Una Teoría Educativa Para la Era Digital

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CCK08: Primer paper del curso de conectivismoCCK08: Connectivism Course First Paper CCK08

CCK08. Disculpa, este texto solo está disponible en inglés.

CCK08. We live in a complex and changing world. A world in which knowledge is rapidly growing with multiple tools augments our ability to interact with each other. The learning process is changing and we need new models and metaphors to explain how knowledge is acquired. Nowadays digital technology is an important part of everyday life for almost all students and some teachers. As Prensky says, “our students are all «native speakers» of the digital language of computers, videogames and the Internet” (Prensky, 2001). Does this affect the way in what students learn?

According to Prensky a typical high school student in USA have watched 20,000 hours of television; have spent 10,000 hours playing videogames and have been reading only 5,000 hours. The new generation is digital native and it means there are a new attitude to technology and some new process that affects learning. Some of them are:

  • Friends distributed across multiple networks as instant messengers, social networks (MySpace, Facebook, etc.), email addresses and cell phone contacts.
  • Online reading and writing. The screen is a natural place to access and show information that could be text, pictures, videos, chat session, forum discussions or a Wikipedia article. As opposed to previous generation with strong text-based learning, digital natives make an intensive media mix.
  • Emphasis on practice. Digital natives usually don’t read manuals or instructions and trust that devices can teach how to manipulate them itself. Trial and error is often a quickly way to get what you want quickly.

Connectivism is a learning theory that fits perfectly to this context and explains how learning happens in a rapid changing core of global knowledge. Connectivism can be defined as “the application of network principles to define both knowledge and the process of learning. Knowledge is defined as a particular pattern of relationships and learning is defined as the creation of new connections and patterns as well as the ability to maneuver around existing networks/patterns” (Siemens, 2008).

To understand the network metaphor we need to know a bit about networks theory. For Wellman a network consist of one or more nodes connected by on or more ties. Nodes are a unit that possibility is connected (for example, individuals, households, workgroups, organizations, states, etc) and ties are one or more specific type of connection. Networks form distinct and analyzable patterns with emergent properties. Following this concepts it is possibly to represent a college student learning network in a graphic like this:

We can explain how learning occurs following nodes and ties and understanding that the key of learn is the process of make connections. The more nodes an ties, the more strong is the knowledge. This is a good way to represent how we learn across diverse sources recognizing and interpreting patterns within a network that is changing continuously. However, there are some questions to connectivism that I have no answer for the moment.

  • Connectivism is clearly related to network theory that is relevant to see connections and relationship between components of a process. Nevertheless, is knowledge only the sum of nodes and ties? If the answer must yes… are these entities relevant to explain by itself the whole learning process.
  • Think in this example: All computer programs are at least a vast group of zeros and ones. It’s a fact. But can not understand and explain how it works analyzing only these numbers. The binary code represents process, relationship and interaction. In other words, software is more than the binary code.
  • What is the role of external factors? Culture, environment and context influence the learning process and favor some relationship instead of others. Networks don’t exist in an empty space and there are some other elements that determine and model knowledge acquisition.

Nonetheless, these questions to come from an initial impressions after introducing in connectivism theory. Perhaps, I loosing some vital node or ties to understand it in a more deeply way.


October 6, 2008   2 Comments

X-ray of a know-it-allRadiografía de un sabelotodo

Know it All

X-ray of a know-it-all

Know it All

Radiografía de un sabelotodo

September 30, 2008   No Comments

The social network theoryLa teoría social de redes

This third week the course of Conectivismo -with George Siemens and Stephen Downes as facilitators- is oriented to reflect on the networks. The theory of networks is of which they are begun mentioning a pair of things that seem obvious but that quickly go more and more comlex. Like the mathematical one.

In a sentence, the theory of networks consists…

“To discover how A, who is touch with B and C, is affected by the relationship between B and C”

(John Barnes)

Barry Wellman’s slides [ppt] begins saying simple things like these. This theory assumes that the reality can be represented like a set of connected units. A network consists of one or more nodes and these nodes can be practically any thing: people, organizations, groups, nations, etc.

