The Collective Building of Knowledge in Collaborative Learning Environments

The intention of this chapter is to investigate how collaborative learning environments (CLEs) can be used to elicit the collective building of knowledge. This work discusses CLEs as lively cognitive systems and looks at some strategies that might contribute to the improvement of significant pedagogical practices. The study is supported by rhizome principles, whose characteristics allow us to understand the process of selecting and connecting what is relevant and meaningful for the collective building of knowledge. A brief theoretical and conceptual approach is presented and major contributions and difficulties about collaborative learning environments are discussed. New questions and future trends about the collective building of knowledge are suggested

The Role of Group Learning in Implementation of a Personnel Management System in a Hospital

A new HR system was introduced in a Dutch hospital. The system implied collaborative work among its users. The project planning seemed to be reasonably straightforward: the system's introduction was intended to take place gradually, including pilots in different departments and appropriate feedback. After some time, the system was successfully adopted by one group of users, but failed with another. We conceptualize the implementation process of groupware as group learning to frame the adoption of the system, and analyze the qualitative data collected during the longitudinal case study. We found that in the user group with strong group learning, adoption of the system occurred effectively and on time. In another user group with rather weak group learning, the use of the system was blocked after a short time. The results provided a first confirmation of our assumption about the importance of group learning processes in the implementation of groupware

The Role of Clusters in Knowledge Creation and Diffusion – an Institutional Perspective

Clusters and networks have received renewed attention in recent years not only as a tool for regional development in general but as an institution of knowledge creation and diffusion between the knowledge infrastructure of a region and the firms within the clusters. They are therefore often regarded as geographically condensed forms of economic cooperation and knowledge exchange. The recent renaissance of interest in institutions as a factor shaping economic performance has therefore also implications for the creation and sustained existence of clusters and networks as a tool for knowledge management and as learning organisations within and across regions. This institutional perspective serves to identify additional factors influencing economic behaviour leading to cooperation. Different strands of institutional thinking –institutions as “social technologies” in the tradition of evolutionary economics, clusters as a form of Coase institution integrating positive external effects of technological knowledge, the importance of knowledge sharing in the context of the “New Institutional Economics” – emphasize that connectivity cannot be effectively coordinated by conventional markets. Clusters and networks are among the non-market devices by which firms seek to coordinate their activities with other firms and other knowledge-generating institutions. But it is also important to emphasize that clusters as coordinating institutions are not automatically just there but that they are the result of an evolving process shaped by policy activities and entrepreneurial behaviour responding to new challenges. Clusters as social technologies are co-evolving with new physical technologies and are therefore in constant need to change themselves. They can be regarded as an answer to the problems of achieving agreement and coordination in a context where there is a collective interest. They combine different additional elements that are important for regional development and economic growth.

Knowledge visualization: From theory to practice

Visualizations have been known as efficient tools that can help users analyze com- plex data. However, understanding the displayed data and finding underlying knowl- edge is still difficult. In this work, a new approach is proposed based on understanding the definition of knowledge. Although there are many definitions used in different ar- eas, this work focuses on representing knowledge as a part of a visualization and showing the benefit of adopting knowledge representation. Specifically, this work be- gins with understanding interaction and reasoning in visual analytics systems, then a new definition of knowledge visualization and its underlying knowledge conversion processes are proposed. The definition of knowledge is differentiated as either explicit or tacit knowledge. Instead of directly representing data, the value of the explicit knowledge associated with the data is determined based on a cost/benefit analysis. In accordance to its importance, the knowledge is displayed to help the user under- stand the complex data through visual analytical reasoning and discovery

The long and winding road: Routine creation and replication in multi-site organizations

Prior research on organizational routines in the ‘capabilities’ literature has either studied how new routines are created during an exploratory process of variation and selection or how existing routines are replicated during a phase of exploitation. Few studies have analyzed the life cycle of new routine creation and replication as an integrated process. In an in-depth case study of England’s Highways Agency, this paper shows that the creation and replication of a new routine across multiple sites involves four sequential steps: envisioning, experimenting, entrenching and enacting. We contribute to the capabilities research in two ways: first, by showing how different organizational levels, capabilities and logics (cognitive and behavioural) shape the development of new routines; and second, by identifying how distinct evolutionary cycles of variation and selective retention occur during each step in the process. In contrast with prior research on replication as an exact copy of a template or existing routine, our study focuses on the replication of an entirely new routine (based on novel principles) that is adapted to fit local operational conditions during its large-scale replication across multiple sites. We draw upon insights from adjacent ‘practice research’ and suggest how capabilities and practice studies may complement each other in future research on the evolution of routines

