What is Connectivism? Week 1: CCK09

Original: George Siemens, What is connectivism?, September 12, 2009, licence;

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Forked: James Neill, September 17, 2009

Anyone can edit: Be bold

Note that there are also tweets (#CCK09), blog posts, and a Discussion forum about this topic. Mashups of the feeds include: [1].

What is connectivism? edit

Connectivism is a learning theory advocated by George Siemens and Stephen Downes, among others, which emphasizes the importance and role of networks and connections between people (and things?) as prominent (central) to the learning process.

"Connectivism is a learning theory that explains how Internet technologies have created new opportunities for people to learn and share information across the World Wide Web and among themselves... A key feature of connectivism is that much learning can happen across peer networks that take place online."[1]

This learning theory claims individual's knowledge is distributed and lives not only in their brain, but also in connections with electronic and human components. That, in turn, allows the learner to develop in their course of learning. It is truly a learning theory for this digital era.

The theory of connectivism has been created to understand how we learn in a networked society and exists due to the exponential growth and complexity of information available on the Internet and the new possibilities to communicate on global networks (Siemens, 2008). The three learning theories most frequently utilized in instructional contexts: behaviorism, constructivism, and cognitivism receive an ambitious approach named connectivism which addresses learning within and across the networks.

Additionally, connectivism refers to connected learning networks, or “nodes”. The greater the network of a node, the greater the connection and therefore, the greater the likelihood of learning. Weaker connected nodes or small world networks, such as finding a new hobby or new job, rely more on chance rather than high-level nodes or networks (Siemens, 2005). A strength of the connectivist approach is its emphasis on learners claiming autonomy over their own learning in development of a personal learning network (Siemens, 2005).

The Principles of Connectivism

• Learning and knowledge rest in the diversity of opinions.

• Learning is a process of connecting specialized nodes or information sources.

• Learning may reside in non-human appliances.

• Capacity to know more is more critical than what is currently known.

• Nurturing and maintaining connections is needed to facilitate continual learning.

• Ability to see connections between fields, ideas, and concepts is a core skill.

• Currency (accurate, up-to-date knowledge) is the intent of all connectivist learning activities.

• 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 (Siemens, 2004).

• Knowledge is created as learners work to understand the experiences around them (Driscoll, 2000).

• Learning as community development.

Weaker and Stronger Ties

The concept of weaker ties making a network stronger is presented in Network Theory, based on Granovetter’s article on the nature of strong and weak ties, and was further expanded upon by Barabási (2003) and Buchanan (2003) with the observation that many networks are “scale free.” “Power functions mathematically define the fact that in real networks, the majority of points have only a few ties, and these numerous little points coexist with a few large central points that have an unusually large number of ties” (Barabási, 2003, p. 100).

Péter Csermely makes the point that weak ties are what make networks strong. “A tie between two elements of the network is weak if taking away or adding the tie does not influence in a statistically sensitive way the average of the network’s typical characteristics (usually one of the group-defining characteristics of the network). Weak ties stabilize networks” (Csermely, 2005, p. 363).

In 2006 Jones and co-authors also discussed the non-hierarchical nature of networked learning in which many weak ties exist, including the ties between students and their professors, each other, and other sources of knowledge.

Siemens says that, “Knowledge does not only reside in the mind of an individual, knowledge resides in a distributed manner across a network . . . learning is the act of recognizing patterns shaped by complex networks" (Siemens, 2006, p. 10).

