CCK08 – Week 8. Power: Networks vs. networks.

November 3, 2008

 

Networks as organization pattern in Biology and Society.

Biological systems exchange molecules in networks of chemical reactions, social systems exchange information and ideas in networks of communications. Biological networks operate in the realm of matter. Social networks operate in the realm of meaning.

The difference between a living organism and a dead organism lies in metabolism, the ceaseless flow of energy and matter through a network of chemical reactions, which enables a living organism to continually generate, repair and perpetuate itself. The two basic aspects of metabolism are this continuous flow of energy and matter and the network of chemical reactions that process the food and form the biochemical basis of all biological structures, functions and behavior. The network is a pattern that is common to all life, the very basic patterns of organization in all living systems. Wherever we see life, we see networks.

They are functional networks, networks of relationships between various processes. Their key characteristic is that they are self-generating. Living networks are self-generating. All living organisms have a physical boundary that discriminates between the system – the self and its environment. The existence of membranes is therefore an essential condition for cellular life. The boundaries of living networks, then, are not boundaries of separation but boundaries of identity.

Network generates its own boundary of exceptions, of confidentiality and loyalty, which is continually maintained and renegotiated by the network of communications.

Social networks are first and foremost networks of communications involving symbolic language, cultural constraints, relationships of power. Each communication creates thoughts and meaning, which give rise to further communications, and thus the entire network generates itself. Living social systems are self-generating networks of communications.

Social systems produce non-material structures.  Ideas, values, beliefs and other forms of knowledge generated by social systems constitute structures of meaning, which we may call semantic structures. The culture’s semantic structures are documented. These material structures – texts, works of art, technologies and material goods – are created for a purpose. They are embodiments of the shared meaning generated by the society’s networks of communications.

Biological and social systems both generate their own boundaries. A social network, a non material, cultural boundary, which imposes constraints on the behavior of its members. Natural sciences deal with material structures while social sciences deal with social structures, essentially rules of behavior. A sustainable community is designed not to interfere with nature’s inherent ability to sustain life. The principles of organization that nature has evolved to sustain the web of life.

 

The Network Society

Networking has emerged as a new form of organization of human activity. The term  Network Society describes this new social structure. Internet is becoming a critical infrastructure of everyday life, crucially enabling individuals to network in new ways that reconfigure and enhance their communicative power- as a type of Fifth Estate. The communicative power of networked individuals is key. Individuals and institutional, networks of networks. People able to reconfigure their access to information, people and other resources.

Networks appear to be the organizing form of life, including social life. Networks reconfigure themselves in real time, on a global-local scale, and permeate all domains of social life. We live in a network society, not in an information society or a knowledge society. Technological paradigm is the dominant medium for social organization. The proper identification of our society, out of ruling if it is the Fourth of Fifth Estate, is in terms of its specific social structure: networks powered by microelectronics and software-base information and communications technologies.

Internet can play in reconfiguring access to people, information, services and resources. It can change the way we do things. Internet can alter the outcomes of these activities. These networks can blur the boundaries of households, organizations, institutions and nations. They enable individuals –not only institutions- to create local and global networks.

Autonomy, diversity, openness and interactivity are not properties of networks generically, but the properties of good networks. Networks in which these values are promoted are robust, stable and reliable. They are good knowledge engines because these principles align with connective knowledge. The web is an engineered space that creates a distributed information space.

Internet has the potential to reshape the communicative power of individuals and groups in numerous ways. Internet is as creating a space of flows, in contrast to a space of places. This new space of flows connects with people and places.  This space of flows enables a multitude of actors to reconfigure access to information, people, services and technologies. Through the space of flows, the networks of networks, the Internet is enabling the development of a Fifth Estate that is enhancing the accountability of many sectors across all societies.  

