1,006 research outputs found

    Searching for effective and efficient way of knowledge transfer within an organization

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    In this paper three models of knowledge transfer in organization are considered. In the first model (A) the transfer of chunks of knowledge among agents is possible only when the sender has exactly one more chunks of knowledge than recipient. This is not dissimilar with bounded confidence model of opinion dynamics. In the second model (B) the knowledge transfer take place when sender is "smarter" than recipient. Finally, in the third scenario (model C) we allow for knowledge transfer also when sender posses the same or greater number of chunks of knowledge as recipient. The simulation bases on cellular automata technique. The organization members occupy nodes of square lattice and they interact only with their nearest neighbors. With computer simulations we show, that the efficiency and the effectiveness of knowledge transfer i) for model C is better than for model B ii) and it is worse for model A than for model B.Comment: 8 pages, 5 figures (in 19 files), for 10th International Conference on Agents and Artificial Intelligenc

    Understanding Mathematics and Science Advice Networks of Middle School Teachers

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    We report findings from a research project designed to examine the mathematics and science advice networks of teachers who participated in professional development under the auspices of the NSF-funded Rocky Mountain-Middle School Math and Science Partnership. We provide descriptive statistics of results. Additionally, we reflect on the research process and discuss some of the practical challenges involved

    Advice seeking network structures and the learning organization

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    Organizational learning can be described as a transfer of individualsā€™ cognitive mental models to shared mental models. Employees, seeking the same colleagues for advice, are structurally equivalent, and the aim of the paper is to study if the concept can act as a conduit for organizational learning. It is argued that the mimicking of colleaguesā€™ advice seeking structures will induce structural equivalence and transfer the accuracy of individualsā€™ cognitive mental models to shared mental models. Taking a dyadic level of analysis authors revisit a classical case and present novel data analyses.The empirical results indicate that the mimicking of advice seeking structures can alter cognitive accuracy. It is discussed the findingsā€™ implications for organization learning theory and practice, addressed the studyā€™s limitations, and suggested avenues for future research

    Discovering academics' key learning connections: An ego-centric network approach to analysing learning about teaching

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    The aim of this exploratory study is to investigate the role of personal networks in supporting academicsā€™ professional learning about teaching. As part of a wider project, the paper focuses on the composition of academicsā€™ networks and possible implications of network tendencies for academicsā€™ learning about teaching. The study adopts a mixed-method approach. Firstly, the composition of academicsā€™ networks is examined using Social Network Analysis. Secondly, the role of these networks in academicsā€™ learning about teaching is analysed through semi-structured interviews. Findings reveal the prevalence of localised and strong-tie connections, which could inhibit opportunities for effective learning and spread of innovations in teaching. The study highlights the need to promote connectivity within and across institutions, creating favourable conditions for effective professional development

    Understanding Teacher Leadership in Middle School Mathematics: A Collaborative Research Effort

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    We report ļ¬ndings from a collaborative research effort designed to examine how teachers act as leaders in their schools. We ļ¬nd that teachers educated by the Math in the Middle Institute act as key sources of advice for colleagues within their schools while drawing support from a network consisting of other teachers in the program and university-level advisors. In addition to reporting on our ļ¬ndings, we reļ¬‚ect on our research process, noting some of the practical challenges involved, as well as some of the beneļ¬ts of collaboration

    Knowledge transfer in a tourism destination: the effects of a network structure

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    Tourism destinations have a necessity to innovate to remain competitive in an increasingly global environment. A pre-requisite for innovation is the understanding of how destinations source, share and use knowledge. This conceptual paper examines the nature of networks and how their analysis can shed light upon the processes of knowledge sharing in destinations as they strive to innovate. The paper conceptualizes destinations as networks of connected organizations, both public and private, each of which can be considered as a destination stakeholder. In network theory they represent the nodes within the system. The paper shows how epidemic diffusion models can act as an analogy for knowledge communication and transfer within a destination network. These models can be combined with other approaches to network analysis to shed light on how destination networks operate, and how they can be optimized with policy intervention to deliver innovative and competitive destinations. The paper closes with a practical tourism example taken from the Italian destination of Elba. Using numerical simulations the case demonstrates how the Elba network can be optimized. Overall this paper demonstrates the considerable utility of network analysis for tourism in delivering destination competitiveness.Comment: 15 pages, 2 figures, 2 tables. Forthcoming in: The Service Industries Journal, vol. 30, n. 8, 2010. Special Issue on: Advances in service network analysis v2: addeded and corrected reference
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