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The key to our flowering at this final stage of our evolutionary cycle lies in the simplicity of being in resonance.

- Jose Argüelles

The image is of Sacred Spaces village at Burning Man 2010.

The Horizon Report, 2010 edition, is out.

Four key trends as key drivers of technology adoptions in higher education, 2010 through 2015

  • The abundance of resources and relationships made easily accessible via the Internet is increasingly challenging educators to revisit their roles in sense-making, coaching, and credentialing.
  • People expect to be able to work, learn, and study whenever and wherever they want to.
  • The technologies we use in education are increasingly cloud-based, and our notions of IT support are decentralized.
  • The work of students is increasingly seen as collaborative by nature, and there is more cross-campus collaboration between departments.

Technologies to watch

The annual Horizon Report describes the continuing work of the New Media Consortium’s Horizon Project, a qualitative research project established in 2002 that identifies and describes emerging technologies likely to have a large impact on teaching, learning, or creative inquiry on college and university campuses within the next five years. The 2010 Horizon Report is the seventh in the series and is produced as part of an ongoing collaboration between the New Media Consortium (NMC) and the EDUCAUSE Learning Initiative (ELI), an EDUCAUSE program.

Survival

There is a certain survival nature in our proclivity toward pictorial information. Being able to accurately assess one’s situation at a glance is an important factor for defending as well as foraging, whether in the forest or the city.

It is interesting that Internet development was a response to a threat to global survival,  Bill Washburn once mentioned to me, I think it was around 1995, when we both worked for Mecklermedia (Jupiter Media), the company that created the original Internet World Trade Shows and Internet World publications.  The net, he said,  provides the impetus and the media and the fertile field for visual language development. It was developed to thrive in a leaderless, anarchic  world. (I hope we’re not going there.)

Shared visual experience

Anyone who travels a bit witnesses a multiplicity of common visual cues. Of course there’s the welcome red and white stripe of a Coke sign, signaling refreshment nearby, only one among the many product brands which have become visually ubiquitous and a shorthand for other kinds of information. Signage systems tending toward the uniform have been implemented in transportation arteries.

Of course, there are the common visual cues we’ve always shared as a result of the experience of living on the same planet: sky, sun, stars, trees, rocks, animals, etc. People around the world share more visual experience than at any previous time. With the proliferation of electronic media, this trend is accelerating.

Evolving through data visualization

Our increasing ability to create — and read — visualizations of large, complex, many-dimensional data sets is a manifestation of how we are evolving the “thinking layer” of the planet, as Tielhard de Chardin calls it, which I am assuming is an evolutionary step forward.

As this abstract, thinking layer of the Internet develops and evolves, individuals gain in freedom of choice. And as they make more and more choices, they become ever more themselves.

About the images, top to bottom:  the shadow of a utility pole against the neighboring apartment building at sunset,  a cell phone credit company sign in rural Jamaica, twisted vines in rural Michigan, a section of a data visualization I made to illustrate the relationships between several dozen databases of customer information at Orbitz Worldwide.

Not so long ago, when content was more of a novelty, words, pictures and numbers in sequence were called “information.” But that’s a misnomer today. Most of the river of symbols that flows through our lives is actually misinformation, because it doesn’t inform. More usually it overwhelms or stupefies or passes by without making much of a dent. At the very least it’s often stuff of incredibly low meaning (my outdoor mailbox) or merely entertaining (most television.)

Information only happens when it informs. Symbolic representations of ideas and analysis, whether marked on paper or HTML-coded, can be called information only when they are meaningful to an audience which is somehow prepared to receive them.

How can you ensure a resonant field for your message? In other words, how can you create that truly rare commodity, information?

It takes two to tango. You have stuff you believe someone may need or want. But the audience must have the appropriate hardware, software and wetware toolkits to process that stuff. You can help by providing them with tools and/or services, or an intellectual context that makes content meaningful enough to be called “information.”

As Jose Arguelles has said, “The essence of information, then, is not its content but its resonance.”

Beneath a change of age lies a change of thought. – Pierre Teilhard de Chardin

Donald R. Woods, professor emeritus of chemical engineering at McMaster University, has done quite a lot of research into what different MBTI types consider to be good exam questions.  Don is perhaps most widely known as a pioneer of McMaster’s distinctive learning strategies: inquiry and problem-based learning. I ran across a reference to his article, Models for Learning and How They’re Connected–Relating Bloom, Jung, and Perry, which was published in the Journal of College Science Teaching, v22, n4 p250-54, Feb. 1993.  After spending half an hour hunting around on ERIC and in various university libraries, I could not find a source, so I dug up his email address on the internet and just contacted him directly.

I’m working with the learning aspects of our travel web site. I was interested to know how to correlate MBTI types to the levels on Bloom’s Taxonomy . I had the idea of associating the categories I came up with to differences in the types of questions people might have when they come to the web site.

Don promptly responded with helpful information.

Sensing/Thinking (ST), which is 30% of the US population, includes ISTP, ESTP, ESTJ, and ISTJ. They ask questions on the Knowledge/Remember level of Bloom’s taxonomy. Questions like, What does it cost to check a bag? What is an e-ticket?