Role of the Educator

Siemens discusses the role of the educator in one of four models: Master Artist, Network Administrator, Concierge, and Curator. The idea of the Master Artist (Seely Brown, 2006) sets the instructor as a master painter in an art class, free to observe the students and point out areas of exceptionalism. Here the students learn from each other with inspiration and guidance from the Master. Clarence Fisher (n.d.) postulates that the teacher functions as a Network Administrator, helping the learner create their learning network. The instructor is available to give perspective on the information and assist the student in evaluating their findings to decide which is the best sources for learning. The Concierge model, by Curtis Bonk (2007), sees educators directing their students by offering resources to start their exploration. The Concierge shows the learner avenues they may not have found on their own, sometimes through a traditional lecture format and other times allowing the learner to explore on their own. Siemens adds the last role of the educator as Curator: "A curator is an expert learner. Instead of dispensing knowledge, he (she) creates spaces in which knowledge can be crafted, explored, and connected. While curators understand their field very well, they don't adhere to traditional in-class teacher-centric power structures. A curator balances the freedom of individual learners with the thoughtful interpretation of the subject being explored. While learners are free to explore, they encounter displays, concepts, and artifacts representative of the discipline" (Siemens, 2008).

All four roles work together with the goal of joining educator expertise to learner construction. As educator take on the active and essential role of teaching and evaluating learners, they must be mindful of the “rapid information growth, increased learner control of information creation and dissemination, and the growing reliance on network models to address complex changes in society are trends that continue to impact much of society.” Educators must support students by facilitating learning experiences that are social, engaging, and connected to prior knowledge (Siemens, 2008, p. 17).

In the Overview of Connectivism video, George Siemens (2013) discusses how connectivism emerged through the digital age as opposed to a face-to-face classroom setting. Connectivism is a "social connected process of learning." Siemens asserts that, "in a networked world, learning is a network forming process, knowledge is a networked product" and occurs at three levels: a biological level, forming conceptual connections, and, lastly, through external social spaces.

Within connectivism in open online learning environments is that the learning involves "active engagement of people with resources in communication with others, rather than the transfer of knowledge from educator to learner" (Kop, 2011, p.20). This means that knowledge is shared among everyone and a sense of connectivism is gained. The knowledge isn't just gained with people in the same room, but can be distributed across the internet, with users engaging with it online "constitute learning" (Kop, 2011, p.20).

Connectivism glossary edit

A helpful way to get started with understanding connectivism is to read over the connectivism glossary.

The rest of this page edit

What follows is some (currently) lightly adapted content originally by Siemens about "what is connectivism?" - an initial class reading - which readers should feel welcomed to edit and improve upon as an introduction to connectivism.

Distinguishing learning theory edit

Mergel’s emphasis on Ertmer’s and Newby’s “five definitive questions to distinguish learning theory” (Distinguishing One Learning section, ¶ 1) provides a framework to organize various theories:

  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? (¶ 2)

How connectivism differs edit

The table below indicates how prominent learning theories differ from connectivism:








Learning theorists

Thorndike, Pavlov, Watson, Guthrie, Hull, Tolman, Skinner

Koffka, Kohler, Lewin, Piaget, Ausubel, Bruner, Gagne

Piaget, Vygotsky

Maslow, Rogers


Siemens, Downes

How learning occurs

Overt and covert behaviors are the same with respect to how they are acquired and modified - they differ only in terms of who can observe the changes. learning is represented as a persistent change in either an overt or covert behaviour.

Structured, computational

Social, meaning created by each learner (personal)

Reflection on personal experience

Learning through doing

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

Influencing factors

Relationship between the antecedent stimuli and consequence stimuli on the response (behaviour). Main mechanism of behaviour change are the changes in the environment following a behaviour (reinforcement/punishment)

Existing schema, previous experiences

Engagement, participation, social, cultural

Motivation, experiences, relationships

Engagement , participation

Diversity of network, strength of ties, context of occurrence

Role of memory

Memory is the precurrent behavior that occurs at the time of acquisition in preparation for problem solving that occurs at the time of remembering (Palmer, 1991)

Encoding, storage, retrieval

Prior knowledge remixed to current context

Holds changing concept of self

Reflection, critical analysis, synthesis

Adaptive patterns, representative of current state, existing in networks

How transfer occurs


Duplicating knowledge constructs of “knower”


Facilitation, openness

Cycle of concrete experiences, reflective observation, abstract conceptualization, active experimentation

Connecting to (adding) nodes and growing the network (social/conceptual/biological)

