This blog post relates to my study of CCK11, and is my submission for assignment 1 – my position on Connectivism. As the word-limit is quite low, I’ve linked to previous blog posts which provide greater depth of discussion and links supporting my assertions.
Clarify and state your position on connectivism
I was very excited to be doing this course. I was introduced to Connectivism in my instructional design course as part of my program with UManitoba back in 2009. At that time, I was unsure about Connectivism and wanted to learn more before forming an opinion on its validity as a learning theory.
My current role with my employer is an instructional designer. My current value system for learning theories centres mostly on usefulness. At this stage, I’m not convinced of its usefulness in terms of underpinning a learning design. This isn’t to say that its not useful, I just haven’t enough experience with it to say that it is. So I’m saddened to say that after 5 weeks studying Connectivism, I’m still largely a fence-sitter. Hope this is okay George. 🙂
For me, I don’t think of learning theories in absolutes. My view is that each learning theory is valid and useful, for given contexts. I have blogged extensively on this view over the past couple of years, increasingly so in the past weeks. I found a real nugget in a video by Ian Robertson that provided concrete examples to illustrate my view about context and learning theories. In this blog post, I reflected on what I thought were the right (and wrong) contexts for Connectivism where a primary factor (at this point) is technological accessibility where making connections is not so easy. This is based on the importance George has placed on technological advancement as a primary driver for considering a new theory for learning. Another significant factor is the discipline or focus of the learning, which I consider a weakness of the theory and discuss in greater detail later in this article.
Is it a new theory of learning?
For me at this stage, the stand-out elements of Connectivism that are novel are:
- Learning may reside in non-human appliances
- How can we continue to stay current in a rapidly evolving information ecology?
- Currency is the intent of all connectivist learning activities
- Decision-making is itself a learning process
- Capacity to know more is more critical than what is currently known
- How do learning theories address moments where performance is needed in the absence of complete understanding?
These aspects are the ones that resonate most with my life experiences as a learner. However, these experiences have been very natural and organic. This course as a MOOC is pseudo-organic. Everybody has assembled to learn about Connectivism, but the learning is driven by a daily email digest, not purely by one’s own curiosity or need to solve a problem. My reflections on this MOOC are detailed in a separate blog post.
Returning to the stand-out principles for me, I’d like to unpack these a little more…
Learning may reside in non-human appliances
For most of my adult life, I have been using computers to organise my learning. It has become an integral part of how I learn. Whether it be storing information, finding information, reflecting on ideas, sharing ideas, feedback and so on. For many years, I rarely bother to commit to memory knowledge – I have honed my skills in being able to find it when and where I need it. If I need to remember the switches to a UNIX command, I access the online manual (using the man command). If I want to recall my previous thoughts on a topic, I refer to my blog. If I need to follow a policy for a task at work, I search the policy portal. The technology becomes an extension of my learning. It’s more about learning to learn and self-sufficiency. I recall George commenting that he would be lost if he were to lose the information on his computers, because it has become a fundamental element of how he learns. I hope I have paraphrased that correctly George. 🙂 I feel exactly the same way.
How can we continue to stay current in a rapidly evolving information ecology?
I have been working in the IT and education industries for 15 years. Both are very evolutionary and constantly changing. From the beginning of my working career, I have had to develop strategies for this challenge.
Currency is the intent of all connectivist learning activities
This links to the previous paragraph – it’s all about remaining current in an evolutionary environment. How can I systemically remain current in a rapidly changing environment.
Decision-making is itself a learning process
Again, this links to the previous paragraph. Deciding what to learn and how deep to learn it is a critical factor in an age of information abundance. Is what I learn today going to be applicable in the near future? You need to constantly reflect upon what you believe to know – challenge previously held assumptions in the light of perpetual change. This too has linkages with Dave Snowden’s view that we are pattern-matching intelligences, rather than information processing intelligences.
Capacity to know more is more critical than what is currently known
Again, a symptom of evolving contexts and related to decision-making. What has worked in the past may no longer work due to changing context.
How do learning theories address moments where performance is needed in the absence of complete understanding?
This I can identify with again and again. There are very few tasks or projects that I have worked on where I have known all that I need to produce a satisfactory output. In my work history, there is very little repetitiveness – almost every day is a new challenge requiring me to develop new skills, ideas, ways of seeing the world. I can only see this trend continuing.
What are the weaknesses of connectivism as formulated in this course?
Like all existing learning theories, their application is contextual. I don’t think George considers Connectivism to be the silver-bullet of learning theories, and really its not. Its just a theory that incorporates the information era of the 21st century and responds to the challenges of learning in this era, plus leverages the affordances of the technology of the time – global interconnectedness.
At times I wonder whether the discipline or topic area suits this style of learning design more so than another. Suifaijohnmak has written an article where he says:
… under a networked learning approach, where diversity of opinions are welcome in a MOOC, then tensions amongst different “voices” seem to be a natural emergence from the networks … This seems to be a natural opposite from the traditional “group” or “team”, or even the Community’s views where consensus and agreed goals are the norms rather than exception.
How do we know if diversity of opinions is the best way to learn under a networked learning ecology (or with internet)?
How do we know if diversity of opinions is the best way to learn full-stop? Does learning and knowledge [always] rest in diversity of opinions? Especially when you consider the traditional working environment is more about groups and teams working towards agreed goals. Again, it depends on context. Are we discussing facts or ideas, for instance.
What are your outstanding questions?
Continuing from the previous section, I’m curious as to what a connectivist learning design would look like for a course teaching a more hardened science, such as physics, chemistry or computer science. I have asked George this question in an Elluminate session, but his response at least for me did not solve my dilemma – how do I apply this theory to more diverse contexts? Learning isn’t always about sharing opinions. Many of these disciplines are objective – a solution is either right or wrong. The value of opinion (in my opinion) is significantly lower than in topical areas that are more culturally influenced, such as education – softer sciences if I may, just as an example.