Thanks Matthias for the elaborations on the types of knowledge and knowledge management. It helps in distinguishing connective knowledge from other types of knowledge, which also accounts for why “knowledge management” is so difficult to define. There is also a challenge when it comes to tacit and emergent knowledge, where the management of knowledge may be perceived as a manipulation of people’s knowledge rather than data and information.
As Haridimos mentions here on tacit knowledge:
Tacit knowledge cannot be “captured”, “translated”, or “converted” but only displayed, manifested, in what we do. New knowledge comes about not when the tacit becomes explicit, but when our skilled performance – our praxis – is punctuated in new ways through social interaction (Tsoukas, 2001).
Could we actually “manage” knowledge which are connective? There is an issue of control here in connective learning, which may be in tension with openness in networked learning, if only certain knowledge are allowed to pass through the connections, whilst others are not. This is especially the case when such information (as perceived as knowledge) are kept behind closed doors, such as copyrighted artefacts, resources. Isn’t it a paradox in open learning and education?
Rita mentions about her concerns on the use of the word management in knowledge here.
What does it mean to manage personal knowledge at an organisation level? To me, making connections, interacting with others, and cooperating and collaborating with colleagues are the actual tasks that could lead up to emergent learning (and connective knowledge), but then whether this practice is to be managed at a personal level or not is debatable. We won’t manage others with knowledge, as it could be perceived as manipulation. Rather the “knowledge” we possess should not be treated as a “commodity”, though knowledge – able could become power, as in the case of organisation. I think that is the tension we have with a closed versus open model of knowledge creation in education where information (rather than knowledge) is still not shared because of many political reasons (for in breach of copy right or it is under intellectual property), or not aligning with certain traditional principles of education on privacy. So, I would go with Harold’s point of using network learning instead of PKM, and as Rita mentioned: “managing knowledge is problematic as it spans too many contexts and also activity of the mind; it is not tangible enough to manage, by for instance sticking it in boxes or writing it down on shopping lists.” Knowledge is fluid and should not be considered as a “commodity” that one could trade off with management. The sort of “knowledge” which is managed is likely information. We don’t need to manage it as a commodity.
Personal knowledge management should therefore cater for individual learning autonomy, when individuals would like to exercise personal learning choice and control in what, when, where, how and who they would like to learn with.
May be we could all manage information, and organise knowledge in a structured manner, to a certain extent. Whether such organisation of information and knowledge is useful and valuable to us will depend on the learning context. If we agree that knowledge is pattern recognition (the connection pattern and the circuit of connections), then learning is about organisation of such data or information which would allow us to recognize the pattern, through the process of immersion, navigation and traverse of the distributed knowledge networks.
Serendipitous learning (learning based on serendipity) may be an emergent phenomena in informal learning which won’t require too much pre-planning or organised learning, and could be best for creating new ideas or products. We often discover new ideas when we navigate diverse networks on the web (social, technology or learning networks). Such mode of learning provides us with the breadth of learning, and could allow for knowledge creation and growth, when we make new connections or strengthen connections with networks or tools, or connection and interaction with nodes of networks (based on people, ideas).
In this From Push to Pull: Emerging Models for Mobilizing Resources by John Hagel and John Seely Brown John and John writes:
Pull models treat people as networked creators (even when they are customers purchasing goods and services) who are uniquely positioned to transform uncertainty from a problem into an opportunity. Pull models are ultimately designed to accelerate capability building by participants, helping them to learn as well as innovate, by pursuing trajectories of learning that are tailored to their specific needs.
So, I think the pull models do exhibit many similarities with the connectivist model of learning, especially when people are the connectivist, creating and navigating through the networks, and growing “knowledge” together with the networks.
The agents (people, actors) and the network are co-evolving in this connectivist model and this gives rise to new understanding and explanation of how knowledge is created, and why knowledge is developed and grown. The product of such learning is the people, who grows with knowledge, as mentioned by Stephen in this Models of knowledge production.
Photo: Credit to Stephen’s post on Models of Knowledge Production