Tuesday, June 05, 2007

The Web 2.0 Driven SECI Model Based Learning Process



The program of the 7th IEEE International Conference of Advanced Learning Technologies (ICALT 2007) is now available. I´ll be presenting our paper "The Web 2.0 Driven SECI Model Based Learning Process".

Abstract:

Nonaka and his knowledge transformation model SECI revolutionized the thinking about organizations as social learning systems. He introduced technical concepts like hypertext into organizational theory. Now, after 15 years Web 2.0 concepts seem to be an ideal fit with Nonaka’s SECI approach opening new doors for more personal, dynamic, and social learning on a global scale. In this paper, we present an extended view of blended learning which includes the combination of formal and informal learning, knowledge management, and Web 2.0 concepts into one integrated solution, by discussing what we call the Web 2.0 driven SECI model based learning process.

Extract from the paper: SECI model based learning process


Learning and knowledge management are increasingly similar in terms of input, outcome, processes, activities, components, tools, concepts, and terminologies and can thus be viewed as two sides of the same coin. Nonaka and Takeuchi adopt a dynamic model of knowledge management, view knowledge as activity rather than object and focus on knowledge creation, collaboration and practice. This knowledge creation model has been referred to as the SECI model.

The basis of this model is a distinction between two types of human knowledge: explicit and tacit. Explicit knowledge or information is codified, objective knowledge that can be transmitted in formal, systematic language. In contrast, tacit knowledge is not easily codified, difficult to express and subjective. Nonaka and Takeuchi argue that knowledge is created and expanded through the social interaction of tacit and explicit knowledge [13]. Similar to the knowledge creation process, the learning process encompasses more than knowledge acquisition. It is a dynamic process within a collective intelligence, continuous knowledge in action, and cyclic conversion of tacit and explicit knowledge. This spiraling, highly dynamic and complex process is modeled in the figure above. It consists of four modes of knowledge conversion: socialization (tacit to tacit), externalization (tacit to explicit), combination (explicit to explicit), and internalization (explicit to tacit). Each of these modes will be discussed in detail below within a learning context, along with actual examples on how various Web 2.0 concepts and emerging technologies can be applied and used in conjunction with one another to support each mode of the learning process.

Nonaka and Takeuchi point out that an individual can acquire tacit knowledge directly from others without using language. Socialization is the process of sharing tacit knowledge, i.e. the rich and untapped knowledge that resides in individuals such as know-how, expertise, understandings, experiences and skills resulting from previous activities, not through language but through observation, imitation, practice, and participation in different formal and informal communities. According to them, the socialization mode starts with building a “field” or “space” of social interaction. Social media provide great opportunities to build such spaces and hand on tacit knowledge from one person to another.

Externalization is a process of articulating tacit knowledge into explicit concepts. It is generally based on metaphors, analogies, concepts, hypotheses, and models. According to Nonaka and Takeuchi, externalization holds the key to knowledge creation, because it creates new, explicit concepts from tacit knowledge. Blogs for example support the externalization process by giving voice to everyone and providing a space to capture personal knowledge and distributed discussions across blogs, immediately document thoughts, and annotate information. The nature of knowledge is such that we always tell more than we can write down [14]. Consequently, tacit knowledge that may be expressed but cannot be easily recorded into formal documents and manuals can be verbalized via oral communications. VoIP and phone/video-conferencing for example are powerful tools to trigger externalization via open participation, dialogue, and discussion. Social media in general offer unique means for effective capturing of context-rich and quality knowledge as it gets created, with a minimum amount of effort. Collaboration contextualizes content. For example, discussions around a blog post through comments and trackbacks give more context to the codified knowledge. And, recording of phone/video-conferences and instant messaging sessions support the online capturing of context-rich knowledge as it gets created. The collective intelligence ensures that knowledge is up-to-date and relevant. In fact, knowledge captured by many is much more likely to be of better value. Wikis are good examples of the collective intelligence at work. They provide an opportunity for social interaction and collaborative knowledge capturing. Knowledge can be expressed and captured through different possible modes of representation and expression including words, spoken or written; image, still and moving; video; music etc. Each medium has its own affordances, its own systems of representation, and its own strategies for representing knowledge [12][15]. Consequently, learners need to reflect across media; that is get familiar with a range of different media tools and determine which is most effective in capturing their knowledge. This is however not a big challenge, since today’s teenagers and kids are growing up digital and are comfortable with various media. Emergent social media provide learners with effective ways to capture and publish their knowledge in a number of ways and in a variety of media such as pictures, video or audio recordings. Knowledge capturing and publishing becomes easier through increasingly better devices that can capture high-quality audio and video.