How do entrepreneurs learn and engage in an online community-of-practice? A case study approach

This paper investigates the ways in which entrepreneurs use communities of practice (CoPs) to express themselves, using narrative theory and rhetorical analysis, to gain insight into an electronic social network medium, namely, YoungEntrepreneur.com. In particular, the study focuses on CoPs themes, including why entrepreneurs engage in CoPs, what role the moderators and resident entrepreneurs can play in managing online CoPs, on communication rituals of the knowledge sharing through interactivity, and on ‘how to develop an intervention’ to maintain and stimulate entrepreneurs for engaging in an online community. Findings reveal that the topic title plays a major role in attracting people. Successful topics with successful conclusions (in terms of the original query that was answered) will not necessarily get high responses and vice versa. It is observed that the domain expert does not play a big role in keeping the discussion going. Finally, the study also discovered that entrepreneurs like to communicate in a story telling genre. A comprehensive set of engagement measurement tools are introduced to effectively measure the engagement in a virtual CoP, along with a classification to define and categorise discourse of messages in terms of content and context, which allow practitioners to understand the effectiveness of a social networking site

Knowledge hubs and knowledge clusters: Designing a knowledge architecture for development.

With globalisation and knowledge-based production, firms may cooperate on a global scale, outsource parts of their administrative or productive units and negate location altogether. The extremely low transaction costs of data, information and knowledge seem to invalidate the theory of agglomeration and the spatial clustering of firms, going back to the classical work by Alfred Weber (1868-1958) and Alfred Marshall (1842-1924), who emphasized the microeconomic benefits of industrial collocation. This paper will argue against this view and show why the growth of knowledge societies will rather increase than decrease the relevance of location by creating knowledge clusters and knowledge hubs. A knowledge cluster is a local innovation system organized around universities, research institutions and firms which successfully drive innovations and create new industries. Knowledge hubs are localities with high internal and external networking and knowledge sharing capabilities. Both form a new knowledge architecture within an epistemic landscape of knowledge creation and dissemination, structured by knowledge gaps and areas of low knowledge intensity. The paper will focus on the internal dynamics of knowledge clusters and knowledge hubs and show why clustering takes place despite globalisation and the rapid growth of ICT. The basic argument that firms and their delivery chains attempt to reduce transport (transaction) costs by choosing the same location is still valid for most industrial economies, but knowledge hubs have different dynamics relating to externalities produced from knowledge sharing and research and development outputs. The paper draws on empirical data derived from ongoing research in the Lee Kong Chian School of Business, Singapore Management University and in the Center for Development Research (ZEF), University of Bonn, supported by the German Aeronautics and Space Agency (DLR).

Where Is Science Going?

Do researchers produce scientific and technical knowledge differently than they did ten years ago? What will scientific research look like ten years from now? Addressing such questions means looking at science from a dynamic systems perspective. Two recent books about the social system of science, by Ziman and by Gibbons, Limoges, Nowotny, Schwartzman, Scott, and Trow, accept this challenge and argue that the research enterprise is changing. This article uses bibliometric data to examine the extent and nature of changes identified by these authors, taking as an example British research. We use their theoretical frameworks to investigate five characteristics of research said to be increasingly pervasive-namely, application, interdisciplinarity, networking, internationalization, and concentration of resources. Results indicate that research may be becoming more interdisciplinary and that research is increasingly conducted more in networks, both domestic and international; but the data are more ambiguous regarding application and concentration. CR - Copyright © 1996 Sage Publications, Inc

A market based approach for resolving resource constrained task allocation problems in a software development process

We consider software development as an economic activity, where goods and services can be modeled as a resource constrained task allocation problem. This paper introduces a market based mechanism to overcome task allocation issues in a software development process. It proposes a mechanism with a prescribed set of rules, where valuation is based on the behaviors of stakeholders such as biding for a task. A bid process ensures that a stakeholder, who values the resource most, will have it allocated for a limited number of times. To observe the bidders behaviors, we initiate an approach incorporated with a process simulation model. Our preliminary results support the idea that our model is useful for optimizing the value based task allocations, creating a market value for the project assets, and for achieving proper allocation of project resources specifically on large scale software projects