This is going to be one of those blog posts where, to borrow from Joan Didion, “I write entirely to find out what I’m thinking.” After reading David Kolb’s (1984) theory of experiential learning and George Siemens’s (2005) theory of connectivism, I can see there are overlaps, but I don’t have a cohesive argument as to how they fit together. Here are some thoughts on their commonalities and relative merits.
Both Kolb and Siemens distinguish their theories from traditional learning theories.
Both authors draw extensively on prior literature but frame their arguments as a departure from established behavioral and cognitive theories of learning.
Kolb writes that the emphasis on “the central role that experience plays in the learning” differentiates it from “rationalist and other cognitive theories of learning that tend to give primary emphasis to acquisition, manipulation, and recall of abstract symbols, and from behavioral learning theories that deny any role for consciousness and subjective experience in the learning process” (p. 20).
Siemens argues that traditional theories of learning fail to account for learning that occurs outside the individual, such as “learning that is stored and manipulated by technology” and learning that occurs in organizations.
Both Kolb and Siemens emphasize process over content.
For Kolb, the emphasis on process is inevitable, for, as he writes, “No two thoughts are ever the same, since experience always intervenes” (p. 26). Learning in that sense is never purely about knowledge acquisition but about continually remodeling one’s understanding of the world; “all learning is relearning” (p. 28).
Similarly, Siemens writes, “The pipe is more important than the content of the pipe. Our ability to learn what we need for tomorrow is more important than what we know today.” Pieces of knowledge are less important than the ability to draw connections between them.
Siemens explicitly grapples with the role of technology in learning.
For Siemens, the rapid evolution of technology calls for a new theory of learning, particularly because “technology performs many of the cognitive operations previously performed by learners.” He emphasizes too that “learning may reside in non-human appliances.”
This is a provocative argument but (in my humble opinion) not fully integrated into the rest of his theory, or not as novel as he makes it out to be. Before we had databases, we had books (and people—Siemens himself cites an unknown source as saying “I store my knowledge in my friends”). While analog information retrieval was much more time-consuming, the process was not fundamentally different from that of querying a database. Knowledge has always resided outside the individual as well as within.
Kolb does not explicitly address technology as an adjunct to human cognition, but as far as I can tell, there is nothing in his theory that precludes technology from playing a role in experience and testing of new concepts.
Kolb articulates a more complete theory of learning.
Patricia Miller (2002) describes several criteria by which a theory can be judged: “A theory should be logically sound, that is, internally consistent, with no statements that contradict each other. A theory should also be empirically sound, that is, not contradicted by scientific observations. Furthermore, it should be clear, testable, and parsimonious, relying on as few constructs, propositions, and the like as possible. Finally, a theory should cover a reasonably large area of science and should integrate previous research” (p. 5).
By these criteria, Kolb’s experiential learning theory is more complete than Siemens’s theory of connectivism. Kolb draws on three previously articulated learning models (by Lewin, Dewey, and Piaget) to articulate a cycle of learning with four distinct stages: concrete experience, reflective observation, abstract conceptualization, and active experimentation. The propositions he makes about learning are all closely tied to this model (e.g., “Learning is a continuous process grounded in experience”).
Siemens, meanwhile, draws on wide-ranging theories (chaos, network, complexity, self-organization) and puts forth eight principles that are not without contradictions. Learning is described as a process but also treated as an object that may reside in appliances. Siemens then writes that knowledge may reside in a database but be converted to learning by human actors. The slippage in terminology here suggests that connectivism has not fully reached the level of a complete theory.
Furthermore, Siemens’s argument that “learning and knowledge rests in a diversity of opinions” is not well substantiated by the preceding arguments. Broad networks are described as important, but this is the only place where opinion is mentioned.
Closing thoughts
Kolb and Siemens both argue for a learning process that is complex and meets the moment at hand. Siemens is writing at a time closer to our current moment (2005 versus 1984) and so is able to speak more directly to the rapid rate of knowledge development and the ability we have now to offload basic cognitive tasks to technological implements. However, both Kolb and Siemens describe learning as a lifelong and constant process, and not always one that is rooted in formal schooling. In that sense, learning is open to everyone, and technology mainly serves to make learning opportunities more democratic.
