Learning and Knowing in Networks: Changing roles for Educators and Designers

George Siemens

In my personal opinion, Driscoll and Siemens’ article did a fantastic job illuminating the path we have been and will be on in education.  They re-addressed the learning theories and gave an excellent synopsis of where education has been and is now with the immersion of the digital age. 

Driscoll posits these learning theories are: Behaviourism, which asserts that learning is a “black box” activity, in that we do not know what occurs inside the learner, focuses its efforts on managing external, observable behaviours, and finds much of its existence in objectivism;  Cognitivism, which spans a continuum from learning as information processing (a computer model) at one end, to learning as reasoning and thinking on the other, finds much of its identity in pragmatism; Constructivism, which covers a broad spectrum of research overlapping with cognitivism, contends that learning involves each individual learner making sense and constructing knowledge within his or her own context; it finds its foundation in interpretivism (2005).  Also, they provided a chart in order to better understand the critical elements of these theories (Appendix A).

Another critical aspect of the article was the critique of the infrastructure of education.  Siemens postulated that, “a growing disconnect in the tools and methods of classroom activity and those of youth culture and larger society is evident” (2008, pg 7).  Also, Siemens hypothesized that even though we are ready for a new era, our schools and the schools infrastructure may not be.  It may have to evolve into another era.  I concur with this postulation because it is occurring at the school at which I am currently working.  Coahulla Creek is the new innovative high school in my county.  We were not allowed to bring anything with us.  If we did, the only thing we could bring was flash drives.  There are no filing cabinets, no text books, and no library books.  Everything is provided to welcome in the digital age.  However, we are struggling because it seems we cannot keep up with the innovations.  Siemens asserted this would occur by his research.  He states,

“The rapid growth of knowledge and information adds increasing complexity to the growth of technology in learning. A number of studies (Friedlander, 2003; Gantz et al., 2007; University of California at Berkeley, 2003) indicate information growth is exceeding the capacity of both people and organizations to manage and make sense of the abundance. Boyack (2004), for instance, states that increase information growth has led to dilution and set in motion the requirement for new ways of sifting an managing information (p. 5192). While reports vary dramatically about the pace global information growth, individuals and organizations alike are faced with the challenge of staying informed in climates of extreme change. The change pressures within society (millennial learners, information growth, advancing technologies) are increasingly being confronted within education, suggesting the need for research on tools and required educational approaches in order to meet learners’ needs” (2008).

As one can see, we are indeed in the digital age and need to accommodate our learners to it, but there is a lot of change that must take place.  Another article to support their concept is “MUVEs and Experiential Learning: Some Examples” by Baba Kofi Weusijana, Vanessa Svihla, Drue Gawel, and John Bransford.  This article deals with the same topics as Siemens. Its web address is http://www.innovateonline.info/pdf/vol5_issue5/MUVEs_and_Experiential_Learning-__Some_Examples.pdf

These articles not only aided in my understanding of the learning theories, but also enabled me to see where we are in education.

References:

Driscoll, M. (2005). Psychology of learning for instruction (Third ed.). Boston, MA: Allyn and Bacon.

Siemens, G. (2008, January 27). Learning and knowing in networks: Changing roles for educators and designers/. Retrieved 09/08/2011, from http://it.coe.uga.edu/itforum/paper105/siemens.pdf

    Appendix A

 Table 1: Learning Theories

Property	Behaviourism	Cognitivism	Constructivism	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
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”	Socialization	Connecting to (adding) nodes
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