Connectivism: Informing Distance Education Theory, Pedagogy and Research

(Critical Review)

George Siemens’ (2005) article “Connectivism: A Learning Theory for the Digital Age” has sparked both innovation and controversy. In stark contrast to Clark’s (1983) analogy that the truck delivering our groceries does not impact our nutrition, “only the content of the vehicle can influence achievement” (Clark, 1983, p. 445), Siemens suggests in the current knowledge economy “the pipe is more important than the content in the pipe” (Siemens, 2005, p.6). As the article unfolds, however, a more apt rendering may be that connectivism repositions media as a type of content, in that media, as tools of cognitive engagement, have the potential to transform the content of learning.

The editor’s note accompanying Siemens’ publication describes it as a “milestone article”. From a theoretical standpoint, connectivism is important because it integrates existing learning theories (Ally 2004) – namely, behaviourism, cognitivism and constructivism – and provides a framework for pedagogy that is responsive to evolving technology and its incorporation in distance education. The impetus for developing new pedagogy, according to Siemens, is that these existing learning theories were formulated before technology “reorganized how we live, how we communicate, and how we learn” (Siemens, 2005, p. 1), and do not encompass types of learning relevant for the digital age.

Connectivism deals with learning – actionable knowledge – that involves developing meta skills for delineating patterns and connections within a mass of technology-mediated knowledge that is rapidly changing/increasing and only tenuously under the learner’s control; evaluating the value of content (i.e. whether information/knowledge is worth being learned); and determining when and what knowledge should be retired and replaced with updated knowledge (the meta skill of unlearning obsolete knowledge) (Siemens, 2005). [Siemens provides Gonzales’ (2004) definition of knowledge half-life – the interval between the time knowledge is acquired and the time it becomes obsolete – to describe the changing nature/character of knowledge in the digital age.] Additionally, connectivism describes and accounts for new types of knowledge, such as the Semantic Web as well as collective/collaborative learning and knowledge production (Siemens, 2005; Anderson, 2004). Ally (2004) suggests a connectivist framework has the potential to inform instructional design for both machines and humans and for how these agents interact.

Siemens is careful to establish theoretical links between connectivism and these earlier learning theories. Referencing Driscoll (2000), Siemens describes that in behaviourism and cognitivism knowledge is external to the learner, and in constructivism knowledge is created as the individual creates meaning from external, complex experiences and that learning is often personalized. In describing connectivism, Siemens draws on the systems concepts of nodes and networks, invoking similar concepts and the terminology used in cognitivism to describe information processing; constructivism’s concepts of learner-centred learning and instructor-as-facilitator (Ally, 2004; Duffy & Cunningham, 1996); and behaviourism’s community-centred social cognition.(Anderson, 2004; Vygotsky, 1978).

However, Siemens effectively grounds connectivism in chaos theory, complexity and self-organization theory, and network theory (networks, small worlds, weak ties), referencing Rocha (1998), Wiley & Edwards (2002) and Barabàsi (2002), respectively. He identifies eight principles of connectivism[1], describing the individual (node) <-> network <-> organization relationship and the embedded learning processes, opportunities for networked scaffolding (Anderson, 2004), and vital meta skills (described above).

As a theory, connectivism has the potential to generate testable hypotheses and provide a mandate for research, to inform emerging pedagogy, and to provide a framework for instructional strategies and learning environments that are “simultaneously learner-centred, content-centred, community-centred, and assessment-centred” (Anderson 2004, p. 67). This is true for education in general, and for distance education in particular. Because of its general distance-based delivery model and widespread incorporation of technology applications, distance education is uniquely positioned to incorporate the enriched, connected, networked learning that connectivism envisions.

The individual, and his/her abilities to create a personal learning network, is the “starting point of connectivism” (Siemens, 2005, p. 6). Anderson (2004) and Cobb (1997) describe that instructional design that places media in the hands of the learner makes learning more constructive. In distance education, technology-mediated learning may provide for richer learning experiences than those facilitated in traditional classroom instruction. For instance, constructivist learning is facilitated by learners creating their own learning paths through content via hyperlinks (Anderson, 2004). Consistent with Perraton (1988), connectivism renders the role of teacher to that of facilitator, though Perraton specifies this occurs when rich media (such as videoconferencing that facilitates face-to-face communication) transforms the relationship (Simonson, Smaldino, Albright & Zvacek, 2012). In connectivism, the teacher/facilitator aids the learner in developing meta skills for creating connections and evaluating knowledge/information.

Connectivism’s focus on a learner-centred approach mirrors trends in distance education research, especially research examining the impact of interaction patterns, not just achievement, on the learning environment (Simonson, Smaldino, Albright & Zvacek, 2012). In terms of research rigour, learning assessment that evaluates the acquisition of meta skills, instead of or in addition to achievement in terms of content knowledge, is applicable across learning environments (distance education and classroom instruction), with the potential to yield more valid inter-group comparisons because effect sizes would likely be less variable.

The networked learning environment envisioned by connectivism similarly resonates with post-Fordist theory in distance education and with open learning theory, both of which describe the personalization of learning, distributed networks, decentralization of delivery and curriculum development with the flexibility to respond to local and individual needs and priorities rather than focusing on mass production and mass consumption (Simonson, Smaldino, Albright & Zvacek, 2012; Edwards, 1995).

