Does connectivism facilitiate surface learning?

This blog post relates to my study of CCK11, and is inspired by a blog post from a fellow classmate, Skip titled Are we dumbing down? Is multitasking taking away of our ability our ability [sic] to absorb?

While Skip I believe is referring to the distraction of back-channels during an online live web-conference when his refers to multi-tasking and inability to absorb, its his use of the word absorb that I am focused on.  Absorb in the context of surface versus deep learning.

Some suggest that surface learning should be avoided as it promotes memorisation and regurgitation – a lack of deep understanding of a concept or idea.

Yet George suggests in his article Connectivism:
A Learning Theory for the Digital Age
that today’s learning environment has changed considerably through technology, and amongst a range of questions relating to these changes, asks:

How do learning theories address moments where performance is needed in the absence of complete understanding?

Later in his article, he makes the point:

A real challenge for any learning theory is to actuate known knowledge at the point of application. When knowledge, however, is needed, but not known, the ability to plug into sources to meet the requirements becomes a vital skill.

So I take this to mean knowledge at point-of-need. With such a high-rate of change in modern times, it seems to me that this is a real change for 21st century workers.  Employees more and more will not intrinsically have the knowledge required to do some tasks and therefore rely on their connective network knowledge.  Is it necessary to always know the “ins and outs of a duck’s bum” to achieve your goals?

4 thoughts on “Does connectivism facilitiate surface learning?

Add yours

  1. Having JIT knowledge is very useful if you already know HOW to process said knowledge. Take for example the study of computer science and learning how to program with Java. Having knowledge of all possible classes in Java isn’t useful. You can always look that stuff up in the developer kit, you just need a “starter pack” in your brain for the most common things that you will always access. That, on the other hand, doesn’t mean that you can learn about algorithms in a JIT fashion. You need to have a schema in your brain about HOW to program algorithms, WHAT they do, HOW they do it and WHY they do it, in order to understand new algorithms that some colleague developed. Without knowing something about algorithms, you can’t just jump in and expect to be able to plug-n-play.

  2. “Employees more and more will not intrinsically have the knowledge required to do some tasks and therefore rely on their connective network knowledge.”

    This is so very true. Why? Spped of change. As one 20 so,mehting told me recently, by the time I get my BA half of what I was taught will be out of date. Bit of an exageration, but point made.

  3. Connectivism from what I have read takes network learning as including all learning. It seems to me you are right about the model being overtly apt at describing surface learning. Perhaps deep learning might be considered more complexly enmeshed knowledge with more connections?

    As to Skip’s question of “dumbing down” I do share some concern around it. I do a lot of work in digital video with students and it is a moving target with software and hardware constantly changing. I often have to learn something well enough to accomplish something and soon forget it. However, I have a store of deep knowledge about the principles involved in the software and hardware that improves my ability to connect ideas, find patterns, and use new surface knowledge effectively. I’m not even sure I consider the ephemeral surface information (how to interface a particular camera with software, for example) might not even be knowledge and seldom become “learning” if only used a couple of times before it is superseded.

    This area is near the core of where I am not sure I accept everything Connectivism is offering; I think I need to read a lot more before deciding, though.

    Thanks to you and Skip for writing on the subject,


  4. Damo, I think it comes down to context.

    For example, for a task like using Word. There’s no point in me learning “the ins and outs of Word”. It’s probably better to know that if I google “word 2008 hypen split line” I’ll find out that holding the Command key on a Mac and hitting the hypen key will insert a special non-breaking hyphen that solves my problem.

    On the other hand, if I’m a maths teacher in charge of a lesson with 30 14 year olds on a hot summer afternoon and their losing interest, I probably don’t want to have to rely on Googling the answer at the end of the lesson.

    I want the deep knowledge of pedagogy, content and the students that allows me to come up with an idea to re-gain their interest.

    Depending on the context you are in, there will be significant advantage to knowing the “ins and outs of a duck’s bum”. But there’s also advantages in “actuating unknown knowledge”.

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