Dynamical Aspects of Knowledge Evolution

Abstract

Undeniably, in this rapidly changing world some knowledge granules change over time. Tracking these changes seems to be one of the most crucial processes in knowledge management. Every potential change is a result of knowledge adoption and application to solve a given problem or task in particular domains. However, there is a lack of a model that provides an eventdriven framework, along with the core adoption process explicitly expressed with related factors, which together serve as an efficient tool to adopt and reuse knowledge on one hand, while on the other, to measure and evaluate the various aspects of knowledge quality and usefulness. This paper aims to fill this gap by introducing a knowledge adoption process and an ontology-aided encapsulation knowledge (OAKE) model. While the former breaks down the tacit adoption process into two explicit sub-processes and measurable factors, the latter exposes knowledge evolution over time by a sequence of recorded events.

University Students’ Research on Artificial Intelligence and Knowledge Management. A Review and Report of Multi-case Studies

“…Potentially, investigations of students very often lead to prototypes of solutions that are directly connected with AI methods and direct or indirect references to KM areas [2,3]. Therefore the understanding of the importance of these solutions among young people is widely known.…”

A Note on Knowledge Management Education: Towards Implementing Active Learning Methods

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