Annotated Bibliography 5
Siemens, G. (2005). Connectivism: A Learning Theory for the Digital Age. International Journal of Instructional Technology and Distance Learning, 2(1), 3-9.
In this seminal 2005 paper, which has 3,848 citations to date, George Siemens begins by making the case for a new learning theory. He argues that behaviorism, cognitivism, and constructivism, that were developed before computers, are no longer adequate as they don’t reflect the underlying social environment. He draws on a paper on blended learning to provide evidence that knowledge is increasing exponentially, and also that the time taken for knowledge to become obsolete is getting shorter. He refers to the latter as the “shrinking half life” of knowledge and claims that this presents new challenges for teaching and learning. (Gonzalez, 2004).
Siemens explores the three main learning theories: behaviourism, cognitivism, and constructivism and the three epistemological traditions to which they are linked: objectivism, pragmatism and interpretivism. (Driscoll, 2000). He uses five references to the literature during this background exploration but perhaps refers too often (three citations out of five) to Marcy P. Driscoll. The author argues that in all of the main learning theories, learning occurs inside the person. He points out that these theories don’t attempt to explain organisational learning or machine learning. Bob Dylan warned of “…your useless and pointless knowledge” in his classic 1965 album Highway 61 Revisited, (Dylan, 1965). Exactly forty years later, Siemens attests that “…the need to evaluate the worthiness of learning something is a meta-skill that is applied before learning itself begins.” (Siemens, 2005, p.5).
The path to connectivism, along which Siemens brings the reader, is often less than smooth. The section where he argues for the inclusion of chaos, in the fabric of learning theories, could be cognitively challenging for some readers. He defines chaos as “a cryptic form of order” and believes that the learner’s challenge is to recognise these hidden patterns. (ScienceWeek, 2004). Later in his paper, the reason for Siemens allusion to chaos theory becomes somewhat apparent. He appears to be drawing a parallel between the ability to form connections between sources of information to create useful information patterns, and the hidden pattern within chaos. This reviewer notes that this skill is not unlike that required for data mining. Phil and Kamber (2011, p.8) describe data mining as “…an essential process where intelligent methods are applied to extract data patterns”.
Siemens uses a computer network metaphor when he writes about nodes and connections. He suggests that the nodes can be fields or communities, and that when nodes gain recognition for being experts, they attract more connections. The author refers to the cross-pollination of learning communities and the value of making connections between disparate fields to create new innovations.
At this juncture, Siemens hardly refers to the literature and makes the case from here until the end of the paper for his own theory, connectivism. He outlines his eight principles of connectivism. One of these is that the capacity to know more is more critical than what is currently known. This is essentially a different word formulation for the proverb “give a man a fish and you feed him for a day; teach a man to fish and you feed him for a lifetime”. Two of the principles could be merged into the single principle that learning is a process of connecting specialised nodes and maintaining these connections to facilitate continual learning. The principle that learning may reside in non-human appliances appears to be borrowed from the field of artificial intelligence. Siemens takes some time to make an articulate and passionate argument for the importance of knowledge management and information flow within organisations. The essence of his theory is that connectivism is the “…amplification of learning, knowledge and understanding through the extension of a personal network.”
Siemens argues that connectivism has implications for management and leadership, media and news, personal knowledge management and the design of learning environments. As knowledge continues to grow, Siemens places a higher value on access to knowledge than knowledge the learner currently possesses. The author concludes that connectivism presents a model of learning which is no longer an individualistic activity.
Driscoll, M. (2000). Psychology of Learning for Instruction. Needham Heights, MA, Allyn & Bacon
Dylan, B. (1965). Tombstone Blues. Retrieved November 28, 2016, from http://bobdylan.com/songs/tombstone-blues/
Gonzalez, C., (2004). The Role of Blended Learning in the World of Technology. Retrieved December 10, 2004, from http://www.unt.edu/benchmarks/archives/2004/september04/eis.htm.
Han, J., Pei, J., & Kamber, M. (2011). Data mining: concepts and techniques. Elsevier.
ScienceWeek (2004) Mathematics: Catastrophe Theory, Strange Attractors, Chaos. Retrieved December 10, 2004, from http://scienceweek.com/2003/sc031226-2.htm.