However, while interaction and collaboration are essential in connectivism and developing the meta skills connectivism espouses, they may not be (as) critical in distance education (though research demonstrating this focused on learners’ perceptions rather than achievements) (Simonson, Smaldino, Albright & Zvacek, 2012). Anderson (2004) describes how these restrict learner independence traditionally associated with distance learning. For example, synchronous videoconferencing at minimum imposes specific time commitments. The implication for instructional design is to ensure a complementary balance (Anderson, 2004), in line with connectivism’s two-way, networked learning environment.

Siemens lays out a clear blueprint for connectivism, grounding it theoretically and providing relevant evidence, with one obvious exception. In the article’s introduction, Siemens lists contemporary learning trends to which connectivism responds, but provides no references. In particular, Siemens states the use of technology tools is altering our brains and reshaping the way we learn. It is reasonable to assume he is referring to technologies such as the Semantic Web, since he later in the article discusses technologies undertaking cognitive processes previously carried out by learners (Siemens, 2005; Anderson, 2004). However, a clearer link between these two points may have strengthened the article.

References

Ally, M. (2004). Foundations of educational theory for online learning. In T. Anderson & F. Elloumi (Eds.), Theory and practice of online learning (pp. 15-44). Athabasca, Canada:  Athabasca University.

Anderson, T. (2004). Towards a theory of online learning. In T. Anderson & F. Elloumi (Eds.),  Theory and practice of online learning (pp. 45-74). Athabasca, Canada: Athabasca University.

Anderson, T. (2009). A rose by any other name: Still distance education-A response to D.R. Garrison: Implications of online and blended learning for the conceptual development and practice of distance education. Journal of Distance Education (Online), 23(3), 111-116. Retrieved from http://0-search.proquest.com.aupac.lib.athabascau.ca/docview/868262401?accountid=8408

Barabàsi, A. L. (2002). Linked: The new science of networks. Cambrige, MA: Perseus Publishing.

Bell, F. (2011). Connectivism: Its place in theory-informed research and innovation in technology-enabled learning. International Review Of Research In Open And Distance Learning, 12(3), 98-118. Retrieved from http://files.eric.ed.gov/fulltext/EJ920745.pdf

Bernard, R. M., Abrami, P. C., Lou, Y., Borokhovski, E., Wade, A., Wozney, L., …Huang, B. (2004). How does distance education compare with classroom instruction? A meta-analysis of the empirical literature. Review of Educational Research, 74(3), 379-439. doi: 10.3102/00346543074003379

Clark, R. (1983). Reconsidering research on learning from media. Review of Educational Research, 53(4), 445-459. Retrieved from             http://www.uky.edu/~gmswan3/609/Clark_1983.pdf

Cobb, T. (1997). Cognitive efficiency: Toward a revised theory of media. Educational Technology Research and Development, 45(4), 21-35. Retrieved from http://www.medvet.umontreal.ca/techno/eta6785/articles/Cognitive_efficiency_media.PDF

Driscoll, M. (2000). Psychology of learning for instruction. Needham Heights, MA: Allyn & Bacon.

Duffy, T. M., & Cunningham, D. J. (1996). Constructivism: Implications for the design and delivery of instruction. In D. H. Jonassen (Ed.), Handbook of research for educational communications and technology (pp. 170-198). New York: Simon & Schuster             Macmillan.

Edwards, R. (1995). Different discourses, discourses of difference: Globalisation, distance education, and open learning. Distance Education, 16(2), 217-255. doi: 10.1080/0158791950160206

Garrison, R. (2009). Implications of online learning for the conceptual development and practice of distance education. Journal of Distance Education (Online), 23(2), 93-103. Retrieved from http://0-search.proquest.com.aupac.lib.athabascau.ca/docview/867413127?accountid=8408

Gonzales, C. (2004). The role of blended learning in the world of technology. Retrieved from             http://www.unt.edu/benchmarks/archives/2004/september04/eis.htm

Perraton, H. (1988). A theory for distance education. In D. Stewart, D. Keegan, & B. Holmberg (Eds.), Distance education: International perspectives (pp. 34-45). New York: Routledge.

Simonson, M., Smaldino, S., Albright, M., & Zvacek, S. (2012). Teaching and learning at a distance: Foundations of distance education (5th edition). Boston, MA: Pearson.

Kop, R., & Hill, A. (2008). Connectivism: Learning theory of the future or vestige of the past?. International Review Of Research In Open & Distance Learning, 9(3), 1-13. Retrieved from http://files.eric.ed.gov/fulltext/EJ815759.pdf

Rocha, L. M. (1998). Selected self-organization and the semiotics of evolutionary systems. Retrieved from http://informatics.indiana.edu/rocha/ises.html

Vygotsky, L. (2002). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.

Wiley, D. A., and Edwards, E. K. (2002). Online self-organizing social systems: The decentralized future of online learning. Retrieved from  http://opencontent.org/docs/ososs.pdf

Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1). Retrieved from http://www.itdl.org/Journal/Jan_05/article01.htm

Footnote:

[1]“Learning and knowledge rests in 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, 2005, p. 5)

 

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