58,767 research outputs found
Closing the gap between software engineering education and industrial needs
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
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
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
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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