Types of learning best explained

Task-based learning, Reasoning, problem solving, interpersonal skill development, complex learning

Reasoning, clear objectives, problem solving

Social, vague
(“ill defined”)


Connecting concrete with abstract, development of new concepts

Complex learning, rapid changing core, diverse knowledge sources

Criticisms edit

Even Siemens (2008) points out that his idea of a new learning theory “based on network structures, complex changing environments, and distributed cognition” has drawn criticism (Learning and Knowing in Networks: Changing roles for Educators and Designers). For example, Pløn Verhagen (2006), in his critique of connectivism, deems it ineffective and “unsubstantiated philosophising” (¶ 14). In Bill Kerr’s challenge to connectivism (2006), he agrees that networks have become important for learning but disagrees that connectivism is necessary because we already have existing theories that satisfactorily address learning in a technologically connected world. Curtis Bonk similarly argues against connectivism as theory and instead suggests it “belongs in a sociological, or anthropological, conception of learning” (Siemens 2008).

Frances Bell ((2011). Connectivism: Its place in theory-informed research and innovation in technology-enabled learning. The International Review of Research in Open and Distributed Learning, 12(3), 98-118. https://doi.org/10.19173/irrodl.v12i3.902) argues that although Connectivism is influential, without the development of a substantial research base it will not be perceived as a standalone learning theory.

Another critique is that other, more suitable, theories exist to answer the questions connectivism attempts to address, such as communities of practice, actor-network theory, and activity theory.

Despite these and other detractors, proponents of connectivism and the concept of networked learning in general, continue to pursue a model of learning that reflects the network-like structure of online interactions that Siemens proposes. Siemens presents as evidence the attendance and discussion at University of Manitoba’s 2007 Online Connectivism Conference, and the level of interest in the course he built with Stephen Downes, Connectivism and Connective Knowledge (CCK08). However, the popularity of a topic or theory should not be the sole basis for declaring something a "new learning theory."

The alternative? Some propose that connectivism be viewed as pedagogy rather than theory, as methodology rather than model, as practice rather than principle. Seen in this way, connectivism as a pedagogical movement has some promising methods worthy of consideration and adoption. Cf. Connectivism as Pedagogy.

Distinctiveness edit

What then, do we find to be distinct about connectivism?

  1. Existing theories of learning fail to account for the expansion and creation of knowledge (what Bereiter calls the learning paradox: “If learners construct their own knowledge, how is it possible for them to create a cognitive structure more complex than the own they already possess (cited in Cambridge Handbook of Learning Sciences, p. 103). Connectivism and networked learning, on the other hand, suggest a continual expansion of knowledge. New and novel connections open new worlds and create new knowledge.
  2. The primacy of the connection – all other forms of learning flow from an initial connection to something – a person, a concept, and idea. Connectivism emphasizes the primacy of the connection and suggests understanding learning is found in understanding how and why connections form. Connections are formed at various levels: neural, cognitive/conceptual, and social.
  3. Growth in abundance and complexity of knowledge. The sheer quantity of information available to most people today is overwhelming. How can we manage? How can existing theories of learning assist us in embracing information as a continual process, rather than an event (constructivism comes closest in this regard)? How do we account for self-organization? For complexity? Clearly, a learning theory is one that should provide a conduit for considering more than the act of learning itself and inform us as to how multiple aspects of information creation interact and evolve.
  4. Technology. There is hesitation to emphasize technology as it suggests an embrace of web 2.0 utopian hype. But it’s difficult to ignore technology. Looking to our history reveals the prominence of technology in opening new doors – from writing to air travel. Technology is an enabler of new opportunities. While we’ve encountered years of hype, the internet is truly a unique invention that ties together the globe and people.
  5. Connectivism brings together concepts from different domains in a novel way. It is rare to have a singularly unique idea. Even existing theories – behaviourism, constructivism, and cognitivism, do not stand as fully complete and original ideas. What makes each of these theories unique is the manner in which they bring together research and concepts prominent during their particular age. Constructivism is an aggregation of thoughts that span from Dewey to von Glaserfeld to Papert. In a similar sense, connectivism is unique in bringing together ideas of neuroscience, cognitive science, network theory, complex systems, and related disciplines. While it is still a somewhat uneasy mix (we can’t simply throw buzzwords into a pot and call it a theory), as much (perhaps more) evidence exists for the key assertions in connectivism as does in any other theory of learning. The very intent of this course is to expand the base of connectivism and explore which principles are involved in the theory.
  6. Beyond a summative theory, it is simultaneously a method. Like many learning theories, connectivism attempts to describe or deconstruct how we learn in such a way as to inform changes to instructional design. But it can also be considered outside of the instructor-learner dyad, allowing an independent learner of any type to deploy a method for investigating a topic of interest, or to laying the foundation for future learning by, for example developing their personal learning network. Learners may choose to identify a professional learning network.