The connections between nodes are “ties” and the theory of networks studies the patterns of relationship, the emergent properties that indicate microsociological studies of Homans or Simmel. Here the things goes more complex and we have to follow one specific methodology with multiple levels of analysis. Differences among actors are traced to the constraints and opportunities that arise from how they are embedded in networks.

At Wednesday’s session Valdis Krebs gave us some interesting examples of things that can be analyzed through Social Networks Analysis (SNA) methodology. SNA is a mathematical and visual analysis of relationships, flows and influence between people, groups, organizations, computers or other information/knowledge processing entities.

Key Opinion Lider

Key Opinion Leaders

In this example Krebs SNA to make he classical study of Lazersfed [doc] on key opinion leaders (in red). As it is seen, the structure is much more complex that the scheme of two-step flow usually used to explain it.

Porn Star HIV Networks

Porn Star HIV Network

This other example shows to the propagation of HIV at porn industry of United States in 2004. At the centre is Darren James who was the first infected by HIV. The red points represent stars infected, yellow points those who had pending results and green points are the actors without HIV.

Can you find the terrorists?

Can you find the terrorists?

Here Krebs shows the connections how terrorists (on the right) has much smaller density bond between its members, although it centers strongly is connected in two cases.

The social networks theory is a mathematical model to analyze the interrelations and is specially useful to diagnose communication processes at organizations. In the educative field, connectivism is clearly the extrapolation of network metaphor to the scope of knowledge to show how people construct it.

At first sight, the main limitation of the model seems to be that bonds are defined in binary terms: there is relationship (1) or there isn’t (0). Nevertheless, the complexity of human interaction (and knowledge acquisition) has nuances and levels which cannot be discriminated as yes/no. Perhaps in these cases we must return to analyze the details to establish a new network that’s with new and more detailed nodes and bonds.

Esta tercera semana el curso de Conectivismo a cargo de George Siemens y Stephen Downes está orientado a reflexionar sobre las redes. La teoría de redes es de esas que se comienzan mencionando un par de cosas que parecen obvias pero que rápidamente se van complejizando. Como la matemática.

“En síntesis, la teoría de redes consiste en como A, que es está conectado con B y C, es afectado por la relación entre B y C”

(John Barnes)

La presentación de Barry Wellman [ppt] comienza diciendo cosas sencillas como estas. Esta teoría asume asume que la realidad puede ser vista como un conjunto de unidades conectadas entre sí. Una red consta de uno o más nodos y estos nodos pueden ser prácticamente cualquier cosa: personas, organizaciones, grupos, naciones, etc.

A las conexiones entre nodos se les llaman vínculos y la teoría de redes se encarga de estudiar los patrones de relaciones o vínculos, las propiedades emergentes que señalan los estudios microsociológicos de Homans o Simmel. Aquí es donde la cuestión comienza a ser más compleja ya que hay seguir una metodología específica con múltiples niveles de análisis donde se analizar las diferencias entre actores a partir de las constricciones y oportunidades que pueden surgir por cómo están embebidos en sus redes.

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September 25, 2008   No Comments

Network and WorkersRedes y Trabajadores

When you hire someone, you “hire” his or her network.

Robin Teigland, Stockholm Schools of Economics (link)

Cuando contratas a alguien, “contratas” su red.

Robin Teigland, Stockholm Schools of Economics (link)

September 24, 2008   No Comments

What is connectivism?¿Qué es el conectivismo?

“At its heart, connectivism is the thesis that knowledge is distributed across a network of connections, and therefore that learning consists of the ability to construct and traverse those networks”.

Stephen Downes, What Connectivism Is.

Welcome to connectivism blog!

Let’s start with presentations. My name is Sebastián Thüer, I have a degree in Communication Science and I’m attending for doctorate in New Technologies and Communication at Malaga University (Spain). This blog is a space that born from the online course I’m doing about Connectivism and Connective Knowledge.

Connectivims is a theory about learning that, as says the quote above, proposes the basic activity of learning is construct networks thought nodes of information. The main connectivism theorists are George Siemens and Stephen Downes.