Combination is the process of systematizing concepts into a knowledge system, and it integrates different bodies of explicit knowledge. Once knowledge is captured, it becomes explicit knowledge i.e. information that can be stored and accessed. Unlike traditional centralized learning object repositories, blogs and wikis build distributed community information stores with up-to-date, context-rich, and searchable learning assets. The captured information can then be transferred within a social context. Blogs and wikis allow quick and wide information dissemination across classroom and organization boundaries. Pod/vodcasting is growing in popularity as a powerful tool to share audio and video recordings. RSS is a successful technology that makes it easy to share resources across networks, as it brings content from different sources (e.g. new blog posts, podcasts) to a learner’s personal space, once she has subscribed to the feed source. The captured information can also be managed individually or collectively. A blog is a very valuable tool for personal information management and wikis and folksonomies are highly effective forms of collaborative information management. During the combination process, reconfiguration of existing explicit knowledge through adding, reorganizing, and combining, can lead to new knowledge, possibly more complex. Other Web 2.0 technologies such as mashups can be used to pull together content from more than one source, remix and assemble it to form a new service.

Since information is available in different forms such as texts, images, sounds, and videos, we need federated search technologies that make it possible to perform search across media and plug into multiple distributed repositories to locate relevant learning resources with a single query. We further need social and community-oriented search technology that builds on the collective intelligence to locate quality resources and services as well as appropriate communities and experts. The collective intelligence decides what is valuable through filtering, rating, feedback, reviews, criticisms, and recommendations and supports the certification of people’s expertise and the assessment of individual digital reputation. Amazon’s review and recommendation system, YouTube’s rating scheme, Google’s PageRank algorithm, eBay’s feedback, Flickr and Del.icio.us’ social tagging, Digg’s voting are successful examples of the collective intelligence at work. The search result should be modular content that can be remixed and aggregated to generate personalized learning resources, third-party lightweight services that can be mashed up to form adapted learning services, personal learning environments (PLE) that can be connected to build a learning community, and small communities that can be networked to create interdisciplinary learning clusters.

According to Nonaka and Takeuchi, internalization is the process of embodying explicit knowledge into tacit knowledge. Explicit knowledge is internalized into individual’s tacit knowledge bases in the form of mental models or technical know-how. Learning by doing triggers internalization. Bringing learners competitively and cooperatively together via multi-player games and multi-user simulations offer the potential to learn through a new form of social experience. Games encourage us to take risks and learn through trial and error. Simulations broaden the kinds of learning experiences we can acquire by getting a chance to see and experiment things in a safe environment that would be impossible in the real world [12]. Internalization is also a process of continuous individual and collective reflection. Effective reflection requires the mastery of different skills such as the ability to see connections and recognize patterns and the capacity to make sense between fields, ideas, and concepts [10].


References:

[10] G. Siemens, Knowing Knowledge, Lulu.com, ISBN: 978-1-4303-0230-8.

[12] H. Jenkins et al., Confronting the challenges of participatory culture, MacArthur Foundation, 2006.

[13] I. Nonaka and H. Takeuchi, The Knowledge-Creating Company, New York: Oxford University, 1995.

[14] D. Snowden, Complex Acts of Knowing - Paradox and Descriptive Self Awareness, Journal of Knowledge Management, Special Issue, July 2002.

[15] G. Kress, Literacy in the New Media Age, New York: Routledge, 2003.

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