58,749 research outputs found

    Fife Workforce Modelling Study: Final Report

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    Future skills issues affecting industry sectors in Wales: electronics sector

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    Closing the gap between software engineering education and industrial needs

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    According to different reports, many recent software engineering graduates often face difficulties when beginning their professional careers, due to misalignment of the skills learnt in their university education with what is needed in industry. To address that need, many studies have been conducted to align software engineering education with industry needs. To synthesize that body of knowledge, we present in this paper a systematic literature review (SLR) which summarizes the findings of 33 studies in this area. By doing a meta-analysis of all those studies and using data from 12 countries and over 4,000 data points, this study will enable educators and hiring managers to adapt their education / hiring efforts to best prepare the software engineering workforce

    Research into the use of ICT and e-learning for work-based learning in the skills sector

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    This research has been commissioned by Becta to provide an evidence-based overview of the current use and effectiveness of work-based e-learning and its integration with more traditional learning methods. The specific objectives of the research were to: investigate the known impact of ICT and e-learning on the skills sector; and describe the ways in which ICT and e-learning can support key workforce development issues such as addressing skills gaps and achieving sustainability in training and development

    Research into the use of ICT and e-learning for work-based learning in the skills sector

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    The report provided an overview of the research commissioned by Becta into the use of ICT for learning by SMEs and the public sector, in the context of work-based learning (WBL). The findings were illustrated with a number of case studies and vignettes of good practice. The report was targeted at stakeholders in work-based learning (WBL)

    Advanced Cyberinfrastructure for Science, Engineering, and Public Policy

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    Progress in many domains increasingly benefits from our ability to view the systems through a computational lens, i.e., using computational abstractions of the domains; and our ability to acquire, share, integrate, and analyze disparate types of data. These advances would not be possible without the advanced data and computational cyberinfrastructure and tools for data capture, integration, analysis, modeling, and simulation. However, despite, and perhaps because of, advances in "big data" technologies for data acquisition, management and analytics, the other largely manual, and labor-intensive aspects of the decision making process, e.g., formulating questions, designing studies, organizing, curating, connecting, correlating and integrating crossdomain data, drawing inferences and interpreting results, have become the rate-limiting steps to progress. Advancing the capability and capacity for evidence-based improvements in science, engineering, and public policy requires support for (1) computational abstractions of the relevant domains coupled with computational methods and tools for their analysis, synthesis, simulation, visualization, sharing, and integration; (2) cognitive tools that leverage and extend the reach of human intellect, and partner with humans on all aspects of the activity; (3) nimble and trustworthy data cyber-infrastructures that connect, manage a variety of instruments, multiple interrelated data types and associated metadata, data representations, processes, protocols and workflows; and enforce applicable security and data access and use policies; and (4) organizational and social structures and processes for collaborative and coordinated activity across disciplinary and institutional boundaries.Comment: A Computing Community Consortium (CCC) white paper, 9 pages. arXiv admin note: text overlap with arXiv:1604.0200
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