Questions edit

  1. What's the difference between connectivism and networked learning? [2]
  2. What's the difference between connectivism and constructivism?
  3. What's the difference between connectivism and social / situated learning as in communities of practice?
  4. What's the difference between connectivism and autopoiesis?
  5. How does connectivism fit within a professional learning network? Are those two related?
  6. What is the role of teachers and instructors in connectivism?
  7. How does the validity of the information on the internet effect the teachers and instructors in connectivism?
  8. With connectivism being the way education is leaning, how do we assure protection from predators and marketers for our students?
  9. How do we ensure learners have interpersonal skills while engaging in technology based learning?

Blogs/ blog posts edit

  1. Connectivism and constructivism, Christy Tucker
  2. Deciphering connectivism, April Hayman
  3. User:Jtneill/Blogs/CCK09, James Neill
  4. What Connectivism Is, Stephen Downes
  5. Connectivism: The Future of Learning?, Erika Huezo
  6. Constructing Knowledge, Alyssa Mills
  7. Connecting with Knowledge, Zelma Soto-Rodriguez

References edit

  1. Barabási, Albert-László (2003). Behálózva. A hálózatok új tudománya. [Enwebbed. The new science of networks] Magyar Könyklub [Hungarian Book Club].
  2. Buchanan, Mark (2003). Nexus, avagy kicsi a világ. A hálózatok úttörő tudománya.[Nexus, or what a little world we live in. The pioneer science of networks] Typotex Kiadó, [Typotex Publishing House] Budapest.
  3. Downes, S. (2005). An introduction to connective knowledge. In T. Hug (Ed.) (2007) Media, Knowledge & Education - Exploring new Spaces, Relations and Dynamics in Digital Media Ecologies. Proceedings of the International Conference held on June 25-26, 2007. November 27, 2007.
  4. Downes, S. (2007). What connectivism is, Half an Hour: A place to write, half an hour, every day, just for me
  5. Jones, C./Ferreday, D./Hodgson V. (2006). Networked Learning, a relational approach – weak and strong ties. In S. Banks, V. Hodgson, C. Jones, B. Kemp, D. McConnell and C. Smith (eds) Proceedings of the Fifth International Conference on Networked Learning 2006. Lancaster: Lancaster University.
  6. Kop, R. (2011) The Challenges to Connectivist Learning on Open Online Networks: Learning Experiences during a Massive Open Online Course, "International Review of Research in Open and Distance Learning"
  7. Siemens, G. (2005). Connectivism: A learning theory for the digital age, International Journal of Instructional Technology & Distance Learning, 2(1).
  8. Siemens, G. (2008). What is the unique idea in Connectivism?, Connectivism: Networked and social learning.
  9. Siemens, G. (January 27, 2008). Learning and Knowing in Networks: Changing roles for Educators and Designers. Presented to ITFORUM for Discussion.
  10. Siemens, G. (August 2013). Overview of connectivism - Dr George Siemens. Presented at the University of the Sunshine Coast, Queensland, Australia.

See also edit

External links edit

  1. "Connectivism (Siemens, Downes)". Learning Theories. 2015-06-01. Retrieved 2019-03-10.