Networks constitute the newest major social organizational form, after tribes, hierarchies and markets.
Commerce was organized around markets. Technology is organized around networks. But networks have their structure and dynamic that imposes laws whatever is the realm where it is present. We recognize in complex linked network an unbalanced distribution that makes its nodes different one to another. That is the case of the 80-20 law formulated by Vilfredo Pareto, the existence of hubs and the free scales networks configured following the preferential attachment dynamic as described by Barabasi. This emerges as properties of a super organism that has its consequences, as described by Manuel Castells :

1.       Network society expands on a global scale.

2.       Networked organizations out-compete all other forms of organization, particularly the vertical, rigid, command-and-control bureaucracies.

3.       Networking of political institutions is the de facto response to the management crisis suffered by nation stated in a supranational world.

4.       Civil society is reconstructed at the local and global level through networks of activists.

5.       Sociability is transformed in the new historical context, with networked individualism emerging as the synthesis between the affirmation of an individual-centered culture, and need and desire for sharing and co-experiencing.

6.       Whole range of social practices, both global and local, communicates in the media space, with its infinite capacity of integrate and exclude.

7.       In the network society, power continues to be the fundamental structuring force of its shape and direction.

Power is located in the networks that structure society and is exercised by specific configurations of these networks that express dominant interests and values. Networks matter because they are the underlying structure of our lives. To counter networks of power and their connections, alternative networks need to be introduced: networks that disrupt certain connections and establish new ones. Network vs. networks.

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CCK08 – Week 7 – Instructional desing. Which is the design of our self teaching strategy?

October 26, 2008

Learning begins with connections. We find connections in the learning process at the neural, conceptual and external/social level. So we are able to say that learning is the ability to form networks.

Through the instructional design we may work, for instance, with the sequences of content, the interactions and the space or ecology. For the design we should have in mind the context: learning needs and situation of learners

It is helpful, in this design stage to use the metaphors of chaos and complexity. Chaos metaphor helps us to be able to find in it some degree of hidden order and to be able to recognize the sensitivity to initial conditions. Complexity helps us to understand the multiple interactions of elements of a system that results in particular incomes. In brief, we should be able to design for adaptability, that is finding ways and patterns for sense making and achieve particular outcome through distributed approaches.

We may use a design model taking into account content, context and connections (concepts and others)

 

Tension in between traditional education practice and connectivsm vision

The following chart summarizes the tension in between the traditional education paradigm versus, what we may call a connectivsm ecology that takes profit of the web 2.0 social networking tools.

Traditional Education

Connectivism ecology

Need to reflect

Build cumulative on existing knowledge

Develop individual understanding over time

Speed and immediacy

Ability to access a vast amount of information

Individual testing

Recognition of individual contribution

User participation, mash ups, remixing and co-construction

Plagiarism?

Combining sources, cut & paste, editing on other peoples’ work

 

Respository of ideas and resources

Cross referencing, difficulty of identifying source of ideas

Individual to be an expert on the field

No one is an expert but part of a social network

Predicating teacher as privileged expert

User generated content, mass participation, co- construction of ideas

Subject fields static and unchanging

Subject field fragmented and diverse

Hierarchical administrative and assessment processes

Participation and negotiation

Institutional tools

Personalized tools

 

Whenever assessing tools in the education practice we may map themusing the following dimensions:

1.       From individual to social learning

2.       Learning through information to learning through experience

3.       Learning passively to learning actively

Engeström states on social networks:

1.       The fallacy is to think that social networks are just made up of people. They are not: social networks consist of people who are connected by a shared object.

2.       In education the primary social object is content.

3.       Education value is not in the content itself but the social interaction, which occurs around the content.

So to design in educations using social networks we must follow these five principles:

1.       Clearly define the social object your service is built around

2.       Define the verbs that users perform on the objects, so that is it clear what the site is for.

3.       Make the objects shareable

4.       Turn invitations into gifts

5.       Charge the publishers, not the spectators

When we finish our formal education, we continue to learn defining self teaching strategies. What is the design behind this strategy? The answer is connectivism. When the curricula, administrative and assessment process is gone, there it is the connections we make at the conceptual and social level. Is here where we need to find a natural way of practicing connectivism that would help us to bring to formal education the successful everyday connective learning experience.

