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This page was originally authored by Micah Williams (2008). This page has been revised by Tom Whyte (2011). This page has been revised by Simon Bailey(2017).

George Siemens (with permission granted)

Connectivism proposes that learning and knowledge exists within networks. The basis of this learning theory shares beliefs with Vygotsky’s Activity Theory and Social Constructivism, in that through interaction, social activity and collaboration learning occurs. However, unlike Connectivism, these theories (including Behaviorism, and Cognitivism) do not address learning outside of the body, nor learning that is stored and manipulated by technology within networks. Even though Connectivism is not at this time an academically recognized learning theory, the global education system must consider its implications for student learning.

Watch this video for an overview of Connectivism.


A simple diagram of connectivism

According to George Siemens, “Connectivism presents learning as a connection/network-forming process” (Siemens, 2005) [1]. Where knowledge is gained through connecting to nodes (any element that can be connected to another element) and providing information back into a network (aggregation of strong and weak nodes), creating a cycle of knowledge development which allows for learning and the ability for individuals to stay current in their field of study (Siemens, 2004) [2]. However, due to the shrinking half-life of knowledge (Gonzalez, 2004) [3], Connectivism states that a leaner must be able to, or learn to filter content based upon information accuracy and relevancy at that point in time. Learners must also be able to filter nodes (as these individual elements can weaken, causing the network to self-organize and adjust) based upon accuracy and relevancy within a network. This constant decision making based on filtered content can change thinking so that future decisions are based on the latest information.

Main Elements

A Network Connection - The ability to access information is more important than the information itself
  • Accurate and up-to-date knowledge (currency) is the intent of all Connectivist learning (Siemens, 2004)
  • Decision-making is essential to learning, and is itself a learning process. For example, deciding what is important to learn shifts with the information climate (Siemens, 2004)
  • The capacity to know more is more important than what is currently known. For example, knowing where to locate information is more important than knowing information (Siemens, 2004)
  • The ability to determine connections between multiple fields, ideas, and concepts is fundamental (Siemens, 2004)
  • The integration of cognition and emotions are important to the development of meaning (Siemens, n.d.) [4]
  • Connections within a network must be maintained and nurtured to facilitate continual learning (Siemens, n.d.)
  • Learning may reside in non-human appliances. For example, content may rest in a community, database or network (Siemens, 2004)
  • Learning is a process of connecting diverse nodes, knowledge sources, or accessing existing networks (Siemens, 2004)
  • Learning rests in the diversity of opinions and viewpoints within the connections of a network (Siemens, 2004)
  • Learning requires both knowledge consumption and creation (Siemens, n.d.)
  • Learning occurs in multiple ways. For example, email, blogs, online and offline conversations (Siemens, n.d.)

Necessity of Connectivism

Connectivism was developed by George Siemens due to the belief that current learning theories including Behaviourism, Cognitivism and Constructivism fail to address the nature of learning in the digital age. Knowledge no longer only resides within the mind of the individual, but is distributed across multiple networks enhanced by technology, where learning “occurs outside of people or within organizations” (Siemens, 2005). Previous theories were created in a time when “information development was slow” (Siemens, 2004), with a significantly large half-life, as compared to the digital era of today where the flow of information is fast, fluid, nebulous and brief in its accuracy and relevancy. Connectivism aims to address not only this knowledge explosion, but the way technology has changed the way that we “live, communicate and learn” (Siemens, 2005).


Debate exists surrounding the question, is Connectivism really a learning theory?

Professor Plon Verhagen in his 2006 critique Connectivism: a new learning theory? states that true learning theories deal with how learning occurs, where Connectivism focuses more on what is learned and why, making the work done by George Siemens a pedagogical viewpoint, not a learning theory. (Verhagen, 2006) [5].

Professor Verhagen further expands his critique on Connectivism by pointing out the following issues:

  • The introduction of a new approach to learning is not justified, as the main elements of Connectivism can be found within pre-existing learning theories
  • Learning theories should explain phenomena, and those explanations should be verifiable, neither of which Connectivism provides sufficiently nor coherently
  • Accepting that “learning may reside in non-human appliances” requires a fundamental alteration of the definition “learning”, which would make this term meaningless

Other academics feel that Connectivism does not exhibit the following traits for a well-constructed learning theory (Gredler, 2005):

  • Clear assumptions and beliefs about the object of the theory
  • Key terms are clearly defined
  • Development of principles from assumptions
  • Explanation of “underlying psychological dynamics of events related to learning”

Rebuttal from Siemens:

In Connectivism: Learning Theory or Pastime for the Self-Amused [6], Siemens responds to his critics and maintains that Connectivism is a learning theory, due to the following reasons:

  • Traditional learning theories are unable to sufficiently handle the dramatic changes occurring in knowledge, society and technology, forcing new theories to be explored
  • Elements of technology allow for the externalization of thoughts, believed to be an important element in knowledge construction
  • Technology has altered human communication, changing the flow of information, resulting in alterations in learning
  • Learning should not be viewed as an event or knowledge acquisition, but a process that involves cognition, memory, emotions, beliefs, and perceptions

Siemens provides further support for Connectivism by answering the “five definitive questions … to distinguish learning theory” (Ertmer, 1993)

  • How does learning occur? - Distributed within a network, social, technologically enhanced, recognizing and interpreting patterns
  • What factors influence learning? - Diversity of network
  • What is the role of memory? - Adaptive patterns, representative of current state, existing in networks
  • How does transfer occur? - Connecting to (adding) nodes
  • What types of learning are best explained by this theory? - Complex learning, rapid changing core, diverse knowledge sources

For a further comparison and analysis of Connectivism as a learning theory, please review the chart provided by Tim Ireland (MET Student) in his Wiki, Situating Connectivism

Instructional Use

Connectivism promotes the acquisition of the most relevant and factual information through accessing multiple “networks”. Connectivism also recognizes that the ability to sort and prioritize the tremendous amount of online information according to its accuracy and relevancy is a difficult skill to master. To help facilitate this process, educators and students must access various online tools for website evaluation:

Other benefits of Connectivism within a learning environment for individuals include:

  • The ability to access the newest information altering the foundations for future study (Siemens, 2006)
  • Learning to connect with information, rather than rote memorization of basic facts (Siemens, 2006)
  • Learn by connecting to information that is available within a network, then build upon this information to form new knowledge, then share it back into the network for others to access
  • Access and use the most accurate information on a topic, making lessons/projects more relevant

Direct Considerations for Teachers:

  • Allow students to use multiple technological devices that are able to connect to the Internet
  • Continually instruct students in the critical evaluation of web based content
  • Model and provide instruction on accessing, and sharing information within multiple networks
  • Create connections with other students, classes, or schools to facilitate the sharing of information through networks

Implications to Learning Environments

When designing a learning environment based on Connectivism, the following elements should be included:

  • Multiple access points to various networks for information creation, storing, sharing, and retrieval
  • Model the use of current information to provide real-world examples of knowledge and thinking in a continual state of flux
  • Scaffold activities to provide necessary skill development to aid in the sorting of information, which will allow for decisions to be made on the importance of information
  • Incorporation of on-line social networking tools to facilitate the flow and exchange of information within a network, pushing the boundaries of individual and group learning similar to Vygotsky's Zone of Proximal Development

To further understand the implications of Connectivism on educational environments and student learning, please watch the following video:

{{#ev:youtube|XwM4ieFOotA}} (Drexler, 2008)[7]

Implementation in Learning Environments

In 2008, George Siemens and Stephen Downes through the Learning Technologies Centre and Extended Education at the University of Manitoba presented Connectivism and Connective Knowledge the “first course explicitly designed according to the principles of Connectivism” (Downes, 2008) [8]. This first offering was described as a “Massive Open Online Course” (MOOC), with over 2200 registered and unregistered global participants. Content for this course was decentralized through various Web 2.0 and Open Source applications. Subsequent offerings of Connectivism and Connective Knowledge have occurred in 2009, and 2011. In 2010, George Siemens, Stephen Downes, Dave Cormier, and Rita Kop facilitated a new course Connectivism & Constructivism, furthering previous work on Connectivism.

See Also

Connectivism: Teaching and Learning

Vygotsky’s Zone of Proximal Development

Learning Theory

Digital Divide

Chaos Theory

Network Theory

Complexity Theory



Drexler, W. (2008, November 26). Networked Student [Video file]. Retrieved from

Downes, S. (2008). Placed to go: Connectivism & Connective Knowledge. Innovate 5 (1). Retrieved from

Downes S. (2006). Learning networks and connective knowledge. Retrieved November 17, 2016:

Dunaway, M.K. (2011). Connectivism, Reference Services Review, 39(4): 675-685. DOI:

Ertmer, P. A., Newby, T. J. (1993). Behaviorism, cognitivism, constructivism: Comparing critical features from an instructional design perspective. Performance Improvement Quarterly, 6 (4), 50-70.

Gredler, M. E. (2005). Learning and instruction: Theory into practice (5th ed.). Upper Saddle River, NJ: Pearson Education

Goldie, J.G.S. (2016). Connectivism: A knowledge learning theory for the digital age?, Medical Teacher, 38:10, 1064-1069, DOI: 10.3109/0142159X.2016.1173661.

Gonzalez, C. (2004). The role of blended learning in the world of technology. Retrieved from

Siemens, G. (n.d.). About: description of connectivism. Retrieved from

Siemens, G. (2004). Connectivism: A Learning Theory for the Digital Age. Retrieved from

Siemens, G. (2005). Connectivism: Learning as network-creation. American Society for Training & Development. Retrieved from

Siemens, G. (2006). Connectivism – Learning Theory or Pastime for the Self-Amused? Retrieved from

Verhagen, P. (2006). Connectivism: A new learning theory? Retrieved from