788 resultados para 130212 Science Technology and Engineering Curriculum and Pedagogy
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Data mining is one of the most important analysis techniques to automatically extract knowledge from large amount of data. Nowadays, data mining is based on low-level specifications of the employed techniques typically bounded to a specific analysis platform. Therefore, data mining lacks a modelling architecture that allows analysts to consider it as a truly software-engineering process. Bearing in mind this situation, we propose a model-driven approach which is based on (i) a conceptual modelling framework for data mining, and (ii) a set of model transformations to automatically generate both the data under analysis (that is deployed via data-warehousing technology) and the analysis models for data mining (tailored to a specific platform). Thus, analysts can concentrate on understanding the analysis problem via conceptual data-mining models instead of wasting efforts on low-level programming tasks related to the underlying-platform technical details. These time consuming tasks are now entrusted to the model-transformations scaffolding. The feasibility of our approach is shown by means of a hypothetical data-mining scenario where a time series analysis is required.
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Policy-makers often fret about the low number of university graduates in the fields of science, technology, engineering and mathematics (STEM). Proposed solutions often focus on providing better information for students and parents about the employability or average wages of different fields to emphasise that STEM professions pay. This paper argues that, from a personal point of view, students are actually making rational decisions, if all benefits and costs are factored into the equation. The authors conclude, therefore, that public policy needs to change the incentives to induce students to enter these fields and not just provide information about them.
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Folded cover.
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Subtitle varies.
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Updates and replaces the pre-college portions of NSF 68-24, Released textbooks, films, and other teaching materials.
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"Serial D."
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"No. 122."
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"No. 29."
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World textile abstracts
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"No. 130."
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Includes bibliographies and indexes.
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United Nations publication. Sales no. : 63.I.21-[63.I.28]"
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Mode of access: Internet.
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Mode of access: Internet.
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"Printed for the use of the Committee on Science and Technology."