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ⓘ Connectivism




                                     

ⓘ Connectivism

Connectivism is a theoretical framework for understanding learning in a digital age. It emphasises how internet technologies such as web browsers, search engines, wikis, online discussion forums, and social networks contributed to new avenues of learning. Technologies have enabled people to learn and share information across the World Wide Web and among themselves in ways that were not possible before the digital age. Learning does not simply happen within an individual, but within and across the networks. What sets connectivism apart from theories such as constructivism is the view that "learning can reside outside of ourselves, is focused on connecting specialized information sets, and the connections that enable us to learn more are more important than our current state of knowing". Connectivism sees knowledge as a network and learning as a process of pattern recognition. Connectivism has similarities with Vygotskys zone of proximal development and Engestroms Activity theory. The phrase "a learning theory for the digital age" indicates the emphasis that connectivism gives to technologys effect on how people live, communicate, and learn. Connectivism is an integration of principles related to chaos, network, complexity, and self-organization theories.

                                     

1. History

Connectivism was introduced in 2005 by two publications, Siemens’ Connectivism: Learning as Network Creation and Downes’ An Introduction to Connective Knowledge. Both works received significant attention in the blogosphere and an extended discourse has followed on the appropriateness of connectivism as a learning theory for the digital age. In 2007 Kerr entered into the debate with a series of lectures and talks on the matter, as did Forster, both at the Online Connectivism Conference at the University of Manitoba. In 2008, in the context of digital and e-learning, connectivism was reconsidered and its technological implications were discussed by Siemens and Ally.

                                     

2. Nodes and links

The central aspect of connectivism is the metaphor of a network with nodes and connections. In this metaphor, a node is anything that can be connected to another node such as an organization, information, data, feelings, and images. Connectivism recognizes three node types: neural, conceptual internal and external. Connectivism sees learning as the process of creating connections and expanding or increasing network complexity. Connections may have different directions and strength. In this sense, a connection joining nodes A and B which goes from A to B is not the same as one that goes from B to A. There are some special kinds of connections such as "self-join" and pattern. A self-join connection joins a node to itself and a pattern can be defined as "a set of connections appearing together as a single whole".

The idea of organisation as cognitive systems where knowledge is distributed across nodes originated from the Perceptron Artificial neuron in an Artificial Neural Network, and is directly borrowed from Connectionism, "a software structure developed based on concepts inspired by biological functions of brain; it aims at creating machines able to learn like human".

The network metaphor allows a notion of "know-where" the understanding of where to find the knowledge when it is needed to supplement to the ones of "know-how" and "know-what" that make the cornerstones of many theories of learning.

As Downes states: "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".

                                     

2.1. Nodes and links Principles

Principles of connectivism include:

  • Currency accurate, up-to-date knowledge is the intent of learning activities.
  • Learning may reside in non-human appliances.
  • Learning and knowledge rests in diversity of opinions.
  • Perceiving connections between fields, ideas and concepts is a core skill.
  • Learning is a process of connecting specialized nodes or information sources.
  • Decision-making is itself a learning process. Choosing what to learn and the meaning of incoming information is seen through the lens of a shifting reality. While there is a right answer now, it may be wrong tomorrow due to alterations in the information climate affecting the decision.
  • Learning is more critical than knowing.
  • Maintaining and nurturing connections is needed to facilitate continual learning.
                                     

3. Teaching methods

Summarizing connectivist teaching and learning, Downes states: "to teach is to model and demonstrate, to learn is to practice and reflect."

In 2008, Siemens and Downes delivered an online course called "Connectivism and Connective Knowledge". It covered connectivism as content while attempting to implement some of their ideas. The course was free to anyone who wished to participate, and over 2000 people worldwide enrolled. The phrase "Massive Open Online Course" MOOC describes this model. All course content was available through RSS feeds, and learners could participate with their choice of tools: threaded discussions in Moodle, blog posts, Second Life and synchronous online meetings. The course was repeated in 2009 and in 2011.

At its core, connectivism is a form of experiential learning which prioritizes the set of formed by actions and experience over the idea that knowledge is propositional.

                                     

4. Criticisms

The idea that connectivism is a new theory of learning is not widely accepted. Verhagen argued that connectivism is rather a "pedagogical view."

The lack of comparative literature reviews in Connectivism papers complicate evaluating how Connectivism relates to prior theories, such as Socially Distributed Cognition Hutchins, 1995, which explored how connectionist ideas could be applied to social systems. Classical theories of cognition such as Activity theory proposed that people are embedded actors, with learning considered via three features – a subject the learner, an object the task or activity and tool or mediating artifacts. Social cognitive theory Bandura, 1962 claimed that people learn by watching others. Social learning theory Miller and Dollard elaborated this notion. Situated cognition alleged that knowledge is situated in activity bound to social, cultural and physical contexts; knowledge and learning that requires thinking on the fly rather than the storage and retrieval of conceptual knowledge. Community of practice Lave & Wenger 1991 asserted that the process of sharing information and experiences with the group enables members to learn from each other. Collective intelligence Levy, 1994 described a shared or group intelligence that emerges from collaboration and competition.

Kerr claims that although technology affects learning environments, existing learning theories are sufficient. Kop and Hill conclude that while it does not seem that connectivism is a separate learning theory, it "continues to play an important role in the development and emergence of new pedagogies, where control is shifting from the tutor to an increasingly more autonomous learner."

AlDahdouh examined the relation between connectivism and Artificial Neural Network ANN and the results, unexpectedly, revealed that ANN researchers use constructivism principles to teach ANN with labeled training data. However, he argued that connectivism principles are used to teach ANN only when the knowledge is unknown.

Ally recognizes that the world has changed and become more networked, so learning theories developed prior to these global changes are less relevant. However, he argues that, "What is needed is not a new stand-alone theory for the digital age, but a model that integrates the different theories to guide the design of online learning materials.".

Chatti notes that Connectivism misses some concepts, which are crucial for learning, such as reflection, learning from failures, error detection and correction, and inquiry. He introduces the Learning as a Network LaaN theory which builds upon connectivism, complexity theory, and double-loop learning. LaaN starts from the learner and views learning as the continuous creation of a personal knowledge network PKN.



                                     
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  • September 2015 Online learning environments in higher education: Connectivism vs. dissociation Education Information Technology. 20 3 579 588
  • distance education, theorist in distance education, creator of theory of Connectivism leader in learning analytics The Government of Canada sponsors an Aboriginal
  • Analytics Knowledge LAK 2011 Retrieved 12 February 2014. Siemens, G., Connectivism A learning theory for the digital age, International Journal of Instructional
  • Cognitive science Cognitive psychology Computational theory of mind Connectivism Cultural psychology Distributed cognition Embodied cognition Embodied
  • resources. Bookboon adware Commonwealth Computer Navigator s Certificate Connectivism Distance education Educational research Educational technology Flexbook
  • 4 257 - 268. Siemens G 2010 Struggling for a metaphor for change. Connectivism Networked and Social Learning 2 Sept 2009 posting Souto - Manning
  • Acquisition of L2 Phonology. Multilingual Matters. The CCK08 MOOC Connectivism course, 1 4 way Dave s Educational Blog Laura Pappano. The Year of

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