Sunday, October 19, 2008

CCK08 - week 6 – Complexity, Chaos and Randomness

Developing Online From Simplicity toward Complexity: Going with the Flow of Non-Linear Learning
Video Lecture: Complexity Science
Complexity and Information Overload in Society .pdf
Complexity, Chaos, and Emergence (George Siemens)

Other useful resources for this week:

Notes from readings:
Reflection halfway through the course – George Siemens
All learning begins with a connection – what are the attributes of those connections?

Developing Online From Simplicity toward Complexity: Going with the Flow of Non-Linear LearningRenata Phelps
‘net generation’ - characterised as chaotic, constructivist, integrated and multi-faceted, and where ‘play’ is central

…two learning systems and cultures, that of school and of the Web, are fundamentally different; one has a basis in control and structure, and the other is seemingly unstructured and chaotic.

Complexity theory is concerned with open, non-linear systems and is essentially a formal attempt to question how coherent and purposive wholes emerge from the interactions of simple and sometimes non-purposive components (Lissack, 1999). At its most humble, it attempts to explain the ‘big consequences of little things’.

‘Curriculum becomes a process of development rather than a body of knowledge to be covered or learned, ends become beacons guiding this process, and the course itself transforms the indeterminate into the determinate’ (Doll, 1989a, p.250)

… many young people, provided with access to the Web, adopt learning approaches consistent with complexity theory. Their learning is ‘naturally’ non-linear.

… complexity’s recognition that it is impossible to break down learning and teaching into determinist and predictable simple elements of knowledge.

Integral to the process of fostering self-directed and life-long learning was an emphasis on self-directed goal setting, but also on acknowledging and embracing ‘emergent’ learning – ‘you don’t always know what you don’t know’!

… learning cannot and should not be goal-directed all the time. ‘Sometimes one should be satisfied with a global, general learning goal and let the learning environment guide the discoveries’ (p.292). …. not only guide but prompt such learning ‘discoveries’.

Non-linear learning was perceived to be more ‘authentic’ than linear learning and more consistent with life-long learning.

While rapid and easy progress through linear and defined content may be reassuring to the learner, little learning may actually be taking place.

… simplification of complex subject matter is a ‘conspiracy of convenience’…. providing realistic levels of complexity in the learning environment can actually make learning easier … Rather than simplifying the environment, the goal of educators should be to aid the learner to function in rich learning environments…. flexible, open, disruptive, uncertain and unpredictable and should accept tension, anxiety and problem creating as the norm.

four-module structure: Thinking, Using, Applying and Creating…. Find ‘windows’ Facts, Skills, Activities, Use in Schools and Reflection…. encapsulated an approach of ‘play’ and exploration.

… some students required or preferred foundational understandings (facts), or foundational skills, while others were comfortable with experiential learning and needed to be challenged to set and achieve ambitious learning goals, and to ‘test out’ their knowledge (activities).

They had more choice about what they learnt, but more importantly, how they learnt it. Students would be encouraged to jump from activities to facts or skills as required. Students were encouraged to identify their own goals; goals that were challenging for them personally. All students were required to demonstrate progress, no matter what their initial level of skill and knowledge. While frameworks were embedded in the materials to support them to set these goals, they were prompted to select content and activities which were most appropriate in achieving their goals and to document, through reflection, the resultant, personally significant learning.

… the Web is … a big tangled spider’s web of information. Bits of it lead to other bits and there is no ‘start’ and ‘finish’.

think about how we learn in contexts other than schools and universities.

Parent analogy:
- no single course you can do on ‘how to become a good parent’
- They don’t know everything there is to know, but when issues or challenges arise they seek out information and advice, and adopt strategies that they feel are appropriate.
- they reflect on whether their strategies are working or not and will seek other information, or adopt other strategies if they don’t.
- consult a variety of resources
- experiment with different approaches

learning in ‘real life’ isn’t generally very ordered or structured. Learning is usually motivated by an activity which needs to be performed or a problem which has been encountered. Individuals seek and select information from all kinds of sources to meet their own personal needs and interests and there is always further learning which they can continue to pursue as their activities and practice develop and they reflect on their new goals.

… ‘cognitive playfulness’ (Martocchio, 1992; Webster, 1995) and exploratory learning … Gare (2000), for instance, describes play as the ‘archetypal chaotic and unpredictable behaviour from which new order emerges’.

Video Lecture: Complexity Science – Seth Bullock
A systems is a set of individual components that are linked by relationships of some kind to form a whole.

Complexity and Information Overload in Society .pdf – Francis Heylighen
… information overload is made worse by “data smog”, the proliferation of low quality information because of easy publication.
… the basic thrust of progress cannot be stopped, this means that we will have to evolve suprahuman systems to complement our limited capacities for processing information and understanding complex systems. These systems cannot be merely technological (the famed superintelligent computers or robots), but must encompass humans as essential components.

… law of Moore, according to which the speed of microprocessors doubles every 18 month, while their price halves.

Ephemeralization, the ongoing increase in efficiency or productivity of all processes involving matter, energy and information, is the most basic manifestation of technological and organizational advance.

… ephemeralization smoothens or lubricates the machinery of society. Movements of matter and information run more freely, with very little loss or resistance. But this applies to unwanted movements too. It has become much easier to distribute weapons, bombs, drugs or poisonous materials, or for criminals or terrorists to coordinate their activities across borders.

1987 "Black Wednesday" collapse of stock prices, which was due not so much to the state of the economy, but to the new phenomenon of computer trading. Specialised computer programs would monitor the prices of different stocks. If prices fell below a certain value, the computer was programmed to offer the shares for sale, before they would lose even more value. But the more shares were on sale, the lower their prices became, triggering yet more selling.