The metaphor of learning as a network is not new. As Siemens says, every new theory has roots in previous ideas updated to the actual context. The point is to know if these ideas are useful to build an explicative model that allows to know better the reality.

A interesting way to approach to connectivims is to compare it with other learning theories. Brenga Mergel (1998) has a paper where his quote Peeg Ermet and Tomoty Newby to make five questions the get the basis for a learning theory. The questions are:

  1. How does learning occur?
  2. What factors influence learning?
  3. What is the role of memory?
  4. How does transfer occur?
  5. What types of learning are best explained by this theory?






How learning occurs

Black box—observable behaviour main focus

Structured, computational

Social, meaning created by each learner (personal)

Distributed within a network, social, technologically enhanced, recognizing and interpreting patterns

Influencing factors

Nature of reward, punishment, stimuli

Existing schema, previous experiences

Engagement, participation, social, cultural

Diversity of network, strength of ties

Role of memory

Memory is the hardwiring of repeated experiences—where reward and punishment are most influential

Encoding, storage, retrieval

Prior knowledge remixed to current context

Adaptive patterns, representative of current state, existing in networks

How transfer occurs

Stimulus, response

Duplicating knowledge constructs of “knower”


Connecting to (adding) nodes

Types of learning best explained

Task-based learning

Reasoning, clear objectives, problem solving

Social, vague
(“ill defined”)

Complex learning, rapid changing core, diverse knowledge sources

“En su corazón, el conectivismo es la tesis de que el conocimiento está distribuido a lo largo de una red de conexiones, y por lo tanto el aprendizaje consiste en la habilidad de construir y atravesar esas redes”. Stephen Downes, What Connectivism Is.

¡Bienvenido al blog de conectivismo!

Comencemos por las presentaciones. Mi nombre es Sebastián Thüer, soy licenciado en Ciencias de la Comunicación y estoy haciendo un doctorado en la Universidad de Málaga (España) sobre Nuevas tecnologías y Comunicación. Este blog es un espacio que nace a partir del curso online que estoy haciendo sobre conectivismo y aprendizajo conectivo.

El conectivismo es teoría acerca del aprendizaje que, como dice la cita de arriba, postula que la actividad básica del aprendizaje es construir redes a través de nodos de información. Sus principales referentes son George Siemes y Stephen Downes.

La metáfora del aprendizaje como una red no es nueva. Como dice Siemens, toda teoría actual tiene su origen en ideas anteriores que se actualizan al contexto actual. Lo importante es saber si estas ideas permiten construir un modelo explicativo que permita comprender mejor la realidad.

Una manera interesante de acercarnos al conectivismo es compararla con otras teorías del aprendizaje. Brenda Mergel (1998) cita en un trabajo a Peggy Ertmer yTomothy Newby para proponer cinco preguntas que permiten construir un marco de análisis. Estas son:

  1. ¿Como sucede el aprendizaje?
  2. ¿Qué factores influyen en el aprendizaje?
  3. ¿Qué papel juega la memoria?
  4. ¿Cómo se da la transferencia?
  5. ¿Qué tipo de aprendizaje es explicado mejor por la teoría?

En el desarrollo del curso el propio Siemens se ha encargado de comparar el conectivismo con otras teorías como el conductismo, el cognitivismo y el constructivismo. El resultado es el siguiente:






¿Cómo ocurre el aprendizaje?

Caja Negra -foco en el comportamiento observable

Estructurado, computacional

Social, el sentido es creado por cada persona

Distribuido dentro de una red, social, mejorado por la tecnología, reconocimiento e interpretación de patrones

Factores de influencia

Premio, castigo, estímulo

Esquemas existentes, experiencias previas.

Compromiso, participación, sociedad, cultura

Diversidad de redes, fortaleza de los vínculos

Rol de la memoria

La memoria es el entramado de experiencias repetidas -donde los premios y castigos son más influyentes.

Codifica, almacena, recupera

El conocimiento previo se mezcla con el contexto actual

Patrones de adaptación, representación del estado actual, existe en las redes

Cómo se da la transferencia Estímulo-respuesta Duplicating knowledge constructs of “knower” Socialización Conectando a / añadiendo nodos

September 19, 2008   2 Comments