CCK08 – Week 6: Living and learning with complexity

October 19, 2008

In previous blogs we have affirmed that connectivsm states that knowledge is in the connections and in the networks (neural, conceptual and external).  Connections together with nodes are the fundamental particles of networks. Networks have structure and dynamic. For change we require structures that also change. And networks are these kinds of structures.

Learning is complex to be confined or reduced to a mechanistic model. Instead, we use networks and ecologies as a model for learning, knowledge and managing the complexity of the environment where learning takes place. Ecologies and networks are reflective of chaos and complexity theories main tenets and provide a suitable replacement for the current classroom and hierarchical model of education. This complex environment we find in education explains the emergency of learners understanding, group formation, advancement of a discipline, etc.

 

Science of complexity

Cynefin framework is a sense making device to make sense of the complexities based in three ontological states: order, complexity and chaos. Cynefin is a Welsh word for place for multiple affiliations. All human interactions are strongly influenced and frequently determined by patterns of our multiple experiences both personal and collective expressed in stories. And patterns are what we use to order the world and make sense of things in complex situations.

Cynefin framework is not about “objective” reality but about perception and understanding. It helps us to think about the ways in which different people might be perceiving the same situation. And this understanding can be used to one’s advantage. Even dough we may define the ordered and un-ordered domains, things are both ordered and un-ordered at once, because both intertwine and interact. But a fifth domain still exists, disorder.

 

Un-ordered domain

 

Weak central connection

Ordered domain

 

Strong central connection

 

Strong connection between components

 

 

Complex relationships

 

Knowable causes and effects

 

 

Weak connections between components

 

 

Chaos

 

 

Known causes and effects

Cynefin Framework

In the realm of complexity chaos, unpredictability that occurs in systems that obey predictable laws as defined by Strogratz  may be seen as “deterministic unpredictability” where a type of order is discovered.

Complexity theory is concerned with open, non-linear systems. Non-linear means ecologically embedded, non-additive, inseparable, heterogeneous, interactive, asynchronous, lagged or delayed. In complexity the autonomy of agents adds an additional level of complexity. In learning we have individual parts, dynamic interaction, criticality of feedback in influencing adaptation and openness

Complexity provides a perspective on learning based on non-linearity of thought and variation as a source and outcome of thinking (Bloom). Networks and the web are non linear environment. So we should benefit of complexity and non-linearity in online learning or learning in general. There is no escape. The system behavior brings stability, emergence and adaptation. Structure is linked with behavior.

Emergence is the outcome (understanding) that arises from different agents interacting and producing unanticipated outcomes. Emergence may manifest through collective self-organization, un-programmed functionality, interactive complexity or/and incompressible unfolding

For an autonomously developing system to acquire knowledge about a realistically complex environment, it must be able to interact extensively with that environment. Such interactions require very sophisticated sensors, which bring information into the system so that the system can test its understanding of the outside world.

We may be able to develop a Global Brain, an intelligent system that links all cognitive and physical resources in the most efficient way possible. Let’s leave for another discussion what efficiency may imply in this context.

CCK08 – Week 5 – Groups and Networks

October 10, 2008
Groups and networks

Groups and networks

This concept map sumarizes the discussions on groups and networks. It highlights what groups and networks are, require and emphazise. I preferred of talking on groups and networks instead of groups vs. networks, because it will be very unprobable to find excluding environements where groups exists without networks and viceversa.

CCK08 – First 4 weeks paper

October 7, 2008

A new theory of knowledge and learning emerges out of the construction and navigation of knowledge networks: Connectivsm.  Neural, conceptual (Burke) and external, networks manifest its connecting character allowing the flow of distributed knowledge. As an amazing fractal structure, we find networks at the three levels of learning.  Based on networks structure in a complex changing environment and distributed congnition, Connectivism is being leveraged by technology.