Intuiting/thinking (NT), which is 10.4% of the US population, includes ENTJ, INTJ, ENTP, and INTP. They want to Understand (Bloom’s second level), and appreciate questions that ask them to compare and contrast.

Intuiting/Feeling (NF), which is 16.3% of the US population, prefer Evaluation questions (what if?)

Most interesting to me is the Sensing/Feeling group, which comprises 43.4% of the US population. They want to know, “How would I feel if…?” and this is not usually the type of question that is addressed in a scholastic exam or on a travel web site:

  • How would I feel if I choose this trip A compared with trip B?
  • Would I be at ease in this hotel room?
  • Would I be happy if I choose this car?
  • How comfortable would I feel if I choose this airline seat?

However, the use of sensory information such as rich media, video, sound, images, diagrams and visualizations of data speaks powerfully to this type of sensing/feeling person, which, if you give credence to this type of analysis, comprises a huge chunk of any potential audience of learners.

Waves made by sound. Fox tracks. Events in the natural world create patterns, specific and literal. The designer works to distill meaning from events in the life of the mind. A trail of symbols and systems forms in the wake of her work. Examine first the imprint of the fox’s running foot, the coarse displacement of the snow. Then the eye encounters the structure of the individual flakes of snow, the blue shadows, the scintillating light. Design evokes the radiance of meanings in which it participates.

What is the meaning of color? Of a point, a line, or a plane? Of a vortex, a fractal, any sort of radial pattern? With no evidence other than the personal and anecdotal, I believe the human race is increasingly thinking in visual ways, and that persons of the highest visual evolution are increasingly able to recognize and describe common design patterns. We’ve seen this happen in many disciplines over the past few decades: art, architecture, urban planning, and programming being a few. Of course no one can argue that we daily absorb and act on great richness of visual information.

As human beings, we are naturally language makers. It makes sense that as we are beginning to communicate in a more global way, and that we are developing a language to do so. This language consists of universals, whether arbitrary or natural, of structure and form, which when completed will provide a vehicle for communicating and manipulating meaning. That this language is primarily visual also makes sense, for it derives from visual experience.

The syntax of visual language, when worked out, will be as deceptively simple as the rules which govern the flight of birds, or the workings of our dopamine cells which, it is theorized, increase or decrease their firing rates in response to errors in predictions about the world around us, predictions based on metaphorical information input to the brain: sensory input and memories of sensory states.

Yet because the radial reciprocity of the code is so complex, we haven’t yet drilled down to the matrix of energy states which underly visual phenomenon. Art and psychology, physics and metaphysics all have their theories; what we’re lacking is a Unified Field Theory of graphical/textual communication.

  • What makes a kid play with the same toy over and over again?

Or, here’s another way to phrase it:

  • What is the structure of interactions between agents which result in ongoing engagement of the learners, the growing of shared meanings and playing with shared cognitive artifacts?

Interactions can be defined as the micro-events that occur between autonomous agents in processes that eventually result in a healthy agents and a healthy network. On the most basic level of life, autonomous organisms solve problems of encounters with the environment through mechanisms such as a selectively permeable membrane, a group of energy currencies such as those used for transport processes across a membrane, a set of catalysts responsible for modulating the rates at which reactions to the environment take place and mechanisms for stabilizing metabolism. More advanced adaptive interactions include motility, multicellular organization, and sensorimotor systems, leading to the development of the mind as a neurosomatic activity which establishes a sense of self in the environment.

Motility is the baseline for the appearance of cognition; in collaborative learning we should expect to see that a knowledge flow which is open and free is the baseline for the appearance of  Surowiecki’s “wisdom of crowds” phenomenon.  Online interactions are like non-terminating data processing algorithms, in that they are defined lists of instructions for completing tasks, but the length of the process cannot be determined in advance. If they are well designed, they extend our adaptive interactions in ways that allow us to move,  use our senses to touch one another, and organize ourselves into complex systems.

It’s that kind of complex organization that provides a venue for self-realization. As our systems become more complex, they give us the opportunity for increasing individuation.

As de Chardin has said, “union differentiates.”

A few weeks ago I wrote Part 1 and Part 2 of this series, outlining some of my thoughts on the topic, What is Learning?

Here is a wrap-up of  people who’ve influenced the development of my learning theory of Relationalism.

