Recent Work in Connectivism
Stephen Downes, Mar 04, 2019, LAK19, Phoenix, Arizona, via Zoom
In this presentation I look at how connectivism is being applied and understood in current literature. I look at connectivism as pedagogy, connectivism as a learning theory, some successes of connectivist methods, and look at connectivism from a wider perspective. Please see this Google Doc for full notes and references.
The proposition advanced in this paper is that since connectivism draws on a number of precedent concepts, which are listed by the authors, it follows that connectivism should be seen as a new theory of learning. "This theoretical approach means an evolution from the existing theoretical knowledge instead of a real theoretical revolution, as it was stated in the initial thesis," write the authors. But there's a difference between drawing on previous theories, including the adoption of their explanatory framework, and drawing on them and offering a new explanation for what came before. I thing connectivism does the latter, and in so doing causes us to look at old phenomena in new ways.
This paper compares a connectivist instructional method with a communicative language teaching (CLT) method in the teaching of English and concludes that the "connectivism instructional method provide unique opportunities for increasing the self-efficacy and task value of students by increasing social intractions and diversity for choosing tasks." This isn't a result of the type 'treatment X improved test score Y' but I do think that it points to one of the wider values of a connectivist approach. The same authors expand on their findings in this article as well.
The question posed here is how students draw links between different learning resources. "Connectivism has yet to recognize how learners form connections to the variety of resources," writes the author. "An often-overlooked stage in the process of forming connections is the evaluation stage. This kind of self-awareness of actions helps the learners judge the value of the node and redirect their learning path."
Does Artificial Neural Network support Connectivism’s assumptions?
Does Artificial Neural Network support Connectivism’s assumptions?, International Journal of Instructional Technology and Distance Learning, 2019/03/04
The answer to the question posed in the title is "yes, mostly" (and I would quibble with the places where the paper says they don't mesh) but the real value of the paper is a step-by-step examination of different types of neural networks used in machine learning and (especially) deep learning. "the only hope is to use unsupervised learning model in which a learner should extract the pattern from given examples without explicit feedback. The repetition and relative similarity between objects in given examples may help a learner to cluster and combine different ideas together to come up with new object. And that is where connectivist's theory lies."
This newsletter is sent only at the request of subscribers. If you would like to unsubscribe, Click here.
Know a friend who might enjoy this newsletter? Feel free to forward OLDaily to your colleagues. If you received this issue from a friend and would like a free subscription of your own, you can join our mailing list. Click here to subscribe.
Copyright 2019 Stephen Downes Contact: firstname.lastname@example.orgThis work is licensed under a Creative Commons License.