MATURE Deliverables Year 1
This deliverable concentrates on the results of the ethnographic study, their implications for the project as well as the revised version of the knowledge maturing model. Specifically, the ethnographic study provided rich descriptions of knowledge maturing practices, so-called Personas, long-running maturing cases, frequently used knowledge routines and hot knowledge maturing areas, stories describing changes in knowledge maturity as well as knowledge maturing indicators. The results of the activities in this work package, most notably the empirical work, converged into the refined version of the knowledge maturing model which is seen as an instrument to convey our understanding about knowledge maturing and is intended as an analytic model to help structure the analysis of organisational and technical infrastructures.
This document provides the pedagogical foundation and concept of a Personal Learning and Maturing Environment (PLME). The presented model for a PLME is basis for a work-integrated learning and maturing environment aiming at supporting the individual learner in acquiring knowledge and distributing it into his community in order to activate communication processes and becoming aware of necessary reseeding phases. The concept of the PLME was derived from theoretical research and end user requirements from MATURE’s application partners. Therefore, a theoretical model of the representation and maturing of knowledge has been derive ed based on the idea of the symbolic interactionism by Meads and Blumer. This model helps to focus on concrete knowledge maturing aspects and identifying main requirements and possibilities of supporting the learner in job-situated learning processes. The second and more practice-oriented strand of developing the PLME concept bases on ethnographically informed studies, application partner scenarios and results of former projects like the APOSDLE project. Therefore, Design Studies have been developed aiming at reflecting the scenarios and the results of the ethnographic studies and were evaluated in workshops by tests with end-users. The preconditions combined with the insights of these evaluations have been adapted to Use Cases and concluding requirements and technical services.
This document describes a model for organisational learning and maturing environments (OLMEs) that aim to support knowledge workers in collaboratively augmenting organisational knowledge and thus enabling organisations to act more successfully and adapt promptly to changes. Knowledge maturing in organisations has been investigated so far mainly from two viewpoints. One supports the careful manual construction of mature knowledge artefacts (such as e-learning documents, business process models or ontologies) that heavily relies on expert knowledge. The other view advocates a bottom-up collaborative creation of artefacts in a Web 2.0 style. However, what has received very little attention is how we can support the smooth transition from the latter to the former approach in an organisational setting by giving guidance. This is exactly the contribution of the OLME model: to identify where transitions between informally defined knowledge artefacts and more structured ones become necessary – from the point of view of the organisation’s goals – and to support these transitions by giving organisational guidance.
The purpose of this document is to provide a conceptual foundation of Maturing Services, which we take to mean intelligent software services which provide an integrated support in the knowledge maturing process. These services mostly work in the background to analyze contents, processes, structures and their use within an organization to discover emergent patterns and support individuals, communities or organizations in dealing with the complexities of these underlying structures and their evolution over time We also describe empirical work that we have conducted to understand the foundations of maturing services, and to test our initial ideas and thinking. This empirical work follows a multi-faceted research methodology that iteratively combines conceptual design of models and algorithms, ethnographic research, controlled lab and simulation studies, design studies and rapid prototyping, as well as evaluation in large scale application settings.