If  human mind can know and is basically a network, then any network can come to know? Seems that the network organization with its structure and dynamic is what makes possible to know. The brain responds to environmental demands, generating, creating, strengthening, weakening, losing and eliminating neural connections. So mind is a construct which is distributed from the brain to the environment (Kerr) and plasticity is its intrinsic core.

 Any interaction in a network, makes the connections to change, resulting in storage of information. Learning results of integrating all information perceived and processed that leave a physical trace of its passage, generating new network organization patterns.

 But how language, which is another specifically human cognitive function has also a role in developing knowledge? Connectivism must develop a answer to this question.

The discovery of patterns in the Universe shows great regularities.  Inner structure of Internet, information linkage in the web, people interaction in social networks, all show a surprising bridge in between local properties or individual actions and the resulting collective interactions. The structure and dynamic of the system is determined by the collective interactions of all of its constitutive parts, and at the same time, it’s individual behavior are framed by the topology and dynamic that emerges.

Network Learning found in communications technologies  and software developments, key drivers for its development.

We begin finding hidden laws that govern the formation, growth, evolution of these networks. In the last years, psychologists, biologists, mathematicians, physics and other scientist have shared their observations and built a new epistemological space that we could call the New Science of Networks. A new theoretical perspective that provides tools to physicists to battle against epidemics, engineering to prevent fails in cascades in large interconnected systems like the power grid or visionary economic analysts that anticipate financial meltdowns.

Kant argued that time and space are the natural and irreducible categories of mind, the way how we perceive reality. Reality manifests itself as complex interconnected networks. Stability, synchronicity, self similarity, threshold, cascades, epidemics, emergency, resiliency, keystones, phases, connectors, evolution, clustering are some of the new way of seeing and thinking the world.  A simpler world that connects very diverse phenomenon, entities and realities.  A world that needs to learn on networked thinking.

Social webs begun its development during the new century even though the first weblog appeared in 1995 and a year later blogs allowed readers to comment. The exchange of files in between PCs was facilitated by Kaza, Gnutella, Bit Torrent. Later Wikipedia, Technoarti, Flickr, Fotolog, Delicious, LinkedIn, My Space and FaceBook allowed social networking, bookmarking, blogging and dating including virtual reality environments like SecondLife. User contributed content was another important component like in YouTube were audience begun producing content. All this new ambient was named web2.0 and Kevin Kelly affirmed that “we are the web”.  The wealth of the networks now is based on commons peer production and profits do not come from comments but from attention and banner clicks. The time spent became the central value of the Internet.

So, Network Learning backed by technology, merging fields and new theoretical views of learning, knowledge and cognition helped in paving a new epistemology space together with the massive participation in the web2.0 . May connectivism play this role?   

The experience

Learning on learning with 2200 class mates on MOOC through networks make people, ideas and  concepts being connected. The same platforms and tools to be used in this course are the one to be observed as a practice and collective experience on Connectivism. Wikis, Moodle, blogs, mails, groups, alerts, Twitter, Wordl, PageFlakes, e-lluminate, UStream, Facebook, Second Life and Flickr are just a selection of tools that me be used. Texts, graphs, cloud tags, audios and videos are enriched by same students with their comments, blogs and references.

Connectivism may be developed as new theory of learning.  To do this, it must answer and provide a better understanding of language and its role in learning, knowledge and cognition. But probably, in its effort to become a new theory and in the middle of epistemological discussions, Connectivism may be losing its potential on the practical field of education and human organization.

Week 4 – History of Network Learning

October 7, 2008

A history of Network Learning should have in consideration the history of Social Web, because in its first stage, infrastructure and applications development are key drivers for its development.

So briefly, we should take into account the technology development in the network infrastructure that ends with the coming of Internet while at the same time consider the invention of the personal computer. The 60’s were very important in the conceptualization of packet switching (Kleinrock), distributed networs (Baran), TCP/IP (Cerf & Kahn), ARPANET and ALOHANET.

