is closely related to abstraction (in some cases the terms are used interchangeably) and I actively try to construct models of events and processes in order to understand and to influence them ( a habit of though that is reinforced in my current work environment, a major strategic consulting firm, in which the making and breaking of models is part of our day-to-day work).
• Achievement – the drive to excel. I spend a lot of time thinking and learning and working to apply what I am learning to test it and see if it will drive success. Though I will not always admit it, there is an element of competition in my social learning style, I like to know things and to show it, and I also like to help the people I live and work with to excel.
• Ideation – abstract thought and modeling drive new ideas, as does the urge to go back to the source and explore other paths and potentials (historical). Generating and sharing ideas through conversations is key to both learning and achievement (social). Generating, testing, and watching new ideas get selected out is woven through learning and modeling is an act of selecting what parts of the world to notice and then testing and in most cases discarding or modifying the model.
• Input. My approach to learning is input intensive (this is not always a good thing, I sometimes get caught up in the noise and fail to model successfully). I read a great deal, on-line and in book form, scan constantly, and pay close attention to my environment. It is probably attention to the environment that is the most important input to my learning. And it is here that I can best blend the visual, verbal and haptic modes of information organization. My wife has taught me through her design and photography work to pay close attention to the visual and tactile detail of the world. You can see this in her blog Itis. We even try to smell and taste the things we see and live with - the salty wet grit of the air in Boston when it warms after a snowfall (note the date of this post) helps me integrate thoughts on climate change, the physical location of Boston as on but removed from the sea, and the paths I use to cycle around the city. All forms of input, all linked back to my abstract and modeling learning styles. One of my most valuable learning tools is the social tagging site Crowdtrust, where I not only keep track of websites I am interested in, but share them with other people (social) and evolve tag clouds that are part of how I model my thoughts.
• Learning – well that it seems a bit recursive to note that my strength in learning shapes my approach to learning and that my learning styles support my strength learning. But then, recursive structures are something that fascinates me. Google’s application of recursive structures to its technical architecture is something to learn from, and one can think of Chris Argyris’s double loop learning as a form of recursive structure. And double loop learning is at once a model of learning in a social environment, is of historical significance and is something that I try to weave into my own work (I will write more on double loop learning in a later post).