Learning as the Networking of explicit/tacit Knowledge Nodes

Building on my previous post „From Knowledge Worker to Knowledge Networker“, I argue here that learning is the networking of knowledge nodes. A distinction that is often cited in the literature is made between explicit and tacit knowledge. Explicit knowledge (or information) is systematic knowledge that is easily codified in formal language and objective. In contrast, tacit knowledge is hard to formalize, difficult to communicate and subjective (Nonaka and Takeuchi, 1995). Consequently, we have two types of knowledge nodes:

• Explicit knowledge nodes are different explicit knowledge assets available in a variety of forms such as texts, images, sounds, videos and captured in distributed information repositories such as blogs, wikis, pod/vodcasts etc.

• Tacit knowledge nodes are diverse social networks and communities. There are different types of frequently overlapping, formal and informal communities including learning communities, communities of practice, and communities of interest.

In my opinion, learning is the networking of explicit/tacit knowledge nodes. What we are trying to do all the time is either to pull together explicit knowledge from more than one source, reflect, detect patterns, remix and assemble it to form a new explicit knowledge asset or to expand our personal social networks by connecting to different communities to create and share tacit knowledge in a collaborative way, through participation, dialogue, discussion, observation, and imitation.