Ephemeralization not only lengthens causal sequences, it increases the number of effects that a cause produces in parallel. An event has generally more than one effect simultaneously. – multiply effect - … greater difficulty to predict, and therefore control, … The reduction of friction in causal networks, however, makes prediction ever more difficult .. chaotic

evolutionary dynamic underlying ephemeralization not only increases the complexity of interactions, but also the complexity of the overall system because it promotes the differentiation and integration of subsystems … any phenomenon, system or process in society becomes more difficult to analyze, model, predict and control.

To compensate for the loss of predictability, this means that they will have to gather more extensive information about all the different factors and interactions that may directly or indirectly affect their situation.

… ephemeralization has made the collection and processing of information much easier. However … fundamental bottleneck in predictability is: the human decision-maker

… information was a scarce resource … ephemeralization has made the retrieval, production and distribution of information infinitely easier … practically eliminating the cost of publication. This has reduced the natural selection processes which would otherwise have kept all but the most important information from being transmitted. … overabundance of low quality information has been called data smog by Shenk (1997). … “spam”

Causal effect of world trade centre on us getting our passports

… ephemeralization forces us to pay attention to ever more data.

The problem is that people have clear limits in the amount of information they can process. To use Simon’s (1972; Simon et al., 1992) well-known phrase, they have bounded rationality. … psychologist Miller (1957) has shown that people can only keep some seven items at once in their working memory. … Long-term memory is much more powerful and can store millions of concepts, although it is short-term memory that we use to think, decide, and solve problems in real-time.

… people will be confronted with more information than they effectively can process: this situation we may call information overload (Berghel, 1997; Kirsh, 2000).

psychologist David Lewis, who analysed these findings, proposed the term "Information Fatigue Syndrome" to describe the resulting symptoms. They include anxiety, poor decision-making, difficulties in memorizing and remembering, reduced attention span, reduced work satisfaction and strained relations with collaborators (Waddington, 1996; Shenk, 1997; Wurman, 1990).

If we consider individuals as goal-seeking, cybernetic systems (cf. Heylighen, 2002), then processing incoming information (perception) is only one half of the story. … Ephemeralization has boosted not only the availability of information but our capacity for action. We have ever more numerous and more powerful tools, support systems, services and products at our disposal. … We may call this the problem of opportunity overload.

Because of ephemeralization, the potential power of actions, whether to the good or to the bad, has tremendously increased.

Perez (1983), inertia: individuals and organizations need years, if not decades, to adapt to a new technology and to learn to use it productively … The more revolutionary the technology, the longer this learning or adaptation process will take…

Ephemeralization of information has allowed more people to be educated more easily and cheaply leading to the understanding for the need of ‘life long learning’ … education will no longer be finished after college, but become a permanent process, as employees need constant training to keep up-to-date with the developments in their field and in society at large.

More important even than the quantity of education is its quality. … This requires education where the focus is not on static rules or facts, but on methods to autonomously analyse problems, find relevant information, synthesize the results, and thus develop new knowledge.

… the human brain is an organ with a limited capacity for storing and processing information.

… g-factor (for “general” intelligence), that appears primarily biological (Jensen, 1998). The g-factor can perhaps best be understood as a measure of the efficiency of information processing in the brain. … there is also a strong influence from the environment beyond the effect of education. … explain this secular rise in intelligence (Neisser, 1998): richer nutrition, better health, more cognitive stimulation by a more information rich environment, more parental attention invested in a smaller number of children, etc.

Distinguishing and filtering out unreliable or irrelevant information is one part of what Shenk (1997) calls information hygiene. … People should not only learn how to recognize information parasites and other forms of low-content messages, they should themselves actively refrain from adding to this “data smog”. Ie “netiquette”

… attention economy… Where the cost for the sender is minimal, the cost for the receivers, while individually almost negligible, is collectively huge. … The cost has shifted basically from sender to receiver.

While our conscious processing in short-term memory is extremely limited, it is clear that the more diffuse, automatic, subsconscious processes relying on long-term memory (e.g. recognizing faces or producing speech) have a capacity that is still beyond the one of present-day computers. … artificial intelligence (AI) … not so much for independently intelligent programs, but for systems that support or “augment” human intelligence (IA, that is, Intelligence Amplification, rather than AI). … various relatively simple tasks on behalf of its user, such as keeping track of contacts and appointments, … Creating such an environment is the main drive behind the vision of the semantic web, (Berners-Lee et al., 2001)

1) individual human minds; 2) economical or social rules for the allocation of attention; 3) computer systems to support human decision-making.

collective intelligence (Lévy, 1997). … as ant nests, bee hives or termite colonies (Bonabeau et al., 1999), encompassing intelligent system is the global brain

collaborative filtering (Shardanand & Maes, 1995): a person who has already read a message may score how relevant or interesting the message is for him or her.

.. the web learns new links between documents in the same way that the brain learns to create associations between phenomena experienced within a short time interval.

.. human intelligence, computer intelligence, and coordination mechanisms

Complexity, Chaos, and Emergence (George Siemens)
Chaos theory - Strogatz defines it as unpredictability that occurs in systems that obey predictable laws, or, more succinctly, “deterministic unpredictability”. … Pure mathematics, advanced physics, and related sciences are its birthplace. … two critical elements: 1) the concept of sensitivity of initial conditions, and 2) recognizing that learning similarly consists of unpredictability that occurs within certain structures of form (deterministic unpredictability).

Complexity theory - a weather system is an example of complexity. Numerous interacting elements produce varying outcomes. Such as in learning

Emergence is an attribute exhibited by complex systems. … our learning is the emergent phenomena of our own interactions with others and how we have engaged with and connected different concepts.

Learning is simply too complex, too multifaceted, too replete with multiple off-ramps, to be confined or reduced to a mechanistic model.

No comments: