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George Siemens, September 12, 2009


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)


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






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, context of occurrence 

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 and growing the network (social/conceptual/biological)

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

The notion of a “new” theory for learning based on network structures, complex changing environments, and distributed cognition has drawn criticism. Pløn Verhagen (2006), in his critique of connectivism(.pdf), specifically argues for the ineffectiveness of a theory based on “unsubstantiated philosophising” ( 14). Bill Kerr (2007) postulates that connectivism is an unnecessary theory, for in his opinion, existing theories satisfactorily address the needs of learning in today’s technologically, connected age. Curtis Bonk (personal communication, September 11, 2007) questions whether connectivism is best seen as a learning theory in the traditional sense—“psycholog[ical] learning theory lineage”—or belongs in a sociological, or anthropological, conception of learning. 


Yet despite detractors, proponents of connectivism, and more generally networked learning, are exploring a model of learning that reflects the network-like structure evident in online interactions—as evidenced by University of Manitoba’s 2007 Online Connectivism Conference attendance and discussion, the level of interest in Connectivism and Connective Knowledge 2008, well as the multiple conferences and research centres focused on networked learning. An argument appealing to popularity, however, is not a real basis for declaring something a “new learning theory.


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 knew 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 cope? 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. I hesitate 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 – form 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.

  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.


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