Late in the 80’s and the 90’s hypertext and browsers were developed and Java, a cross platform software language made applications independent from software. The California ideology, which meant the freedom of hippie artisanship merged into the market economy, resulted in the acceptance of the commercial Internet while at the same time the web without fees. Finally MS, leader of the operative systems that governs the PCs decided to give away its Internet Explorer browser.

Social webs begun its development during the new century even though the first weblog appeared in 1995 and a year later blogs allowed readers to comment. The exchange of files in between PCs was facilitated by Kaza, Gnutella, Bit Torrent. Later Wikipedia, Technoarti, Flickr, Fotolog, Delicious, LinkedIn, My Space and FaceBook allowed social networking, bookmarking, blogging and dating including virtual reality environments like SecondLife. User contributed content was another important component like in YouTube were audience begun producing content. All this new ambient was named web2.0 and Kevin Kelly affirmed that “we are the web”.  The wealth of the networks now is based on commons peer production and profits do not come from comments but from attention and banner clicks. The time spent become the central value of the Internet.

But going back to the history of Network Learning merging fields and theortical views of learning, knowledge and cognition helped in paving a new epistemology space. Backed by the massive participation in the web based in the 1billons people on-line, the 2M reports in Wikipedia, the 200M members in My Space,  the 80M blogs in Technorati, the 900,000 members of affiliate program of Amazon and the 30M users Facebook + 4M/month, a model for the process involved in education and learning was a must. May connectivism play this role?          

Week 3 – Networks concept map

October 1, 2008
Network concept map

Network concept map

Week 3 – Networks, networks, networks…

October 1, 2008

The discovery of hidden patterns shows great regularities in the Universe. For example, inner structure of Internet, information linkage in the web, people interaction in social networks. A surprising bridge in between local properties or individual actions and the resulting collective interactions.

The structure and dynamic of the system is determined by the collective interactions of all of its constitutive parts, and at the same time, it’s individual behavior are framed by the topology and dynamic that emerges.

This take us near getting the answers to understand the stability of large ecosystems in nature to present fluctuations of financial markets.

 In the last years, psychologists, biologists, mathematicians, physics and other scientist have shared their observations and built a new epistemological space that we could call the new science of networks. A new theoretical perspective that provides tools to physicists to battle against epidemics, engineering to prevent fails in cascades in large interconnected systems like the power grid or visionary economic analysts that anticipate financial meltdowns.

We had built tools that allow us to graph and view these connections between nodes. We begin finding hidden laws that govern the formation, growth, evolution of these networks.

Kant argued that time and space are the natural and irreducible categories of mind, way how we perceive reality. A reality that manifest itself also as intricate networks.

Stability, synchronicity, self similarity, threshold, cascades, epidemics, emergency, resiliency, keystones, phases, connectors, evolution, clustering are some of the new way of seeing and thinking the world.  A simpler world that connects very diverse phenomenon, entities and realities.  A world that needs to learn on networked thinking.

 

 

 

 

Connective knowledge (Week 2): It is the organization, stupid!

September 21, 2008

This second week of the Connectivism course brought to me what is one of my basics questions in Networks Science. If a human mind can know and if a mind is basically a network, then any network can come to know? Seems that the network organization with its structure and dynamic is what makes possible to know.

 

The brain responds to environmental demands, generating, creating, strengthening, weakening, losing and eliminating neural connections. So mind is a construct which is distributed from the brain to the environment (Kerr). Plasticity is intrinsic core feature of the brain.

 

When something impacts a network, the connections between the objects in the network change. And this results in storage of information. Learning results of integrating all information perceived and processed that leave a physical trace of its passage, generating new network organization patterns.

 

But how language, which is another specifically human cognitive function dedicated to communication (and thinking), has also a role in developing knowledge?

CCK08 – What Connectivism is? – Concept Map

September 16, 2008

… and finally a concept map on Connectivism.

Connectivism concept map

Connectivism concept map