I am delighted that my paper entitled “Re conceptualizing the role of tutors in research-based pedagogy: the tutor(s) as the curriculum” has been accepted for presentation.
(…) systems matter more than networks. Networks don’t exist in a vacuum. They exist and are shaped by the environments in which they exist. Networks are ephemeral. Systems exist to preserve. Systems exist as predictive agents. It’s hard to control people in networks – they have too much agency, they can do what they want. The lack of controlability makes it difficult to achieve intended outcomes in networks. When agents want a clear outcome, they turn to systems. Systems preserve power.
George Siemens, (2019). I was wrong about networks. Full article available here
Review covers literature for the period from 1996 to 2018: What are the benefits of networked learning communities for continuing professional development sharing and learning?
In the area of teacher professional development, research has shown that teacher networks add value for their development, the implementation of changes, leadership, and improved teaching practices. Four main themes emerged in response to the primary research question. These were:
- Enhanced social learning processes for CPD: learning communities help participants in this study to develop their competencies by sharing information and collaboration / helps to minimize the isolation that learners may have due to cultural, social or geographical reasons
- Greater use of formal and informal learning for CPD: Communication, collaboration and learning between individuals occurs both through formal and informal networks/ Yet, formal learning paths are rarely designed to meet the demands VLE teachers face in professional practice
- Learning across barriers in time and space for CPD: Networked learning communities provide a means for supporting the development of professional development learning communities across states and countries
- Increased levels of interaction for CPD: By cultivating interaction among CPD learners, networked learning communities support profound learning and greater levels of professional practice
Networked learning theory suggests that the real power of networked learning communities rests primarily in “collaborative inquiry that challenges thinking and practice” based on the richness of VLE teacher professional knowledge sharing and creation (Katz, Earl, & Jaffar, 2009, p.21) and that this type of collaborative inquiry rests on the strength of the relationships between the actors or nodes in the network (Church et al., 2002; Haythornwaite, & de Laat, 2010)
Full article available here
Sometimes, when we talk about learner independence, active learning or agency, we forget that this is not always for granted. Student consensus can not be considered a given. Trying out new things in a course (changing formats, layouts or mediums) produces changes that can be met with resistance and suspicion and it usually takes time until the cohort is convinced that what you are doing is actually working for them.
Student-Centered Learning and Student Buy-In article in Inside Higher Ed shows the results of curriculum change in a Biology course over a period of four years in relation to student satisfaction and acceptance. Pre- and post- course surveys show that student resistance decreased over the years and while grades did not change, the students’ perception of their gains has.
I remember that when we first introduced networked practices in an undergraduate design studio, students were terrified of the idea that their preliminary research and drawings would be published online for everyone to see. When talking about this, some expressed the fear that their ideas would loose their originality or that by the end of the semester everyone would converge to a single design idea/concept. Of course, none of this happened: in fact, it was quite revealing to see how diverse the research approaches and their respective representations actually were from a very early stage in the design process.
But there is also another interesting aspect in this article: the very fact that there was no single teacher but 13 of them. Now, I think this severely enhances the idea of a learning community. It’s not just about changing the format, it is about how you do it. By opening up the curriculum to more researchers and more teachers and by presenting the students with a course that is founded on a collaborative effort you ultimately denounce the idea of the expert and what comes along with that. And it is not by chance that grades have nothing to do with this. The very act of learning and being part of a learning community luckily can never fall into the hands of assessment.
For a thorough analysis on each one, please visit full article here
Trees start from a root node and might connect to other nodes, which means that could contain subtrees within them. Trees are defined by a certain set of rules: one root node may or may not connect to others, but ultimately, it all stems from one specific place. The tree follows one direction and cannot have loops or cyclical links.
Graphs are non linear structures: their data doesn’t follow an order. Trees will always be graphs, but not all graphs will be trees. Graphs do not have a concept of a root node. They can have a direction or not or they could have some links that have direction and others that don’t. Every graph must have at least one single node. (a graph with one node is called singleton).
Edges (sometimes referred to as links) can connect nodes in any way possible. Edges are what differentiates graphs. There are two types of edges: a edge that has a direction or flow, and an edge that has no direction or flow. We refer to these as directed and undirected edges, respectfully. In a directed edge, we can only travel from the origin to the destination, and never the other way around (digraph). However, it’s an entirely different story with undirected edges. In an undirected edge, the path that we can travel goes both ways. That is to say, the path between the two nodes is bidirectional, meaning that the origin and destination nodes are not fixed.
In mathematics, graphs are a way to formally represent a network, which is basically just a collection of objects that are all interconnected. For example, in mathematical terms, we describe graphs as ordered pairs. Remember high school algebra, when we learned about (x,y) ordered pair coordinates? Similar deal here, with one difference: instead of x and y, the parts of a graph instead are: v, for vertices, and e, for its edges. If our graph has more than one node and more than one edge that ordered pair — (V, E) — is actually made up of two objects: a set of vertices, and a set of edges. The “unordered” part is really important here, because remember, unlike trees, there is no hierarchy of nodes.
Facebook, a massive social network, is a type of graph. Twitter, on the other hand, works very differently from Facebook. I can follow you, but you might not follow me back.
Vaidehi Joshi, A Gentle Introduction To Graph Theory. In Medium, Retrieved from here