20,360 research outputs found

    Flexible Global Software Development (GSD): Antecedents of Success in Requirements Analysis

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    Globalization of software development has resulted in a rapid shift away from the traditional collocated, on-site development model, to the offshoring model. Emerging trends indicate an increasing interest in offshoring even in early phases like requirements analysis. Additionally, the flexibility offered by the agile development approach makes it attractive for adaptation in globally distributed software work. A question of significance then is what impacts the success of offshoring earlier phases, like requirements analysis, in a flexible and globally distributed environment? This article incorporates the stance of control theory to posit a research model that examines antecedent factors such as requirements change, facilitation by vendor and client site-coordinators, control, and computer-mediated communication. The impact of these factors on success of requirements analysis projects in a “flexible” global setting is tested using two quasi-experiments involving students from Management Development Institute, India and Marquette University, USA. Results indicate that formal modes of control significantly influence project success during requirements analysis. Further, facilitation by both client and vendor site coordinators positively impacts requirements analysis success

    Devolution and education

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    They include:     School/Site-based decision making/Management  School/Site-based autonomy  Self-Managing Schools  Autonomy for local schools  Decentralised/Site-based management    Essentially it concerns the distribution of power and funding between governments and schools and structural changes in the governance, management and financing of schools. Internationally there are significant differences in how it operates but there is general consensus amongst advocates of such initiatives that they will improve school effectiveness and student learning outcomes by producing better educational decision-making; improving school management and leadership; improving quality of teaching; leading to a more responsive curriculum; and producing more efficient use of resources

    The educational research-practice interface revisited

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    The question of how the realms of research and practice might successfully relate to one another is a persisting one, and especially so in education. The article takes a fresh look at this issue by using the terminology of collaboration scripts to reflect upon various forms of this relationship. Under this perspective, several approaches towards bridging the research/ practice gap are being described with regard to the type and closeness of interaction between the two realms. As different focuses and blind spots become discernible, the issue is raised concerning which 'script' might be appropriate depending upon the starting conditions of research interacting with practice

    Supporting connectivism in knowledge based engineering with graph theory, filtering techniques and model quality assurance

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    [EN] Mass-customization has forced manufacturing companies to put significant efforts to digitize and automate their engineering and production processes. When new products are to be developed and introduced the production is not alone to be automated. The application of knowledge regarding how the product should be designed and produced based on customer requirements also must be automated. One big academic challenge is helping industry to make sure that the background knowledge of the automated engineering processes still can be understood by its stakeholders throughout the product life cycle. The research presented in this paper aims to build an infrastructure to support a connectivistic view on knowledge in knowledge based engineering. Fundamental concepts in connectivism include network formation and contextualization, which are here addressed by using graph theory together with information filtering techniques and quality assurance of CAD-models. The paper shows how engineering knowledge contained in spreadsheets, knowledge-bases and CAD-models can be penetrated and represented as filtered graphs to support a connectivistic working approach. Three software demonstrators developed to extract filtered graphs are presented and discussed in the paper.The work presented has evolved during the IMPACT project, funded by the Swedish Knowledge Foundation, and has been partly presented on three conferences [8-10]. The three conference papers show the rendering of graphs for CAD-models, spread sheets and KBE-rules together with the first case example in this article. The work has also been partially supported by grant DPI2017-84526-R (MINECO/AEI/FEDER, UE), project CAL-MBE.Johansson, J.; Contero, M.; Company, P.; Elgh, F. (2018). Supporting connectivism in knowledge based engineering with graph theory, filtering techniques and model quality assurance. Advanced Engineering Informatics. 38:252-263. https://doi.org/10.1016/j.aei.2018.07.005S2522633

    Linking Policy Research and Practice in 'STIG Systems': Many Obstacles, but Some Ways Forward

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    This paper reflects on the relevance of systems thinking about the interdependent policy issues bearing on the dynamics of science, technology and innovation in their relationship to economic growth. Considering the approach that characterizes much of the current economics literatures treatment of technology and growth policies, we pose the critical question: what kind of systems paradigm is likely to prove particularly fruitful in that particular problem-domain: Evolutionary, neo-Schumpeterian, and complex system dynamics approaches are conceptually attractive and we analyze their respective virtues while also acknowledging their more serious problematic features. Those become visible quickly when trying connect systems-relevant research with practical policy-making in this field. Not content to have simply identified some significant obstructions in the path toward that goal, the paper also suggests some potentially feasible ways forward.Techonological Change, systems paradigm, STIG systems,
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