  • Lev Vygotsky described how people use a semiotic process (language and sign systems) to mediate (external) social relationships into (internal) psychological functions. He also had quite a bit to say about the role of play in learning.
  • Benjamin Lee Whorf described the relationship between language and the rest of the culture of the society which uses the language, in his volume, Language, thought and reality
  • James Zull, professor of biology and biochemistry at Case Western Reserve, in his book, The Art of Changing the Brain describes how knowledge is situated in growing, evolving network configurations in the brain. Those neural configurations are activated in the future when presented with the same types of experiences, and apparently, they reconfigure and grow some more.
  • Ted Panitz, for example, suggests that learners create knowledge as they collaboratively and cooperatively work to understand their experiences in nature, in society and culture, growing their own meanings.
  • In his theory of connectivismGeorge Siemens situates learning in the creation of network connections. He says, “Connectivism is the integration of principles explored by chaos, network, and complexity and self-organization theories.”
  • Howard Gardner describes a cognitive architecture of multiple intelligences.
  • Cognition itself is now being seen by some as distributed, as described, for example, in James Surowiecki’s book, The Wisdom of the Crowd. These multiple intelligences belong not just to the person, but to the person’s community.
  • Paivi Hakkinen and Sanna Jarvela have found that social negotiation of meaning in an online forum is dependent on the presence of multiple articulated viewpoints, and may be tied in part to the design of the learning activity
  • Peter Checkland‘s soft systems inquiry focuses strongly on agents and agency.
  • Terry Anderson has described social learning in terms of user interfaces and technologies for distance learning and online learning. These technologies live on the Internet, World Wide Web and private networks, and are accessed through personal computers and mobile devices.
  • Jon Dron has described how increasingly complex online user interfaces provide a venue in which individuals can socially construct knowledge, from the bottom up.  If the software is well designed, the interactions are organic, self-organizing, evolutionary and stigmergic.  Learning experience designers can embed in the user interface the kind of control over the learning trajectory that a teacher role would normally take. Learners can choose whether to control their learning or to delegate that control to the group. In principle, then, social learning appears to offer the best of both worlds, assisting dependent learners through the provision of structure yet enabling autonomy at any point.

Dale Chihuly sculpture, Milwaukee Art Museum

My own theory of learning is called relationalism.

Relationalism draws a picture of learning as simultaneously personal and social.  People grow neural configurations, and groups evolve their networks, when they attend to and interact with human and non-human agents,  in complex socio-cultural and environmental contexts.

This is a bit like the constructivistsTed Panitz, for example, suggests that learners create knowledge as they collaboratively and cooperatively work to understand their experiences in nature, in society and culture, growing their own meanings.

Relationalism is similar to the learning theory of connectivism, which situates learning in the creation of network connections.  I am not even going to try to summarize the tenets of connectivism here, except to retiterate George Siemens‘ statement that “Connectivism is the integration of principles explored by chaos, network, and complexity and self-organization theories.”

Relationalism extends connectivism by:

  • being more rigorous in the definition of connections, through the development of a taxonomy of learning interactions between agents in a learning network
  • emphasizing the radical responsibility of learners for their own learning
  • understanding that learners are part of larger groups which exhibit different levels of engagement between agents. These larger groups are variously described as communities of inquiry, learning communities , community of learners, classroom community, communities of practice, group, network and collective.
  • understanding that a dependency for learning is the creation of a safe container, to create a trustworthy environment, where engaged people feel free to generate shared narrative, and play with new ideas and ways of being.
  • understanding that nothing but sheer love drives a kid to interact with the same toy over and over again. This behavior was well described by C. J. Jung, who said, “The creation of something new is not accomplished by the intellect but by the play instinct acting from inner necessity. The creative mind plays with the objects it loves.”

What learning is NOT:

Learning is not a process of acquiring facts.  However, I used to think differently. Back in Hillsboro High School, when I used to “cram” for a test, I assumed that I could stuff a lot of facts into my head in a hurry, the night ahead of time. Then those facts would be mine and I could haul them out at appropriate times, for example, on the test the next day. This is the cognitive approach to learning, which assumes that the purpose of learning is the individual’s acquisition of “knowledge”, which is assumed to be an entity or static state. One might call it a the triumph of industrialism: the materialistic world view which reduces knowledge to a possession. Cognitivists view learning as a process of inputs, much as occurs in computer information processing, with knowledge stored in the database of short term memory, coded in symbolic mental models for long-term recall.

Neural network model, Museum of Science, Boston

What learning IS:

Learning is the structural evolution of the brain that occurs as we engage in the world

OK, so learning is NOT the process of acquiring anything. So what is it?

Much of  my thinking about how people learn is founded on research on how learning comes from the structure and biology of the brain. These studies published in the past few decades in fields such as cognitive neuroscience, neurobiology, and neurophysiology, describe how memory traces are formed in the brain as a result of concrete experience, reflective observation, active testing and forming of abstract hypotheses.

According to this research, learning is a physiological process of growth of structures in the learner’s mind–growing new neural configurations as a response to being presented with new experiences.

The manifestation, as I understand it, of this physiological growth, is the evolution of  structures of language, thought and reality (oooh, that’s the title of Benjamin Lee Whorf‘s fabulous book. Check it out!)

James Zull, professor of biology and biochemistry at Case Western Reserve, talks about this in his book, The Art of Changing the Brain.    Knowledge is situated in the growing, evolving network configurations. Those neural configurations are activated in the future when presented with the same types of experiences, and apparently, they reconfigure and grow some more.

In the external world, outside the brain and out in the landscape of Earth, group learning is growing connections between networks. Learning occurs as learners engage in the experiences of practice and reflection, and as teachers, in whatever form, engage them in experiences of modeling and demonstrating.

As my 16-year-old son Zachary once remarked, “You can’t not learn when you’re doing something.”

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